System and method for creating lead compounds, and compositions thereof

Abstract

A method for selecting from a chemical space a chemical structure that reacts with, or catalyses, a target molecule utilising computational and / or combinatorial computers implemented algorithmic search techniques to permit computer simulation of such a reaction or catalysis wherein the chemical space comprises a protein, the DNA or RNA sequence thereof, or a protein generated from said DNA or RNA sequences.

Description

[0001] SYSTEM AND METHOD FOR CREATING LEAD COMPOUNDS, AND COMPOSITIONS THEREOF

[0002] BACKGROUND OF THE RELEVANT PRIOR ART

[0003] One or more embodiments of the invention generally relate to novel computational and / or combinatorial computer-implemented algorithmic search techniques for chemical structures, moieties, formulas and / or the like for in-silica, e.g., performed via computer simulation in reference to biological or biochemical experiments, etc., lead generation. More particularly, certain embodiments of the invention relate to algorithms to search for chemical formulas that react with, or catalyse, a given chemical formula as a new and useful step for in-silica lead generation of drugs outside known parts of vast chemical space, e.g., referring to the property space spanned by all possible molecules and chemical compounds adhering to a given set of construction principles and boundary conditions. The following back- ground information may present examples of specific aspects of the prior art (e.g., without limitation, approaches, facts, or common wisdom) that, while expected to be helpful to further educate the reader as to additional aspects of the prior art, is not to be construed as limiting the present invention, or any embodiments thereof, to anything stated or implied therein or inferred thereupon. Chemical space is a concept in cheminformatics referring to the property space spanned by all possible molecules and chemical compounds adhering to a given set of construction principles and boundary conditions. It contains millions of compounds which are readily accessible and available to researchers. It is a library used in the method of molecular docking. [Source: Rudling, Axel; Gustafsson, Robert; Almlbf, Ingrid; Homan, Evert; Scobie, Martin; Warpman Berglund, Ulrika; Helleday, Thomas; Stenmark, Pal; Carlsson, Jens (2017-10-12). "Fragment-Based Discovery and Optimization of Enzyme Inhibitors by Docking of Commercial Chemical Space". Journal of Medicinal Chemistry. 60 (19): 8160- 8169. doi:10.1021 / acs.jmedchem.7b01006]. A chemical space often referred to in cheminformatics is that of potential pharmacologically active molecules. Its size is estimated to be in the order of 1060molecules. Currently, there are no widely-accepted rigorous methods by the scientific community for determining the precise size of this space. The assumptions [source: Bohacek, R. S.; C. McMartin; W. C. Guida (1999). "The art and practice of structure-based drug design: A molecular modelling perspective". Medicinal Research Reviews (1): 3-50] used for estimating the number of potential pharmacologically active molecules, however, use the Lipinski rules, in particular the molecular weight limit of 500. The estimate also restricts the chemical elements used to be Carbon, Hydrogen, Oxygen, Nitrogen and Sulfur. It further makes the assumption of a maximum of 30 atoms to stay below 500 Daltons, allows for branching and a maximum of 4 rings and arrives at an estimate of 1063. This number is often misquoted in subsequent publications to be the estimated size of the whole organic chemistry space, [source: Kirkpatrick, P.; C. Ellis (2004). "Chemical space". Nature. 432 (432): 823-865.] which would be much larger if including the halogens and other elements. However, there is a formula for the number of graphs of a certain kind [source: Omer Gimenez & Marc Noy, “Asymptotic Enumeration and Limit Laws of Planar Graphs”, Journal of the American Mathematical Society, 2009.

[0004] The following is an example of a specific aspect in the prior art that, while expected to be helpful to further educate the reader as to additional aspects of the prior art, is not to be construed as limiting the present invention, or any embodiments thereof, to anything stated or implied therein or inferred thereupon. By way of educational background, another aspect of the prior art generally useful to be aware of is that chemical libraries used for laboratorybased screening for compounds with desired properties are examples for real-world chemical libraries of small size (a few hundred to hundreds of thousands of molecules).

[0005] Systematic exploration of chemical space is possible by creating in-silica databases of virtual molecules, [source: L. Ruddigkeit; R. van Deursen; L. C. Blum; J.-L. Reymond (2012). "Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB- 17". J. Chem. Inf. Model. 52 (11): 2864-2875] which may be visualized by projecting multidimensional property space of molecules in lower dimensions. [Source: M. Awale; R. van Deursen; J. L. Reymond (2013). "MQN-Mapplet: Visualization of Chemical Space with Interactive Maps of DrugBank, ChEMBL, PubChem, GDB-11 , and GDB-13". J. Chem. Inf. Model. 53 (2): 509-18; L. Ruddigkeit; L. C. Blum; J.-L. Reymond (2013). "Visualization and Virtual Screening of the Chemical Universe Database GDB-17". J. Chem. Inf. Model. 53 (1): 56-65.] Generation of chemical spaces may involve creating stoichiometric combinations of electrons and atomic nuclei to yield all possible topology isomers for the given construction principles. In cheminformatics, software programs called "structure generators" may be used to generate the set of all chemical structure adhering to given boundary conditions. Constitutional isomer generators, for example, may generate all possible constitutional isomers of a given molecular gross formula.

[0006] In the real world, chemical reactions allow us to move in chemical space. The mapping between chemical space and molecular properties may often not be unique, meaning that there may be very different molecules exhibiting very similar properties. Materials design and drug discovery both involve the exploration of chemical space.

[0007] In view of the foregoing, it is clear that these traditional techniques may not be sufficient to effectively utilize currently available computational resources to best and most efficiently navigate the vastness of chemical space and thus leave room for more optimal approaches to successfully retrieve chemical formula information. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:

[0009] FIG. 1A illustrates a simple graph, a multigraph, and a molecular graph, respectively, in accordance with an embodiment of the present invention.

[0010] FIG. 1 B illustrates a flowchart of an exemplary method of inputting a chemical formula and / or a by-product formula to obtain a desired list of outcomes, e.g., including related formulas, amino acids, proteins, and / or further direction concerning multiple additional related searches and so on and so forth, in accordance with an embodiment of the present invention.

[0011] FIG. 2 illustrates a flowchart of an exemplary method of inputting a formula into a chemical search interface to search for atoms, molecules, chemical structures and / or compounds, etc., to calculate an index of the input formula, in accordance with an embodiment of the present invention.

[0012] FIG. 3 illustrates a flowchart of an exemplary method of how to use a formula search for high throughput screening in accordance with an embodiment of the present invention.

[0013] FIG. 4A illustrates a flowchart of an exemplary method of how to make a formula search for high throughput screening, in accordance with an embodiment of the present invention.

[0014] FIG. 4B illustrates a flowchart of an exemplary method of how to make a computational and / or combinatorial algorithm for that shown in FIG. 4A, in accordance with an embodiment of the present invention.

[0015] FIG. 40 illustrates a flowchart of an exemplary method of how a pharmaceutical company or other interested party and / or entity may use the computational and / or combinatorial algorithm shown in FIG. 4B, in accordance with an embodiment of the present invention.

[0016] FIG. 5 illustrates a flowchart of an exemplary method of how to calculate an index for that shown in FIG. 3, in accordance with an embodiment of the present invention.

[0017] FIG. 6 illustrates a flowchart of an exemplary method of an index calculation operation, in accordance with an embodiment of the present invention.

[0018] FIG. 7 illustrates a flowchart of an exemplary method of a sub-enumeration calculation operation, in accordance with an embodiment of the present invention.

[0019] FIG. 8 illustrates a flowchart of an exemplary method of algorithm interpretation regarding bonds between atoms, in accordance with an embodiment of the present invention. FIG. 9 illustrates a flowchart of an exemplary method of calculating and / or identifying an isomer with a maximum number of hydrogen atoms, in accordance with an embodiment of the present invention.

[0020] FIG. 10 illustrates a flowchart of an exemplary method of calculating and / or identifying an isomer with a second-highest number of valences, in accordance with an embodiment of the present invention.

[0021] FIG. 11 illustrates a flowchart of an exemplary method of that included in the "second highest valence loop body" shown in FIG. 10, in accordance with an embodiment of the present invention.

[0022] FIG. 12 illustrates an exemplary chemical reaction, in accordance with an embodiment of the present invention.

[0023] FIG. 13A-B illustrate an example structure of benzene, in accordance with an embodiment of the present invention.

[0024] FIG. 14 illustrates a table of search results to target benzene, in accordance with an embodiment of the present invention.

[0025] FIG. 15 illustrates a flowchart of an exemplary method of a search for NAPBQI, a toxic byproduct produced during the xenobiotic metabolism of the analgesic paracetamol, in accordance with an embodiment of the present invention.

[0026] FIG. 16 illustrates a table of enzyme displayed in codified format, in accordance with an embodiment of the present invention.

[0027] FIG. 17 illustrates a block diagram depicting an exemplary client / server system which may be used by an exemplary web-enabled / networked embodiment of the present invention.

[0028] FIG. 18 illustrates a block diagram depicting a conventional client / server communication system, which may be used by an exemplary web-enabled / networked embodiment of the present invention.

[0029] FIG. 19 illustrates an exemplary flowchart configured to provide a structure diagram list, in accordance with an embodiment of the present invention.

[0030] FIG. 20 illustrates an exemplary flowchart configured to determine drug like formulas, in accordance with an embodiment of the present invention.

[0031] FIG. 21 illustrates an exemplary flowchart configured to select a drug formula that inhibit protein that may cause drug resistance, in accordance with an embodiment of the present invention.

[0032] FIG. 22 illustrates an exemplary group of compounds configured to be formulated in the form of an intraocular injectable solution, in accordance with an embodiment of the present invention. Unless otherwise indicated illustrations in the figures are not necessarily drawn to scale.

[0033] DETAILED DESCRIPTION OF THE INVENTION

[0034] The present invention is best understood by reference to the detailed figures and description set forth herein.

[0035] In a first embodiment, there is provided a method for selecting from a chemical space a chemical structure that reacts with, or catalyses, a target molecule utilising computational and / or combinatorial computer-implemented algorithmic search techniques to permit computer simulation of such a reaction or catalysis wherein the chemical space comprises a protein, the DNA or RNA sequence thereof, or a protein generated from said DNA or RNA sequences: which method comprises the steps of: analysing the protein to identify an index associated with the peptides present; inputting a peptide to search for and the protein associated index identified, into an executable program stored on a non-transitory computer-readable storage medium, wherein the program instructs one or more processors to perform a method comprising: steps for inputting a peptide to search for; steps for inputting a list of valences required for each atom; steps for inputting a list of atoms comprising the space to search; steps for calculating the index associated with the peptides present, a constant number index step; steps for enumerating all sums which add to precisely a constant number corresponding to the result of employing a partition algorithm based upon certain atomic numbers and said constant number index step; steps for determining the quantity of a first atom; steps for Subenumerating to choose the other atoms wherein said Sub-enumerating steps recursively calls itself; steps for branch testing iform in said Sub-enumerate steps, which defers H quantity to last; steps for calculating an H quantity in Isomer with a maximum hydrogen; steps for interpreting a formula as all non-fragment isomers of said formula, wherein bonds between two atoms are either single, double or triple, and Isomers with rings are allowed as well as non-cyclic isomers and isomers of any topology, and wherein a canonical isomer comprises a maximum number of H or valence 1 atoms; steps for configuring atoms in a line with highest valence atoms at both ends, single bonded to form a canonical isomer; steps for adding a double bond, triple bond or ring will reduce number of H by an even number; steps for branch testing maximum h, which compares canonical isomer to a putative partition, wherein if test false leaves odd number of H, all isomers of this kind are optionally simultaneously to be rejected, and if test true, prints the formula with numbers of each atom specified; steps for calculating a maximum hydrogen number, wherein the first branch skips H itself and any omitted atoms, and wherein said maximum hydrogen number steps loops over other atoms to find maximum valence, incrementing said maximum hydrogen number in the loop, except valence 1 are decremented; steps for calculating a second highest valence, in which branches test if there is a solitary atom then determines that N has the second highest valence, and in which a branch on i skips H and any omitted atoms once again; and steps for generating a final chemical structure, moieties, or formulas for in-silico analysis; and, filtering the final chemical structure, moieties, or formulas, based on a selected chemical structure exhibiting the same, or a similar index by mass.

[0036] In a preferred embodiment, the method may further comprise inputting the filtered chemical structure into a computer simulation to carry out biological or biochemical experiments as a means for lead generation.

[0037] In a preferred embodiment, the method may further comprise the steps for presenting the Periodic Table up to atomic number 48, being 24 spin up and 24 spin down.

[0038] Preferably, wherein the mass filtering step in the computational and / or combinatorial computer-implemented algorithmic search follows the sequence:

[0039]

[0040] In a particularly preferred embodiment, the method further comprises subjecting the filtered chemical structure to a SMILES string analysis. Preferably, the SMILES string analysis in the computational and / or combinatorial computer-implemented algorithmic search follows the sequence:

[0041] SUBSTITUTE SHEET (RULE 26)

[0042] In a further preferred embodiment, the chemical structure sought functions to inhibit a protein and the method comprises; determining a first index such that the protein does not metabolise the target molecule, and inputting the first index determined into the computational and / or combinatorial computer-implemented algorithmic search.

[0043] SUBSTITUTE SHEET (RULE 26) More preferably, the chemical structure sought is such that drug resistance from the protein is reduced or eliminated. In this embodiment, the method further comprises: determining a second index such that drug resistance from the protein is reduced or eliminated and inputting the second index determined into the computational and / or combinatorial computer-implemented algorithmic search.

[0044] In a further preferred embodiment, the computational and / or combinatorial computer- implemented algorithmic search technique following the sequence:

[0045] More preferably, in this embodiment, the chemical space to be investigated may be reduced to a list of peptides, preferably dipeptides and / or tripeptides. The method according to the present invention may preferably be utilised to select a chemical structure that reacts

[0046] SUBSTITUTE SHEET (RULE 26) with, or catalyses, a target molecule that represents sensations of sight for a person whose visual system is impaired or damaged and exhibiting a similar function to neurotransmitter molecules in the eye, brain or central nervous system of a human, from a chemical space comprising protein, the DNA or RNA sequence thereof, or a protein generated from said DNA or RNA sequences, utilising computational and / or combinatorial computer-implemented algorithmic search techniques to permit computer simulation of such a reaction or catalysis.

[0047] In this embodiment, the method comprises the steps of: analysing the protein to identify an index associated with the peptides present; inputting a peptide to search for and the protein associated index identified, into an executable program stored on a non-transitory computer-readable storage medium, wherein the program instructs one or more processors to perform a method comprising: steps for inputting a peptide to search for; steps for inputting a list of valences required for each atom; steps for inputting a list of atoms comprising the space to search; steps for calculating the index associated with the peptides present, a constant number index step; steps for enumerating all sums which add to precisely a constant number corresponding to the result of employing a partition algorithm based upon certain atomic numbers and said constant number index step; steps for determining the quantity of a first atom; steps for Subenumerating to choose the other atoms wherein said Sub-enumerating steps recursively calls itself; steps for branch testing iform in said Sub-enumerate steps, which defers H quantity to last; steps for calculating an H quantity in Isomer with a maximum hydrogen; steps for interpreting a formula as all non-fragment isomers of said formula, wherein bonds between two atoms are either single, double or triple, and Isomers with rings are allowed as well as non-cyclic isomers and isomers of any topology, and wherein a canonical isomer comprises a maximum number of H or valence 1 atoms; steps for configuring atoms in a line with highest valence atoms at both ends, single bonded to form a canonical isomer; steps for adding a double bond, triple bond or ring will reduce number of H by an even number; steps for branch testing maximum h, which compares canonical isomer to a putative partition, wherein if test false leaves odd number of H all isomers of this kind are optionally simultaneously be rejected, and if test true prints the formula with numbers of each atom specified; steps for calculating a maximum hydrogen number, wherein the first branch skips H itself and any omitted atoms, and wherein said maximum hydrogen number steps loops over other atoms to find maximum valence, incrementing said maximum hydrogen number in the loop, except valence 1 are decremented; steps for calculating a second highest valence, in which branches test if there is a solitary atom then determines that N has the second highest valence, and in which a branch on i skips H and any omitted atoms once again; and steps for generating a final chemical structure, moieties, or formulas for in-silico analysis; and, filtering the final chemical structure, moieties, or formulas, based on a selected chemical structure exhibiting the same, or a similar index by mass.

[0048] Preferably, the method may further comprise subjecting the filtered chemical structure to a SMILES string analysis.

[0049] More preferably the method according to this aspect of the present invention may further comprise the steps of creating synthetic molecules that represent sensations of sight for a person whose visual system is impaired or damaged; selecting a compound using tabulated three indices, so that not all belong to a first index, and a second or third index not zero; such structures with a similar function to neurotransmitter molecules in the eye, brain and central nervous system; the aforesaid indices depending on structure diagrams and exact placement of Hydrogen atoms not usually shown in chemical structure diagrams.

[0050] Embodiments of the invention are discussed below with reference to the Figures. However, those skilled in the art will readily appreciate that the detailed description given herein with respect to these figures is for explanatory purposes as the invention extends beyond these limited embodiments. For example, it should be appreciated that those skilled in the art will, in light of the teachings of the present invention, recognize a multiplicity of alternate and suitable approaches, depending upon the needs of the particular application, to implement the functionality of any given detail described herein, beyond the particular implementation choices in the following embodiments described and shown. That is, there are modifications and variations of the invention that are too numerous to be listed but that all fit within the scope of the invention. Also, singular words should be read as plural and vice versa and masculine as feminine and vice versa, where appropriate, and alternative embodiments do not necessarily imply that the two are mutually exclusive.

[0051] It is to be further understood that the present invention is not limited to the particular methodology, compounds, materials, manufacturing techniques, uses, and applications, described herein, as these may vary. It is also to be understood that the terminology used herein is used for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention. It must be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include the plural reference unless the context clearly dictates other- wise. Thus, for example, a reference to "an element" is a reference to one or more elements and includes equivalents thereof known to those skilled in the art. Similarly, for another example, a reference to "a step" or "a means" is a reference to one or more steps or means and may include sub-steps and subservient means. All conjunctions used are to be understood in the most inclusive sense possible. Thus, the word "or" should be understood as having the definition of a logical "or" rather than that of a logical "exclusive or" unless the context clearly necessitates otherwise. Structures described herein are to be understood also to refer to functional equivalents of such structures. Language that may be construed to express approximation should be so under- stood unless the context clearly dictates otherwise.

[0052] All words of approximation as used in the present disclosure and claims should be construed to mean "approximate," rather than "perfect," and may accordingly be employed as a meaningful modifier to any other word, specified parameter, quantity, quality, or concept. Words of approximation, include, yet are not limited to terms such as "substantial", "nearly", "almost", "about", "generally", "largely", "essentially", "closely approximate", etc.

[0053] It should also be noted that such words of approximation as contemplated in the foregoing clearly limits the scope of claims such as saying 'generally parallel' such that the adverb 'generally' does not broaden the meaning of parallel.

[0054] Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art to which this invention belongs. Preferred methods, techniques, devices, and materials are described, although any methods, techniques, devices, or materials similar or equivalent to those described herein may be used in the practice or testing of the present invention. Structures described herein are to be understood also to refer to functional equivalents of such structures. The present invention will be described in detail below with reference to embodiments thereof as illustrated in the accompanying drawings.

[0055] References to a "device," an "apparatus," a "system," etc., in the preamble of a claim should be construed broadly to mean "any structure meeting the claim terms" exempt for any specific structure(s) / type(s) that has / (have) been explicitly disavowed or excluded or admitted / implied as prior art in the present specification or incapable of enabling an object / aspect / goal of the invention. Further- more, where the present specification discloses an object, aspect, function, goal, result, or advantage of the invention that a specific prior art structure and / or method step is similarly capable of performing yet in a very different way, the present invention disclosure is intended to and shall also implicitly include and cover additional corresponding alter- native embodiments that are otherwise identical to that explicitly disclosed except that they exclude such prior art structure(s) / step(s), and shall accordingly be deemed as providing sufficient disclosure to support a corresponding negative limitation in a claim claiming such alternative embodiment(s), which exclude such very different prior art structure(s) / step(s) way(s).

[0056] From reading the present disclosure, other variations and modifications will be apparent to persons skilled in the art. Such variations and modifications may involve equivalent and other features which are already known in the art, and which may be used instead of or in addition to features already described herein.

[0057] Features which are described in the context of separate embodiments may also be provided in combination in a single embodiment. Conversely, various features which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination. Further, repeated use of the phrase "in one embodiment," or "in an exemplary embodiment," "an embodiment," do not necessarily refer to the same embodiment, although they may. Moreover, any use of phrases like "embodiments" in connection with "the invention" are never meant to characterize that all embodiments of the invention must include the particular feature, structure, or characteristic, and should instead be understood to mean "at least some embodiments of the invention" include the stated particular feature, structure, or characteristic.

[0058] References to "user", or any similar term, as used herein, may mean a human or nonhuman user thereof. Moreover, "user", or any similar term, as used herein, unless expressly stipulated otherwise, is contemplated to mean users at any stage of the usage process, to include, without limitation, direct user(s), intermediate user(s), indirect user (s), and end user(s).

[0059] References to "end user", or any similar term, as used herein, is generally intended to mean late-stage user(s) as opposed to early stage user(s). Hence, it is contemplated that there may be a multiplicity of different types of "end user" near the end stage of the usage process.

[0060] In some situations, some embodiments of the present invention may provide beneficial usage to more than one stage or type of usage in the foregoing usage process. In such cases where multiple embodiments targeting various stages of the usage process are described, references to "end user", or any similar term, as used therein, are generally intended to not include the user that is the furthest removed, in the foregoing usage process, from the final user therein of an embodiment of the present invention.

[0061] References to "person", "individual", "human", "a party", "animal", "creature", or any similar term, as used herein, even if the context or particular embodiment implies living user, maker, or participant, it should be understood that such characterizations are sole by way of example, and not limitation, in that it is contemplated that any such usage, making, or participation by a living entity in connection with making, using, and / or participating, in any way, with embodiments of the present invention may be substituted by such similar performed by a suitably configured non-living entity, to include, without limitation, automated machines, robots, humanoids, computational systems, information processing systems, artificially intelligent systems, and the like. It is further contemplated that those skilled in the art will readily recognize the practical situations where such living makers, users, and / or participants with embodiments of the present invention may be in whole, or in part, replaced with such non-living makers, users, and / or participants with embodiments of the present invention.

[0062] Headings provided herein are for convenience and are not to be taken as limiting the disclosure in any way.

[0063] The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.

[0064] It is understood that the use of specific component, device and / or parameter names are for example only and not meant to imply any limitations on the invention. The invention may thus be implemented with different nomenclature / terminology utilized to describe the mechanisms / units / structures / components / devices / parameters herein, without limitation. Each term utilized herein is to be given its broadest interpretation given the context in which that term is utilized.

[0065] Terminology

[0066] The following paragraphs provide definitions and / or context for terms found in this disclosure (including the appended claims):

[0067] "Comprising" and "contain" and variations of them-Such terms are open-ended and mean "including but not limited to".

[0068] "Configured To." Various units, circuits, or other components may be described or claimed as "configured to" perform a task or tasks. In such contexts, "configured to" or "operable for" is used to connote structure by indicating that the mechanisms / units / circuits / components include structure (e.g., circuitry and / or mechanisms) that performs the task or tasks during operation. As such, the mechanisms / unit / circuit / component may be said to be configured to (or be operable) for perform(ing) the task even when the specified mechanisms / unit / circuit / component is not currently operational (e.g., is not on).

[0069] "Based On." As used herein, this term is used to describe one or more factors that affect a determination. This term does not foreclose additional factors that may affect a determination.

[0070] The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

[0071] All terms of exemplary language (e.g., including, without limitation, "such as", "like", 'for example", "for instance", "similar to", etc.) are not exclusive of any other, potentially, unrelated, types of examples; thus, implicitly mean "by way of example, and not limitation...", unless expressly specified otherwise.

[0072] Unless otherwise indicated, all numbers expressing conditions, concentrations, dimensions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term "about."

[0073] The term "comprising," which is synonymous with "including," "containing," or "characterized by" is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. "Comprising" is a term of art used in claim language which means that the named claim elements are essential, but other claim elements may be added and still form a construct within the scope of the claim.

[0074] As used herein, the phase "consisting of' excludes any element, step, or ingredient not specified in the claim.

[0075] With respect to the terms "comprising," "consisting of," and "consisting essentially of," where one of these three terms is used herein, the disclosed and claimed subject matter may include the use of either of the other two terms. Thus in some embodiments not otherwise explicitly recited, any instance of "comprising" may be replaced by "consisting of or, alternatively, by "consisting essentially of', and thus, for the purposes of claim support and construction for "consisting of' format claims, such replacements operate to create yet other alternative embodiments "consisting essentially of' only the elements recited in the original "comprising" embodiment to the exclusion of all other elements.

[0076] Definitions

[0077] Reference to the term "chemistry" generally implies the scientific discipline involved with elements and compounds composed of atoms, molecules and ions: their composition, structure, properties, behavior and the changes they undergo during a reaction with other substances. In the scope of its subject, chemistry occupies an intermediate position between physics and biology. It is sometimes called the central science because it provides a foundation for understanding both basic and applied scientific disciplines at a fundamental level analysis, e.g. spectroscopy and chromatography. Scientists engaged in chemical research are known as chemists. Most chemists specialize in one or more sub-disciplines.

[0078] Reference to the term "chemical reaction" generally implies a process that leads to the chemical transformation of one set of chemical substances to another mechanism. Chemical reactions are described with chemical equations, which symbolically present the starting materials, end products, and sometimes intermediate products and reaction conditions. Chemical reactions happen at a characteristic reaction rate at a given temperature and chemical concentration. Typically, reaction rates increase with increasing temperature because there is more thermal energy available to reach the activation energy necessary for breaking bonds between atoms. Reactions may proceed in the forward or reverse direction until they go to completion or reach equilibrium. Reactions that proceed in the forward direction to approach equilibrium are often described as spontaneous, requiring no input of free energy to go forward. Non-spontaneous reactions require input of free energy to go forward (examples include charging a battery by applying an external electrical power source, or photosynthesis driven by absorption of electromagnetic radiation in the form of sun- light), decays, and reactions between elementary particles, as described by quantum field theory.

[0079] Reference to the term "chemical equation" generally implies the symbolic representation of a chemical reaction in the form of symbols and formulae, wherein the reactant entities are given on the left-hand side and the product entities on the right-hand side.

[0080] Reference to the term "chemical engineering" generally implies a branch of engineering that uses principles of chemistry, physics, mathematics, biology, and economics to efficiently use, produce, design, transport and transform energy and materials. The work of chemical engineers may range from the utilization of nano-technology and nano- materials in the laboratory to large-scale industrial processes that convert chemicals, raw materials, living cells, microorganisms, and energy into useful forms and products, of the cell also depends on the reactions of smaller molecules and ions. These may be inorganic, for example water and metal ions, or organic, for example the amino acids, which are used to synthesize proteins. The mechanisms by which cells harness energy from their environment via chemical reactions are known as metabolism. The findings of bio- chemistry are applied primarily in medicine, nutrition, and agriculture. In medicine, biochemists investigate the causes and cures of diseases. In nutrition, they study how to maintain health wellness and study the effects of nutritional deficiencies. In agriculture, biochemists investigate soil and fertilizers, and try to discover ways to improve crop cultivation, crop storage and pest control.

[0081] Reference to the term "molecular genetics" implies the field of biology that studies the structure and function of genes at a molecular level and thus employs methods of both molecular biology and genetics. The study of chromosomes and gene expression of an organism may give insight into heredity, genetic variation, and mutations. This is useful in the study of developmental biology and in understanding and treating genetic diseases.

[0082] Reference to the term "proteins" generally implies large biomolecules, or macromolecules, consisting of one or more long chains of amino acid residues. Proteins perform a vast array of functions within organisms, including catalyzing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells and organisms, and transporting molecules from one location to another. Proteins differ from one another primarily in their sequence of amino acids, which is dictated by the nucleotide sequence of their genes, and which usually results in protein folding into a specific three-dimensional structure that determines its activity. A linear chain of amino acid residues is called a polypeptide. A protein contains at least one long polypeptide. Short polypeptides, containing less than 20-30 residues, are rarely considered to be proteins and are commonly called peptides, or sometimes oligopeptides.

[0083] Reference to the term "metabolism" generally implies the set of life-sustaining chemical reactions in organisms. The three main purposes of metabolism are: the conversion of food to energy to run cellular processes; the conversion of food / fuel to building blocks for proteins, lipids, nucleic acids, and some carbohydrates; and the elimination of nitrogenous wastes.

[0084] Reference to the term "biochemical engineering" generally implies a field of study with roots stemming from chemical engineering and biological engineering. It mainly deals with the design, construction, and advancement of unit processes that involve biological organisms or organic molecules and has various applications in areas of interest such as biofuels, food, pharmaceuticals, biotechnology, and water treatment processes, and statistical measures that assess relationships among members of large data sets. For example, there are methods to locate a gene within a sequence, to predict protein structure and / or function, and to cluster protein sequences into families of related sequences. The primary goal of bioinformatics is to increase the under- standing of biological processes.

[0085] Reference to the term "cheminformatics" generally implies the use of computer and informational techniques applied to a range of problems in the field of chemistry. These in silica techniques are used, for example, in pharmaceutical companies and academic settings in the process of drug discovery. These methods may also be used in chemical and allied industries in various other forms. The primary application of cheminformatics is in the storage, indexing and search of information relating to compounds. The efficient search of such stored information includes topics that are dealt with in computer science as data mining, information retrieval, information extraction and machine learning. Related research topics include: unstructured data; information retrieval; information extraction; structured data mining and mining of structured data; database mining; graph mining; molecule mining; sequence mining; tree mining; and, digital libraries. Chemical data may pertain to real or virtual molecules. Virtual libraries of compounds may be generated in various ways to explore chemical space and hypothesize novel compounds with desired properties. Virtual libraries of classes of compounds (drugs, natural products, diversity-oriented synthetic products) were recently generated using the FOG (fragment optimized growth) algorithm. This was done by using cheminformatic tools to train transition probabilities of a Markov chain on authentic classes of compounds, and then using the Markov chain to generate novel compounds that were similar to the training database.

[0086] Reference to the term "in silica" (e.g., pseudo-latin for "in silicon", alluding to the mass use of silicon for computer chips) generally implies an expression meaning "performed on computer or via computer simulation" in reference to biological experiments.

[0087] Reference to the term "drug discovery" generally implies he process by which new candidate medications are discovered.

[0088] Reference to the term "computational science" generally implies a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems.

[0089] Reference to the term "chemical graph theory" generally implies the topology branch of mathematical chemistry which applies graph theory to mathematical modelling of chemical phenomena.

[0090] Reference to the term "data mining" generally implies the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a com- prehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.

[0091] Reference to the term "chemical space" generally implies a concept in cheminformatics referring to the property space spanned by all possible molecules and chemical compounds adhering to a given set of construction principles and boundary conditions. It contains millions of compounds which are readily accessible and available to researchers. It is a library used in the method of molecular docking.

[0092] Reference to the term "docking" in molecular modeling generally implies a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex.

[0093] Reference to the term "structure mining" generally implies the process of finding and extracting useful information from semi-structured data sets. Graph mining, sequential pattern mining and molecule mining are special cases of structured data mining.

[0094] Reference to the term "molecule mining" generally implies that since molecules may be represented by molecular graphs, this capability is strongly related to graph mining and structured data mining.

[0095] Reference to the term "sequential pattern mining" generally implies a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. It is usually presumed that the values are discrete, and thus time series mining is closely related, but usually considered a different activity. Sequential pattern mining is a special case of structured data mining.

[0096] Reference to the term "chemical genomics" generally implies the systematic screening of targeted chemical libraries of small molecules against individual drug target families (e.g., GPCRs, nuclear receptors, kinases, proteases, etc.) with the ultimate goal of identification of novel drugs and drug targets. Typically, some members of a target library have been well characterized where both the function has been determined and compounds that modulate the function of those targets (ligands in the case of receptors, inhibitors of enzymes, or blockers of ion channels) have been identified. Other members of the target family may have unknown function with no known ligands and hence are classified as orphan receptors. By identifying screening hits that modulate the activity of the less well characterized members of the target family, the function of these novel targets may be elucidated.

[0097] Reference to the term "computational chemistry" generally implies a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures and proper- ties of molecules and solids.

[0098] Reference to the term "information engineering" generally implies the engineering discipline that deals with the generation, distribution, analysis, and use of information, data, and knowledge in systems. The field first became identifiable in the early 21st century. The components of information engineering include more theoretical fields such as machine learning, artificial intelligence, control theory, signal processing, and information theory, and more applied fields such as computer vision, natural language processing, bioinformatics, medical image computing, cheminformatics, autonomous robotics, mobile robotics, and telecommunications.

[0099] Reference to the term "molecular design software" generally implies software for molecular modeling, that provides special support for developing molecular models de nova. In contrast to the usual molecular modeling programs, such as for molecular dynamics and quantum chemistry, such software directly supports the aspects related to constructing molecular models, including: molecular graphics; interactive molecular drawing and conformational editing; building polymeric molecules, crystals, and solvated systems; partial charges development; geometry optimization; and, support for the different aspects of force field development.

[0100] Reference to the term "molecular graphics" generally implies the discipline and philosophy of studying molecules and their properties through graphical representation. Reference to the term "molecular modelling" generally implies methods, theoretical and computational, used to model or mimic the behavior of molecules. The methods are used in the fields of computational chemistry, drug design, computational biology and materials science to study molecular systems ranging from small chemical systems to large biological molecules and material assemblies. The simplest calculations may be performed by hand, but inevitably computers are required to perform molecular modelling of any reasonably sized system. The common feature of molecular modelling methods is the atomistic level description of the molecular systems. This may include treating atoms as the smallest individual unit (a molecular mechanics approach), or explicitly modelling protons and neutrons with its quarks, anti-quarks and gluons and electrons with its photons (a quantum chemistry approach).

[0101] Reference to the term "nanoinformatics" generally implies the application of informatics to nanotechnology. It is an interdisciplinary field that develops methods and software tools for understanding nanomaterials, their properties, and their interactions with biological entities, and using that information more efficiently. It differs from chem- informatics in that nanomaterials usually involve nonuniform collections of particles that have distributions of physical properties that must be specified. The nanoinformatics infrastructure includes ontologies for nanomaterials, file formats, and data repositories.

[0102] Reference to the term "enzymes" generally implies macromolecular biological catalysts that accelerate chemical reactions. The molecules upon which enzymes may act are called substrates, and the enzyme converts the substrates into different molecules known as products. Almost all metabolic processes in the cell need enzyme catalysis in order to occur at rates fast enough to sustain life.

[0103] Reference to the term "isomer" generally implies ions or molecules with identical formulas but distinct structures. Isomers do not necessarily share similar properties. Two main forms of isomerism are structural isomerism (or constitutional isomerism) and stereoisomerism (or spatial isomerism).

[0104] Reference to the term "structural analog" generally implies a chemical analog or simply an analog, is a com- pound having a structure similar to that of another compound, but differing from it in respect to a certain component. It may differ in one or more atoms, functional groups, or substructures, which are replaced with other atoms, groups, or substructures. A structural analog may be imagined to be formed, at least theoretically, from the other compound. Structural analogs are often isoelectronic.

[0105] Reference to the term "stereoisomerism" generally implies a form of isomerism in which molecules have the same molecular formula and sequence of bonded atoms (constitution), but differ in the three-dimensional orientations of their atoms in space. This contrasts with structural isomers, which share the same molecular formula, but the bond connections or their order differs. By definition, molecules that are stereoisomers of each other represent the same structural isomer.

[0106] Reference to the term "euclidean distance" generally implies the "ordinary" straight- line distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm.

[0107] Reference to the term "benzene" generally implies an organic chemical compound with the chemical formula C6H6. The benzene molecule is composed of six carbon atoms joined in a ring with one hydrogen atom attached to each. As it contains only carbon and hydrogen atoms, benzene is classed as a hydrocarbon.

[0108] Reference to the term "dipeptide" generally implies an organic compound derived from two amino acids. The constituent amino acids may be the same or different. When different, two isomers of the dipeptide are possible, depending on the sequence. Several dipeptides are physiologically important, and some are both physiologically and commercially significant. A well-known dipeptide is aspartame, an artificial sweetener.

[0109] Dipeptides are white solids. Many are far more water-soluble than the parent amino acids. For example, the dipeptide Ala-Gin has the solubility of 586 g / L more than 10x the solubility of Gin (35 g / L). Dipeptides also may exhibit different stabilities, e.g. with respect to hydrolysis. Gin does not withstand, sterilization procedures, whereas this dipeptide does. Because dipeptides are prone to hydro- lysis, the high solubility is exploited in infusions, i.e. to provide nutrition.

[0110] Devices or system modules that are in at least general communication with each other need not be in continuous communication with each other, unless expressly specified otherwise. In addition, devices or system modules that are in at least general communication with each other may communicate directly or indirectly through one or more intermediaries. Moreover, it is understood that any system components described or named in any embodiment or claimed herein may be grouped or sub-grouped (and accordingly implicitly renamed) in any combination or sub-combination as those skilled in the art may imagine as suitable for the particular application, and still be within the scope and spirit of the claimed embodiments of the present invention.

[0111] A description of an embodiment with several com ponents in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the present invention.

[0112] As is well known to those skilled in the art many careful considerations and compromises typically must be made when designing for the optimal manufacture of a commercial implementation any system, and in particular, the embodiments of the present invention. A commercial implementation in accordance with the spirit and teachings of the present invention may configured according to the needs of the particular application, whereby any aspect(s), feature(s), function(s), result(s), component s), approach (es), or step(s) of the teachings related to any described embodiment of the present invention may be suitably omit- ted, included, adapted, mixed and matched, or improved and / or optimized by those skilled in the art, using their average skills and known techniques, to achieve the desired implementation that addresses the needs of the particular application.

[0113] In the following description and claims, the terms "coupled" and "connected," along with their derivatives, may be used. It should be understood that these terms are not intended as synonyms for each other. Rather, in particular embodiments, "connected" may be used to indicate that two or more elements are in direct physical or electrical contact with each other. "Coupled" may mean that two or more elements are in direct physical or electrical contact. How- ever, "coupled" may also mean that two or more elements are not in direct contact with each other, but yet still cooperate or interact with each other.

[0114] A "computer" may refer to one or more apparatus and / or one or more systems that are capable of accepting a structured input, processing the structured input according to prescribed rules, and producing results of the processing as output.

[0115] Those of skill in the art will appreciate that where appropriate, some embodiments of the disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Where appropriate, embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications net- work. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0116] "Software" may refer to prescribed rules to operate a computer. Examples of software may include: code segments in one or more computer-readable languages; graphical and or / textual instructions; applets; pre-compiled code; interpreted code; compiled code; and computer programs.

[0117] The example embodiments described herein may be implemented in an operating environment comprising computer-executable instructions (e.g., software) installed on a computer, in hardware, or in a combination of software and hardware. The computerexecutable instructions may be written in a computer programming language or may be embodied in firmware logic. If written in a programming language conforming to a recognized standard, such instructions may be executed on a variety of hardware platforms and for interfaces to a variety of operating systems.

[0118] Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0119] A network is a collection of links and nodes (e.g., multiple computers and / or other devices connected together) arranged so that information may be passed from one part of the network to another over multiple links and through various nodes. Examples of networks include the Internet, the public switched telephone network, the global Telex network, computer networks (e.g., an intranet, an extranet, a local-area network, or a wide-area network), wired net- works, and wireless networks.

[0120] The Internet is a worldwide network of computers and computer networks arranged to allow the easy and robust exchange of information between computer users. Hundreds of millions of people around the world have access to computers connected to the Internet via Internet Service Providers (ISPs). Content providers (e.g., website owners or operators) place multimedia information (e.g., text, graphics, audio, video, animation, and other forms of data) at specific locations on the Internet referred to as webpages. Websites comprise a collection of connected, or otherwise related, webpages. The combination of all the websites and their corresponding webpages on the Internet is generally known as the World Wide Web (WWW) or simply the Web.

[0121] Aspects of the present invention are described below with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0122] The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures.

[0123] These computer program instructions may also be stored in a computer readable medium that may direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0124] Further, although process steps, method steps, algorithms or the like may be described in a sequential order, such processes, methods and algorithms may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any order practical. Further, some steps may be performed simultaneously.

[0125] It will be readily apparent that the various methods and algorithms described herein may be implemented by, e.g., appropriately programmed general purpose computers and computing devices. Typically, a processor (e.g., a micro-processor) will receive instructions from a memory or like device, and execute those instructions, thereby performing a process defined by those instructions. Further, programs that implement such methods and algorithms may be stored and transmitted using a variety of known media.

[0126] When a single device or article is described herein, it will be readily apparent that more than one device / article (whether or not they cooperate) may be used in place of a single device / article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device / article may be used in place of the more than one device or article.

[0127] The functionality and / or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality / features. Thus, other embodiments of the present invention need not include the device itself. The term "computer-readable medium" as used herein refers to any medium that participates in providing data (e.g., instructions) which may be read by a computer, a processor or a like device. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media.

[0128] Various forms of computer readable media may be involved in carrying sequences of instructions to a processor. For example, sequences of instruction (i) may be delivered from RAM to a processor, (ii) may be carried over a wireless transmission medium, and / or (iii) may be format- ted according to numerous formats, standards or protocols, such as Bluetooth, TDMA, CDMA, 3G.

[0129] Where databases are described, it will be under- stood by one of ordinary skill in the art that (i) alternative database structures to those described may be readily employed, (ii) other memory structures besides databases may be readily employed. Any schematic illustrations and accompanying descriptions of any sample databases presented herein are exemplary arrangements for stored representations of information.

[0130] A "computer system" may refer to a system having one or more computers, where each computer may include a computer-readable medium embodying software to operate the computer or one or more of its components.

[0131] A "network" may refer to a number of computers and associated devices that may be connected by communication facilities. A network may involve permanent connections such as cables or temporary connections such as those made through telephone or other communication links.

[0132] As used herein, the "client-side" application should be broadly construed to refer to an application, a page associated with that application, or some other resource or function invoked by a client-side request to the application. A "browser" as used herein is not intended to refer to any specific browser (e.g., Internet Explorer, Safari, Firefox, or the like), but should be broadly construed to refer to any client-side rendering engine that may access and display Internet-accessible resources, as native code, by providing hooks into another application, by facilitating use of the mechanism as a plug-in, by linking to the mechanism, and the like.

[0133] Exemplary networks may operate with any of a number of protocols, such as Internet protocol (IP), asynchronous transfer mode (ATM), and / or synchronous optical network (SONET), user datagram protocol (UDP), IEEE 802.x, etc.

[0134] Embodiments of the present invention may include apparatuses for performing the operations disclosed herein. An apparatus may be specially constructed for the desired purposes, or it may comprise a general-purpose device selectively activated or reconfigured by a program stored in the device. Embodiments of the invention may also be implemented in one or a combination of hardware, firmware, and software. They may be implemented as instructions stored on a machine-readable medium, which may be read and executed by a computing platform to perform the operations described herein.

[0135] More specifically, as will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident soft- ware, micro-code, etc.) or an embodiment combining soft- ware and hardware aspects that may all generally be referred to herein as a "circuit," "module" or "system." Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable pro- gram code embodied thereon.

[0136] In the following description and claims, the terms "computer program medium" and "computer readable medium" may be used to generally refer to media such as, but not limited to, removable storage drives, a hard disk installed in hard disk drive, and the like. These computer program products may provide software to a computer system. Embodiments of the invention may be directed to such computer program products.

[0137] An algorithm is here, and generally, considered to be a self-consistent sequence of acts or operations leading to a desired result. These include physical manipulations of physical quantities.

[0138] Unless specifically stated otherwise, and as may be apparent from the following description and claims, it should be appreciated that throughout the specification descriptions utilizing terms such as "processing," "computing," "calculating," "determining," or the like, refer to the action and / or processes of a computer or computing system, or similar electronic computing device, that manipulate and / or transform data represented as physical, such as electronic, quantities within the computing system's registers and / or memories into other data similarly represented as physical quantities within the computing system's memories, registers or other such information storage, transmission or display devices.

[0139] In a similar manner, the term "processor" may refer to any device or portion of a device that processes electronic data from registers and / or memory to transform that electronic data into other electronic data that may be stored in registers and / or memory. A "computing platform" may comprise one or more processors.

[0140] Embodiments within the scope of the present disclosure may also include tangible and / or non-transitory computer-readable storage media for carrying or having computerexecutable instructions or data structures stored thereon. Such non-transitory computer- readable storage media may be any available media that may be accessed by a general purpose or special purpose computer, including the functional design of any special purpose processor as discussed above.

[0141] Introduction

[0142] Background

[0143] "Enumerating molecules is a mind-boggling problem that has fascinated chemists and mathematicians alike for more than a century. Taking the definition from various dictionaries, to enumerate means (1) "to name things separately, one by one", and (2) "to determine the number of, to count." Interestingly enough, both definitions have been taken when enumerating molecules. Historically, the latter definition was first used, and mathematical solutions were devised to count molecules. Some of the solutions developed were not only valuable to chemists but to mathematicians as well. Indeed, as we shall see in this chapter, while trying to solve the problem of counting the isomers of paraffin structures' or counting substituted aromatic com- pounds, important concepts in graph theory and combinatorics were developed. The terms graph and tree were even coined in a chemistry context.

[0144] About four decades ago, with the advance of computer science, researchers started to look at the former definition of enumeration, and devised computer codes to explicitly list molecules. Again, while studying this challenging problem, important concepts in computer science were developed. Artificial intelligence textbooks generally quote DENDRAL, a code to enumerate molecules, as the first expert system. Historically, molecular enumeration has brought a fertile ground of research between chemistry, mathematics, and computer science. Still today new concepts and techniques are being developed at the interstice of these fields. Enumerating molecules is not only an interesting academic exercise but has practical applications as well. The foremost application of enumeration is structure elucidation. Ideally, the ... chemist collects experimental data (NMR, MS, IR, . . . ) for an unknown compound, the data is fed to a code, and the resulting unique structure is given back. Although such a streamlined picture is not yet fully automated, and may never be, there are commercial codes that may, for instance, list all structures matching a given molecular formula, an IR spectrum, or an NMR spectrum. Another important application is in molecular design. Here the problem is to design compounds (drugs, for example) that optimize some physical, chemical, or biological property or activity. Although not as prolific as structure elucidation, molecular design has introduced some novel stochastic solutions to molecular enumeration. Finally, with the advent of combinatorial chemistry, molecular enumeration takes a central role as it allows computational chemists to construct virtual libraries, test hypotheses, and provide guidance to design optimal combinatorial experiments." [Source: https: / / prod- ng.sandia.gov / techlib-noauth / access-control. cgi / 2004 / 040960.pdf; retrieved on: 08-06-19], "The term enumerating has been used in the literature for both listing molecules one by one and determining the number of molecules corresponding to a given set of constraints." [Source: https: / / prod-ng.sandia.gov / techlib-no-auth / access-control.cgi / 2004 / 040960.pdf, retrieved on: 08-06-19],

[0145] FIG. 1A illustrates multiple graphs 100A, including: a simple graph 102A, a multigraph 104A, and a molecular graph 106A, respectively, in accordance with an embodiment of the present invention. "A simple graph G is defined as an ordered pair G=(V(G),E(G)), where V V(G) is a nonempty set of elements called vertices, and E=E(G) is a set of unordered pairs of distinct element of V called edges. In most cases of chemical interest^] the sets V and E are finite .... Of course, there is a relationship between graphs and chemical structures .... [Simple graph 102A] may, for instance, be viewed as a representation of cyclohexane. But there are molecules that do not fit the simple graph picture. A multigraph is a graph where the edge set is not necessarily composed of distinct pair of vertices, in other words, multiple edges are allowed in a multigraph. A multigraph is without a loop when vertices are not allowed to be paired with themselves. [Multigraph 104A] is a representation of benzene. In a simple graph or a multigraph, the degree of a vertex is the number of edges attached to it, and the multiplicity of an edge is the number of times that edge occur in the graph ... [Simple graph 102A] contains vertices of degree 1 and 4, and all edges have multiplicity 1 ; in [multigraph 104A] the vertices have degrees 1 and 4 and the edges have multiplicities 1 and 2. The degree sequence of a graph or a multigraph is the sequence of numbers of vertices having a given degree starting with degree O and ending with the maximum degree for all vertices . . . [Simple graph 102A] has no vertices of degree 0, 12 vertices of degree 1 , no vertices of degree 2 and degree 3, and 6 vertices of degree 4, the degree sequence is (0,12,0,0,6). Graph (b) has the degree sequence (0,6, 0,0, 6)." [Source: https: / / prod-ng.san- dia.gov / techlib-noauth / access-control.cgi / 2004 / 040960.pdf, retrieved on: 08-06-19],

[0146] "While [multigraph 104A] could correspond uniquely to benzene, one cannot distinguish 1 ,2-dichlorobenzene from 1 ,4-dichlorobenzene using this representation. To make the distinction between the two compounds one has to attach to each vertex, a label, or color, that is unique to each element of the periodic table (for instance, the atomic symbol). Finally, in a molecular structure, atoms are always connected through some bonds, in other words, a molecular structure is in one piece. A molecular graph is thus defined as a connected multigraph with vertices colored by the atomic symbols of the periodic table. We use the term color instead of label since, as we shall see next, labeled graphs have a specific definition in graph theory. [Molecular graph 106A] is the molecular graph of 1 ,2- dichlorobenzene. Clearly, in a molecular graph, each vertex is an atom and each edge is a bond. The terms atom valence replace the terms vertex degree, and bond order replace edge multiplicity. Note that with the exception of rare gases, a molecular graph comprises more than one atom. Because molecular graphs are connected, their valence sequences start with valence 1 and usually end with valences 4 or 5 for most organic compounds. The valence sequence of benzene is (6, 0,0, 6)." [Source: https: / / prod-ng.sandia.gov / techlib-no- auth / access-control.cgi / 2004 / 040960.pdf, retrieved on: 08-06-19],

[0147] Building upon the general framework described above regarding identifying and numerically quantifying chemical structures and molecules as "graphs" suitable for subsequent calculation and manipulation, a multitude of theories and computational processes exist for the navigation of chemical space and location of individual searched- for chemical species and / or entities. Such efforts attempt to meet sizable industry demand in the area, provided that there is a need to: (1) characterize vast chemical space; and, (2) conveniently and reliably navigate chemical space. For instance, such problems, prior to the advent of sophisticated and powerful modem computers, appeared entirely intractable, e.g., the chemical space for (an enzyme for) benzene is two raised to power 6,441 possible isomers of 114 atoms from C, H, N, O.

[0148] It is understood that the development of pharmaceutical drugs, products, therapies and / or the like may cost upwards millions or even several billions of dollars. Effective computer-implemented computational and / or combinatorial tools and methods may open new territory through direct exploration of chemical space for new drug discovery and associated lead generation. More particularly, proprietary algorithms provided by the disclosed embodiments may also indicate exactly how many leads may need to be searched to return usable results for a particular project.

[0149] As commonly known, benzene is a substance known to be a carcinogen, which increases the risk of cancer and other illnesses, and is also a notorious cause of bone marrow failure. To better characterize, understand, account for, treat and / or cure illnesses caused by benzene and other carcinogens, it may be necessary to deconstruct a complex molecule, such as benzene, into its constituent elements using enzymes like an amino acid or proteins made from amino acids. Should such constituent substances fail to occur in nature, a search for an amino acid may involve hundreds of millions of isomers to computationally and / or combinatorically enumerate.

[0150] Treatments and therapies for cancer include chemotherapy and radiation therapy, with significant percent- ages of sufferers not surviving regardless of receiving such treatment, no available permanent cure, and very severe side effects. Similarly, regarding challenges faced due to inadequacies of currently available medical care, shortcomings in current industrial safety measures have left substantial numbers of people in certain industries facing the effects of exposure to various deleterious substances such as benzene. Nevertheless, advances in current computer capabilities have produced favorable results regarding the reduction of vast numbers of isomers to molecular formulas. For example, a search executed via the disclosed embodiments for benzene results in 37 target formulas, 406 enzyme formulas and 37 analogs, and a unique dipeptide. Thus, successful and timely navigation of the once intractable and perpetual chemical space now appears possible and is out- lined by the presented embodiments.

[0151] General Description of the Disclosed Embodiments

[0152] To create a computational and combinatorial computer-based algorithmic method to effectively navigate chemical space, e.g., as generally understood and defined herein as a concept in cheminformatics referring to the property space spanned by all possible molecules and chemical compounds adhering to a given set of construction principles and boundary conditions, thousands of chemical formulas were collected, including everything from molecules in air, food additives, alcohols, substances thought to cause cancer in rats and mice, in monkeys, vitamins, sugars, antibiotics, cancer markers, the stuff in DNA, chemotherapy drugs, cholesterol molecules, hemoglobin, coffee. Elements considered include that shown in the periodic table, commonly understood and defined herein to be a tabular display of the chemical elements, which are arranged by atomic number, electron configuration, and recurring chemical properties. The periodic table is ordered by atomic number, which may a special case of an integer called the index, e.g., as may be defined for a subset of the periodic table. The periodic table, as modeled and searched through herein, may be divided into two contiguous parts, and extended into a larger table with molecular formulas ordered by the index, which may have a constraint that forces the periodic table and / or elements and / or chemical structures associated there- with to change in discrete operations or steps.

[0153] Disclosed embodiments herein relate to the input of a chemical formula in a defined search space to obtain a list of chemical formulas that may bind or complex with the input formula.

[0154] Additional functionality of the disclosed embodiments include: to input one chemical formula and a byproduct formula and a search space to thus obtain a list of chemical formulas that might dissociate the byproduct from the input formula by way of catalysis; to input one chemical formula and a search space to obtain a list of chemical formulas that might be targets of that formula; to input one chemical formula and a search space to thus obtain a list of chemical formulas that might competitively inhibit that formula; to restrict the search results to particular sometimes unique dipeptides; to use these dipeptides to fingerprint a protein from its peptide sequence, and to search a protein database or use experimental methods to search for such proteins; to use above searches twice to obtain a list of formulas, amino acids or proteins that may cause drug resistance, or be markers of drug resistance; and, to perform multiple searches, build graphs or chains of interactions. Such a systematic computational and combinatorial computer-based algorithmic approach as disclosed herein successfully finds a needle, e.g., a desired target molecule, chemical structure, analog, moiety and / or the like, in a haystack of incomprehensible size, e.g., chemical space overall. Thus, disclosed systems and methods provide a powerful tool against every kind of disease or malfunction of very complex biochemical organisms.

[0155] System Structure

[0156] FIG. 1A illustrates a simple graph, a multigraph, and a molecular graph, respectively, in accordance with an embodiment of the present invention. In the present embodiment, simple graph 102A, multigraph 104A, and molecular graph 106A, respectively, are shown as a part of multiple graphs 100A, all of cyclohexane. By way of example and not limitation, in one of embodiments, multiple graphs 100A provide the foundation upon which any one or more of the below-disclosed computational and / or combinatorial algorithms may be based, e.g., such that the disclosed algorithms may receive such a structure as any one or more of multiple graphs 100A to enumerate the same for subsequent search purposes as may be necessary to locate related molecules, chemical structures and / or the like.

[0157] FIG. 1 B illustrates a flowchart of an exemplary method of inputting a chemical formula and / or a byproduct formula to obtain a desired list of outcomes, e.g., including related formulas, amino acids, proteins, and / or further direction concerning multiple additional related searches and so on and so forth, in accordance with an embodiment of the present invention. In the present embodiment, a method 100B is shown that is at least partially implemented in a computer and executed by one or more processors associated therewith. Method 100B includes various routes, operations, steps, and / or sequences, etc., for outputting a number of related items, e.g., a list of formulas 120B, amino acids 122B, proteins 124B and / or additional sequential and / or concurrent searches 126B upon activation at a start operation 134B followed by, for example, any one or more of input operations 130B, 132B, 108B, and / or 112B, e.g., input a chemical formula and a byproduct formula operation 130B. In an alternative embodiment shown in 508 a chemical formula includes predefined elements such as, without limitation, letter sequences made of G A S P V T C N D I L E Q M K H F R V W, assuming the user provides an assumed index to each such as, without limitation, G 40, A 48, S 56 etc, and a valence to each such as, without limitation, 2. A search space may, without limitation, also include such predefined elements. By way of example and not limitation, following route "A1of method 100B, input of chemical formula and a byproduct formula operation 130B yields obtain a list of dipeptides operation 102B. A dipeptide, as commonly under- stood and defined herein, refer to an organic compound derived from two amino acids. The constituent amino acids may be the same or different. When different, two isomers of the dipeptide are possible, depending on the sequence. Several dipeptides are physiologically important, and some are both physiologically and commercially significant. A well-known dipeptide is aspartame, an artificial sweetener. Such dipeptides may then be used at use these dipeptides to fingerprint a protein operation 104B to fingerprint a protein prior to conclusion of method 100B at end operation 128B.

[0158] By way of example and not limitation, following route "B" of method 100B, input of chemical formula and a byproduct formula operation 132B yields obtain a list of chemical formulas that might dissociate the byproduct from the input formula by way of catalysis operation 106B prior to conclusion at end operation 128B. Alternatives to routes "A" and "B" as shown in FIG. 1 B and described herein, include the following: input a chemical formula and a search space operation 108B that yields an obtain a list of chemical formulas that might bind or complex with the input chemical formula operation 110B; input a chemical formula and a search space operation 112B that yields an obtain a list of chemical formulas that might competitively inhibit the input chemical formula operation 114B; or a perform the reverse search of "A" and "B" to find targets of a given chemical formula within a specified search space, all prior to end operation 128B to conclude method 100B. Additionally, or in the alternative to any one or more that described above, any one or more of the operations may be repeated by use above searches twice module or operation 118B to yield any one or more of a list of formulas 120B, amino acids 122B, proteins 124B and / or additional sequential and / or concur- rent searches 126B prior to end operation 128B. Those skilled in the art will appreciate the type, configuration, placement and / or order, etc., of the various modules and / or operations shown in FIG. 1 B are by way of example only and thus not limiting to that shown. Other suitable type, configuration, placement and / or orders may exist without departing from the scope and spirit of the disclosed embodiments.

[0159] FIG. 2 illustrates a flowchart of an exemplary method of inputting a formula into a chemical search interface to search for atoms, molecules, chemical structures and / or compounds, etc., to calculate an index of the input formula, in accordance with an embodiment of the present invention. In the present embodiment, general background information necessary for the performance of method 200 includes reference to a particular input molecular formula or isomer as being identified as "consistent" if its index, e.g., as calculated through any known method and / or by proprietary algorithms associated with the presently disclosed embodiments such as being proportionate to the number of valencies of a given element and / or compound, is not divisible by 3, and "inconsistent" if its index is a multiple of 3. Further, small molecules may avoid inconsistency by becoming ions or even adopting open shell configuration.

[0160] By way of example and not limitation, method 200 may begin at start operation 202 where, subsequently, a user of method 200, e.g., at least partially implemented in a computer, inputs the formula into a chemical search inter- face to search for atoms, molecules, chemical structures and / or compounds, etc., (e.g., as already described by presenting the periodic table up to atomic number 48) at chemical formula input operation 204. The user next inputs a list of valencies required for each atom, e.g., 4 for C, 3 for N, 2 for O, 1 for H, at valency input operation 206 prior to inputting the list of atoms comprising the space to search, like: C, H, N, O, or S, and / or also by presenting the same on a periodic table at chemical space definition input operation 208. The user may then next interact with the chemical search interface by, e.g., pressing a of the button and / or contacting a touch sensitive screen at interface interaction input operation 210 to trigger the chemical search interface to calculate, using one or more algorithms, an index of the input formula at index calculation operation 212 prior to any one or more of those algorithms being further used to calculate an index step at an index step calculation operation 214. In the example of dichlorobenzine at 202, without limitation, at 204 user inputs C6H4CI2, at 208 user selects search space C_H_N_O_, at 210 user selects Enzymes, at 212 index 74 calculated by 6 multiplied by 6, added to 4 multiplied by 1 , added to 2 multiplied by 17 prior to further steps.

[0161] Chemical structural analogs may, by way of example and not limitation, in one or more embodiments, use the index calculated in index calculation operation 212 at analog index usage operation 216, where method 200 may then proceed to numerical adjustment operation 220, where for certain enumerated chemical target formulas, if the calculated index is odd 27 is deducted therefrom, or, if even, 72 may be deducted therefrom, or - alternatively - the index may be left unchanged if doing so would yield a negative result.

[0162] Should knowledge of chemical structural analogs not be desired, method 200 may proceed to enzyme or catalyst adjustment operation 218, where, for enzymes / catalysts if the calculated index is odd 27 is added thereto, if even 72 is added thereto prior to conclusion of method 200 at end operation 222.

[0163] FIG. 3 illustrates a flowchart of an exemplary method of how to use a formula search for high throughput screening in accordance with an embodiment of the present invention. In the present embodiment, method 300 is shown for conducting a high-throughput screening of chemical structures, compounds, and / or the like in accordance with any one or more of the algorithmic, computational and / or combinatorial procedures in accordance with the presently disclosed embodiments. By way of example and not limitation, method 300 may be a high-level and / or general representation of how to use any one or more of the searchings, characterizing, navigating and / or parsing algorithms for traversing chemical space as disclosed herein.

[0164] Method 300 may begin at start operation 302 from which a formula search may be entered at a formula search entrance operation 304, whereupon such input formula and / or formulae may be subjected to one or more filters at filter operation 306, by way of example and not of limitation using Lipinski rule of five. Lipinski, C. A., Lombardo, F., Dominy, B. W., Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23, 3-25. Completion of application of filter operation 306 progresses method 300 to novelty determination operation 308, where the novelty of an input chemical formula and / or formulae is assessed.

[0165] An assessment of "yes" yields isomer enumeration operation 310 where any one or more or all isomers of a particular input chemical formula and / or formulae are assessed via traditional known chemical structure enumeration methods or those proprietary and associated with the presently disclosed embodiments prior to progressing to synthesis operation 312, where complete chemical reaction modeling may occur upon input of additional and / or different reagents intended to simulate a reaction with originally input chemical formula and / or formulae at formula search entrance operation 304 prior to progression to high through- put screening operation 314 and conclusion of method 300 at end operation 316.

[0166] Alternatively, an assessment of "no" at novelty determination operation 308 may progress method 300 directly to high throughput screening operation 314 and conclusion of method 300 at end operation 316. "High-throughput screening", as both generally understood and referred to herein, refers to and / or implies a method for scientific experimentation especially used in drug discovery and relevant to the fields of biology and chemistry. [Source: Inglese J and Auld D S. (2009) Application of High Throughput Screening (HTS) Techniques: Applications in Chemical Biology in Wiley Encyclopedia of Chemical Biology (Wiley & Sons, Inc., Hoboken, NJ) Vol 2, pp 260-274 doi / 10.1002 / 9780470048672. wecb223; Macarron, R.; Banks, M. N.; Bojanic, D.; Burns, D. J.; Cirovic, D. A.; Garyantes, T.; Green, D. V.; Hertzberg, R. P.; Janzen, W. P.; Paslay, J. W.; Schopfer, U.; Sittampalam, G. S. (2011). "Impact of high-throughput screening in biomedical research". Nat Rev Drug Discov. 10 (3): 188-195.] Using robotics, data processing / control software, liquid handling devices, and sensitive detectors, high-throughput screening allows a researcher to quickly conduct millions of chemical, genetic, or pharmacological tests. Through this process one may rapidly identify active compounds, antibodies, or genes that modulate a particular biomolecular pathway. The results of these experiments provide starting points for drug design and for understanding the noninteraction or role of a particular location.

[0167] FIG. 4A illustrates a flowchart of an exemplary method of how to make a formula search for high throughput screening, in accordance with an embodiment of the present invention. In the present embodiment, method 400A begins at start operation 402A that may progress to any one or more or all of the following: index operation 404A, input space 406A, and atomic numbers and / or valences 408A. Index operation 404A may calculate and / or otherwise attribute an index value via isomer enumeration to one or more input chemical formulae into method 400A; likewise, input space 406A may be representative of the chemical space in which related chemical formulae, species, analogs, and / or the like are sought; and, atomic numbers and / or valences 408A may consider the atomic number and / or valency of input chemical formulae. By way of example, without limitation, method 410A initializes loop 412A to 420A. In method 410A ztotal is used to calculate maxz. Example dichlorobenzine index 74 + step 72 - byproduct index 12 = index step 134; maxz is the most of 1st atom usually C, example dichlorobenzine maxz = 134 / 6=22 which used as loop limit in 418A. It is not necessary to incrementally advance by sequential integer values. The order is not important, it may be in any order covering the same range.

[0168] By way of example and not limitation, in one or more embodiments, calculative methods associated with index operation 404A may calculate an index value for an input chemical structure and / or the like at start operation 402A by the following example algorithm: the atomic number of a given element, e.g., equivalent to the number of protons in the nucleus of the given atom and / or element such as 8 for oxygen ("O), 1 for hydrogen ("H"), so on and so forth, added to any (absolute value of) number of additional electrons for a charged ion, e.g., an anion. Thus, in this context, an index value for an input formula of the hydroxide anion, e.g., OH-, results in an index value calculation at index operation 404A as follows: (index value of O)+(index value of H)+(absolute value of any additional electrons)=8+ 1+1=10. Similarly, an index value calculated solely for the hydroxy group with the chemical formula of OH may be calculated by the index operation 404A as follows: (index value of O)+(index value of H)=8+1=9. Those skilled in the art will appreciate that the above-included examples of enumeration for calculating index values by operation 404A are provided for illustrative purposes only and that many other suitable alternative calculative procedures may be employed by index operation 404A without deviating from the scope and spirit of the presently disclosed embodiments. Method 400A, after considering any one or more of index operation 404A, input space 406A, and atomic numbers and / or valences 408A may progress to increment operation 410A, which, as shown in FIG. 4A, may assign an initial increment start position or value of "O" to systematically cycle through index values associated with corresponding chemical structures and / or formulae to identify isomers and / or other compounds related to input chemical formulae. Such increment operation 410A may assign a total number of increments and / or steps equivalent to the index attributed to an input chemical formula and / or a maximum number of increments proportionate to a total value, e.g., "ztotal", divided by the atomic number of the input chemical formula.

[0169] Method 400A then progresses from increment operation 410A to enumerate and / or sub-enumerate operation 412A, which may involve a multiplication modification of incremented values associated with the index of an input chemical structure by its atomic number as shown in FIG. 4A and / or involve any other mathematical modification. By way of example and not limitation, enumerate related operations in FIG. 4A may be further explained in addendum 414A as a partition algorithm given a list of atomic numbers and a constant number index step. In an embodiment, "enumerate all" sums that which add to precisely a constant number; e.g., given C, H and 11 are an input list may be proportionate to each atoms respective atomic number, e.g., [6,1] and 11. Calculative procedures may include, in one or more embodiments, iteratively cycle through various additive combinations of C and H that may add up to a total of 11 , e.g., C having an atomic number of 6, H having an atomic number of 1 , and so on and so forth.

[0170] Completion of enumeration operations as described in connection with enumerate and / or sub-enumerate operation 412A may progress method 400A to subsequent increment operation 416A where the index step calculated earlier at increment operation 410A, for example, or any operation thereafter, may be again incremented to approach a max iteration value "maxz" at iteration maxi- mum identification operation 418A.

[0171] Method 400A here may return via return loop 420A to enumerate and / or subenumerate operation 412A in some embodiments. More particularly, by way of example and not limitation, return loop 420A in FIG. 4A chooses the quantity of first atom (e.g., CO, Cl, ...) to then call enumerate and / or sub-enumerate operation 412A, e.g., further shown as "subenumerate" in FIG. 7, to choose the other atoms (e.g., NO, N1 , ...). In some embodiments, enumerate and / or sub- enumerate operation 412A recursively calls itself. In certain embodiments, branch testing "iform" in sub-enumerate FIG. 7 defers H quantity to last. In other embodiments, the H quantity may be calculated for one or more isomers with max hydrogen in FIG. 9. Method 400A may conclude should a satisfactory number of iterations be completed yielding index values (e.g., denoted by "z") being less than a max index and / or iteration value "maxz" at end operation 422A. An aspect of method 400A is to produce the requested list of molecular formulas and show how many there could be.

[0172] FIG. 4B illustrates a flowchart of an exemplary method of how to make a computational and / or combinatorial algorithm for that shown in FIG. 4A, in accordance with an embodiment of the present invention. In the present embodiment, a 4-by-4 loop is defined as a for loop for d within a for loop for c within a for loop for b within a for loop for a. In the present embodiment, method 400B begins at start operation 402B from which a 4-by-4 loop is created of four integer numbers a, b, c, d each from 0 to an input number at operation 404b, where (inside the loop) a calculation of a division of the four integer numbers a, b, c, d by 3 is performed to obtain four numbers a3, b3, c3, d3 at operation 406B. Should such numbers calculated at operation 406B equal those obtained from a previous iteration of operation 406B, such numbers may be discarded at operation 408B. After looping through O through an example input number of 8 four times, in one or more embodiments, 24 lists of four numbers including representative numbers O and 2 may be obtained at operation 41 OB. In this manner, at least for the present embodiment, 24 spin up states and 24 spin down states have the same period 9 as found in the periodic table.

[0173] Next, at operation 412B, different input numbers, e.g., for input as an input number at operation 404B, may be tried to, for example (but not limitation), observe that numbers higher than 8 are not found and / or to identify location of atoms and / or moieties to obtain calculative identification of atoms of a certain specific period, e.g., period 9. By way of example and not limitation, in one or more embodiments, operations 404B-412B may be collectively referred to as group operation 422B.

[0174] Subsequent to successful completion of group operation 422B, method 400B may proceed to operation 414B where any one or more operations identified within the inside of group operation 422B of method 400B may permit a user of the same to choose between: (1) reduced; or, (2) not reduced states and / or conditions. Operation 416B later determines, by way of example and not limitation, if [(a3*d3)-(b3*c3)] is +1 or -1 , obtained results may be classified as "reduced", if zero such results are "not reduced" before operation 418B that may find that 14 of the 24 lists of four numbers from operation 41 OB may be reduced and 10 may not be reduced; the 14 come in two pairs of seven named: O, B, A, S, I, K, and D; in each period of 9 there may be 7 reduced and 2 not reduced prior to conclusion of method 400B at end operation 420B.

[0175] FIG. 40 illustrates a flowchart of an exemplary method of how a pharmaceutical company or other interested party and / or entity may use the computational and / or combinatorial algorithm shown in at least FIG. 4B, in accordance with an embodiment of the present invention. In the present embodiment, any one or more of the systems, methods, and / or search algorithms presented in the preceding figures and described in connection therewith may be adapted, adjusted or otherwise used by a search entity such as a pharmaceutical company through method 400C which may begin at start operation 402C. Input of a known formula, e.g., C6H6, may occur, e.g., through input by a user of method 400C, at input operation 404C as follows: press up or down to select 6 hydrogen atoms first; if formula has H and C atoms only: (1) add any third atom, e.g., N to remove later; (2) remove C then add it back; (3) choose number of C then remove N. Next, at operation 406C, input of other known formulas, e.g., C2H5N02 may occur as follows: select 5 hydrogens first so CH changes to CHS; add third atom, e.g., N and press down to reduce it to 1 so CH5 changes to CH5N; remove C but add it back, then choose 2 C so NH5 changes to NH5C2; add O then N1 H5C2 changes to N1 H5C2O2. Those skilled in the art will appreciate that operations 404C and 406C may be collectively referred to as group operation 408C and include additional or fewer chemical structure and / or formula input operations other than that shown in method 400C of FIG. 4C without departing from the scope and spirit of the presently disclosed embodiments. Subsequent to group operation 408C, a user of method 400C may press, e.g., on an appropriately equipped at least partially computer-based interface, an identified key and / or key strokes such as " ... " to choose the particular desired chemical space to search: e.g., C, H, N, O from any single group atoms (atomic numbers 1 to 48). Default settings, e.g., regarding searching for chemical formulas related to an input formula input at group operation 408C, may be input at operation 412C, e.g., where numbers of single group atoms input earlier at operation 410C may be left unchanged while searching for possible related chemical formulas; default space is C, H, may add any other atoms like N and O; and, it may be possible for the removal of C if another non-hydrogen atom is added. At operation 4140, the user may request target compounds and / or formulas, enzymes, and / or chemical analogs as those sought to appear within any results, etc.

[0176] Next, at operation 4160, reactions may be searched for where such reactions may generally be input or viewed in the form X + C ^ Y + Z + C, where X or Y is the target reactant and Z is the byproduct, and C is the catalyst or enzyme. By way of example and not limitation, in one or more embodiments, a user may be enabled to press a button denoted as "targets" for possible formulas for a given input reactant X or Y having specified formula for an enzyme C at operation 4180. Likewise, such a user may be enabled at operation 4200 to press an "enzymes" button to search for an uncover possible formulas for enzyme C having specified target X or Y; and, to press an "analogs" button, at operation 4220 for formulas that could be substituents for a given formula. Ongoing operation 424C indicates that algorithms associated with method 400C interpret a formula as, for example (but not limitation thereto), all non-fragment isomers of that formula. In an example, non-fragment isomers may be defined as those which are fully saturated. Bonds between two atoms may be single, double or triple. Isomers with rings are allowed as well as non-cyclic isomers and isomers of any topology. Ongoing operation 426C may indicate that input atoms must each have a specified valence, where the second atom in any formula must be H.

[0177] Operation 428C, which in some embodiments may be considered to be a "catch-all" type operation intended to encompass various specifics not set forth and discussed explicitly for method 400C, may at least include any one or more of the following conditions: hybrid or non-hybrid cannot be specified; a new spinor basis (e.g., for input chemical formulas) may include some hybrid molecular orbitals or it may not; inconsistent hybrid orbitals may collapse to a point in spinor space; no heavy atoms may be permitted or considered beyond atomic number 48 (e.g., hence no radioactive atoms); oxidation numbers cannot be specified at present; all output formulas may be saturated and fragments are eliminated. Method 400C may then culminate at end operation 430C. Those skilled in the art will appreciate the configuration possibilities set forth here are provided for example purposes only and that additional or fewer configurations may exist regarding manipulation and search for related chemical formulas relative to an input formula, inclusive of enzymes, etc., without departing from the scope and spirit of the disclosed embodiments.

[0178] FIG. 5 illustrates a flowchart of an exemplary method of how to calculate an index for that shown in FIG. 3, in accordance with an embodiment of the present invention. In the present embodiment, method 500 to calculate an index numerical value may be performed at, for example, index operation 404A of method 400A shown in FIG. 4A and may begin at start operation 502. Next, at operation 504, chemical formulas may be input having a general format of, for example (but not limitation thereto): Z1z1 HhZ2z2 ...Znzn and / or the like. Operation 506 may incrementally define or otherwise attribute index values to molecules and / or chemical structures in accordance with their respective atomic numbers and additions made to account for additional electrons prevalent in charged ions. Such calculative procedures are detailed for index operation 404A of method 400A shown in FIG. 4A and are not repeated herein. Indexing calculations, in one or more embodiments, may be calculated iteratively and thus have incremental index, or "i" values beginning from "0" and incrementing, by integer values, forward. The symbol Z is conventional for atomic number. Z1 is usually C, Z2 is always H so omitted, Z3 is often N. In method 508 Z1 , Z3 ... Zn could also be amino acids from G A S P V T C N D I L E Q M K H F R V W, and predefined or precalculated values like Z(G)=40, Z(A)=48, Z(S)=56 etc stored. Operation 510 may be described by notation 508, which indicates that Z(Zi) may represent the atomic number of a given atom Zi or calculated index(Zi) for a given chemical structure or formula, where such an atomic number or index value may be further numerically aggregated, multiplied or manipulated and / or incremented by addition operation 512 that may, in some embodiments, also incorporate an index operation 514 that may be iteratively repeated in loop 516 prior to increment operation 518. Assessment of increment value "i" at operation 520 permits for method 500 to conclude at end operation 524 should less than a specified total "n+1" value be attained by increment operation 518, or (alternatively) method 500 may return to operation 510 via loop operation 522. Thus, method 500 may be performed repeatedly to iteratively enumerate chemical structures of input formula and systematically identify and output relates formulas thereto dependent at least partially upon chemical formula input at start operation 502 and subsequent operations.

[0179] FIG. 6 illustrates a flowchart of an exemplary method of an index calculation operation, in accordance with an embodiment of the present invention. In the present embodiment, method 600 to calculate an index for chemical formulas and / or structures input thereto may begin at start operation 602 that proceeds to index operation 604 that provides for user interactivity to engage, e.g., by clicking on or otherwise activating, search capabilities regarding the following: targets 606, enzymes 608, and analogs 610.

[0180] Index values intended to be calculated on behalf of targets 606, e.g., as may be determined by any one or more of the index value calculative methods previously presented and discussed, may be further augmented or numerically manipulated, e.g., for odd index values, at odd index value operation 612 that may progress method 600 subtraction operation 618 where 27 may be subtracted from the odd index calculated value at operation 612 prior to culmination of method 600 at end operation 628. Those skilled in the art will appreciate that the exact number values subtracted at subtraction operation 618 may be different than 27, e.g., higher or lower, depending on the calculative metric employed by method 600 without departing from the scope and spirit of the disclosed embodiments. An aspect of 27 and 72 and 11 is that they are linked by equation to the numerical value of physical constant reduced Planck constant. An aspect of 14 and 32, the atomic numbers of Silicon and Germanium, is that they are linked by equation to the numerical value of the numerical constant, the speed of light. The speed of light has the curiously symmetrical number 88088 in an electron counting scale. After division by the highest multiple of 27, the remainder is 14. After division by the highest multiple of 72, the remainder is 32. The steps preferably should not be anything different unless every index were rescaled. By way of example, without limitation, using numbers like 1.0545 and 2 x 1.0545 in place of integer indexes, the steps then are 28.4715 and 75.924 instead of 27 and 72. This or any equivalent method is not considered materially different from the algorithm specified here.

[0181] Should calculated values of the index be even, method 600 may progress to even index value operation 614 that may progress method 600 to subtraction operation 620 where 72 may be subtracted from the odd index calculated value at operation 612 prior to culmination of method 600 at end operation 628. Those skilled in the art will appreciate that the exact number values subtracted at subtraction operation 620 may be different than 72, e.g., higher or lower, depending on the calculative metric employed by method 600 without departing from the scope and spirit of the disclosed embodiments.

[0182] Index values intended to be calculated on behalf of enzymes 608, e.g., as may be determined by any one or more of the index value calculative methods previously presented and discussed, may be further augmented or numerically manipulated, e.g., for odd index values, at odd index value operation 616 that may progress method 600 addition operation 622 where 27 is added to the calculated index value and index operation 624 where 72 is added to the calculated index value prior to culmination of method 600 at end operation 628. Those skilled in the art will appreciate that the exact number values added at addition operations 622 and 624 may be different than 27 and 72, respectively, e.g., higher or lower, depending on the calculative metric employed by method 600 without departing from the scope and spirit of the disclosed embodiments.

[0183] Index values intended to be calculated on behalf of analogs 610, e.g., as may be determined by any one or more of the index value calculative methods previously presented and discussed, may be further augmented or numerically manipulated at index operation 626 that may progress method 600 to end operation 628. Those skilled in the art will appreciate that numerical manipulation at index operation 626 may include any number of transformations without departing from the scope and spirit of the disclosed embodiments.

[0184] FIG. 7 illustrates a flowchart of an exemplary method of a sub-enumeration calculation operation, in accordance with an embodiment of the present invention. In the present embodiment, method 700 may be employed to enumerate and / or sub-enumerate at least portions of chemical formulas as may be associated for subsequent search related purposes, e.g., to locate, uncover, and return search results related to that input. Accordingly, method 700 may begin at start operation 702 to progress to operation 704 where iform and zsum operations may involve the input of chemical formulas in the general format of Z1 H Z3 ... Zn etc., prior to progressing to operation 706 that may assess whether such iform calculations are at least one integer value beneath a set value "n".

[0185] Method 700 may then progress to operations 708 and 710. Operation 708 calculates a value for iJ as equal to an atomic number that may be numerically manipulated or transformed, e.g., having 2 added thereto, where other such values including zmax may be calculated as (index step- zsum) / iJ, where further numerical increments and / or adjustments are possible, including assessments, e.g., z[iform+2]=0. Operation 710 may perform calculative operations similar to that described for operation 708 for an isomer with a maximum possible hydrogen count, e.g., permitting for a stable chemical compound, etc., and / or include other or different calculative operations. A guiding aspect of method 700 is to go through the possible values like NO, N1 ... rejecting all combinations that give the wrong index value, example dichlorobenzene byproduct C2 index step 134 rejects C0H_N0O17 because O-O'- ... -0-0 may only have canonical isomer H-O17-H which would give it 17x8+2=136 not equal index step 134. Input dichlorobenzine and byproduct 02 in search space C_H_N_O_ the algorithm listed 541 formulas and rejected 969 formulas. Subsequent to operation 708, operation 712 performs a sub enumerate calculation involving iform values considered earlier to increment the same by one integer value, e.g, iform+1 , and / or additional numerical manipulations such as zsum+(iJ x z[iform+2]). Those skilled in the art will appreciate that the example terms "zsum" and "iform" are provided as an example and that other terms may be used for describing and / or referring to numerical values associated with enumeration of chemical formulas without departing from the scope and spirit of the disclosed embodiments.

[0186] Method 700 may progress to operation 716 that further numerically manipulates number values according to: z[iform+2]=z[iform+2]+1 , and then operation 720, which performs: z[iform+2]<=zmax, to increment enumerated values systematically until a maximum, e.g., zmax, is reached prior to culmination of method 700 at end operation 722.

[0187] Subsequent to operation 710, operation 714 performs a max hydrogen ("h") index step to ensure that total number of enumerated hydrogen values are even prior culmination of method 700 at end operation 722. Alternatively, by way of example and not limitation, operation 714 may progress to operation 718 involving representation of chemical formulas incoming or input thereto in the form of Z1z1 HhZ3z3 ... Znzn prior culmination of method 700 at end operation 722.

[0188] FIG. 8 illustrates a flowchart of an exemplary method of algorithm interpretation regarding bonds between atoms, in accordance with an embodiment of the present invention. In the present embodiment, method 800 may be implemented at least partially in conjunction with any one or more of the methods and / or algorithms presented earlier and may begin at start operation 802. Next, at operation 806, method 800 may involve or otherwise employ an algorithm that interprets any input formula thereto as all non-fragment isomers of that formula and may consider at least the following example conditions: bonds between two atoms may be single, double or triple; isomers with rings may be allowed as well as non-cyclic isomers and isomers of any topology; a canonical isomer may have maximum number of H or valence atoms; atoms may be placed in a line with highest valence atoms at both ends, single bonded, where such a configuration may be referred to as a canonical isomer.

[0189] Method 800 may progress to operation 808 after operation 806 where, by way of example and not limitation, any one or more of the following example operations regarding data manipulation or transformation may be per- formed regarding the enumeration of input chemical formulas: adding a double bond, triple bond or ring will reduce number of H by an even number; the branch testing max H in FIG. 7 compares canonical isomer to a putative partition; if test "false" leaves an odd number of H-all isomers of this kind may simultaneously be rejected; if test "true" prints a formula with numbers of each atom specified, prior to culmination of method 800 at end operation 810. Operations 806 and 808 may be collectively referred to as group operation 804. Those skilled in the art will appreciate that additional or fewer transformation may be applied to algorithms associated with the enumeration of chemical formulas as disclosed herein without departing from the scope and spirit of the disclosed embodiments.

[0190] FIG. 9 illustrates a flowchart of an exemplary method of calculating and / or identifying an isomer with a maximum number of hydrogen atoms, in accordance with an embodiment of the present invention. In the present embodiment, method 900 shown in FIG. 9 shows how to calculate max hydrogen, the first branch skips H itself and any omitted atoms. By way of example and not limitation, in one or more embodiments, COHNO will skip C and H. The method loops over other atoms to find max valence e.g. C in CHNO. The method increments max Hin the loop, except valence 1 , e.g., C1 will decrement. The last step in method 900 calls "second highest valence loop body" shown in FIGS. 10 and 11. Enzymes for NH2 with search space C_H_ is a simple example with CO, C1 , C2, C3, C4 rejected but C5H6 the only answer. Method 909 initialises variables. For CO method 910 i=1 z1=0 false, proceeds to method 918 i=2 loops back to 910 false then method 918 i=3 then method 920 tests false exiting to method 922 Second highest valence. For 01 method 910 i=1 z1 =1 tests true, then method 912 valence C=4>0 tests true, then method 914 maxvalence=4 maxn=1 , method 916 maxh incremented (4-2)x1=2, method 918 i=2, then method 920 loops back to method 910. Method 910 tests false to skip Hydrogen then method 918 i=3 then method 920 tests false exiting to method 922 Second highest valence. For 02 method 910 i=1 z1=2 tests true, then method 912 valence C=4>0 tests true, then method 914 maxvalence=4 maxn=2, method 916 maxh incremented (4-2)x2=4, then method 918 i=2, then method 920 loops back to method 910. Method 910 tests false to skip Hydro- gen then method 918 i=3 then method 920 tests false exiting to method 922 Second highest valence. 03 to CS are similar with z1 ranging 3 to 5 and maxn ranging 3 to 5 and maxh incremented 6 to 10 in method 910, further incremented 2 in method 1010. CO to C4 don't have enough electrons to reach the required number 9+27=36 but C5H6 has exactly the right number.

[0191] It should be noted that the use of computer system in most practical applications requires careful considerations by those the skilled in the art at least because among 40 isomers of C5H6 is a ring-shaped toxic molecule. Prior art software like MOLGEN or OMG may be used on C5H6 to find isomers. Gugisch, R., Kerber, A., Kohnert, A., Laue, R., Meringer, M., Rucker, C., Wassermann, A.: MOLGEN 5.0, A Molecular Structure Generator (2016) Advances in Mathematical Chemistry and Applications: Revised Edition, 1 , pp. 113- 138. Peironcely, J. E., Rojas- Cherto, M., Fichera, D., Reijmers, T., Coulier, L., Faulon, J. L., & Hankemeier, T. (2012). OMG: Open Molecule Generator. Journal of cheminformatics, 4(1), 21. doi: 10.1186 / 1758-2946-4-21 https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC3558358 / .

[0192] Method 900 may begin at start operation 902 from which increment operation 904 may assess chemical formula values through "zn" where subsequently a user of method 900 may optionally input a chemical space intended to be searched at input space operation 906 prior to progressing to max h assessment operation 909 where a maximum number of hydrogen and / or valences may be tabulated, calculated, identified and / or otherwise assessed. Next, method 900 may progress to operation 910 where incremental values of calculated indexes, e.g., "i", may be assessed to determine position for subsequent method progression. That is, should assessed index values "i" be not equal to a specified value, e.g., 2, and another pre-set condition be satisfied, e.g., and incremental values of assessments of index values for various parts of a given chemical formula, etc., then method 900 may either progress to a maximum valence assessment operation 912 or bypass said operation, and other operations 912-916, to forward to increment operation 918 to count and calculate additional i values for isomer possibilities to identify an isomer for a given input chemical formula with a maximum H value.

[0193] Alternative to the bypass as described above, various data transformation operations 912-916 may systematically assess maximum hydrogen values for related isomers in input chemical space, e.g., as done so at operation 906, by considering (at a minimum) valence hydrogen and / or isomer configurations, where index values less than a specified value may be returned at operation 920 to operation 910 or forwarded to a second highest valence hydrogen assessment operation 922 prior to culmination of method 900 at end operation 924.

[0194] FIG. 10 illustrates a flowchart of an exemplary method of calculating and / or identifying an isomer with a second-highest number of valencies, in accordance with an embodiment of the present invention. In the present embodiment, method 1000 may be an embodiment of second highest valence hydrogen assessment operation 922 of method 900 shown in FIG. 9. Method 1000 may begin at start operation 1002 from which it may progress to operation 1004 for assessment of a maximum number of available valencies, e.g., that must be greater than or equal to 2, prior to progression of various additional operations. Should a maxh (e.g., a maximum hydrogen) value be assessed in increments of 2 at operation 1010, then method 1000 may progress directly to end operation 1022 to culminate therein.

[0195] Alternatively, other calculative procedures exist whereby method 1000 progresses to assessment of a max index or increment value, e.g., beginning from 1. Those skilled in the art will appreciate that repository 1008 may include various types of stored information concerning maximum identified hydrogens, valencies, atomic numbers, and / or second valencies and such considerations may be at least partially assessed by method 1000 throughout.

[0196] Subsequent to operation 1006, operations 1012-1020 may, at least partially according to the mathematical formulas depicted therein, incrementally parse through input chemical formulas to determine second-highest available vacancy positions prior to culmination of method 1000 at end operation 1022.

[0197] FIG. 11 illustrates a flowchart of an exemplary method of that included in the "second highest valence loop body" shown in FIG. 10, in accordance with an embodiment of the present invention. In the present embodiment, operation 1016 of method 1000 shown in FIG. 10 is shown in more detail. By way of example and not limitation, in one or more embodiments, method 1100 may begin at start operation 1102 from which valencies may be calculated according to at least partial satisfaction of the mathematical conditions set forth by operation 1104, that is: Valence Zi < maxvalence AND Valence Zi > max2ndvalence, e.g., where such a successful assessment of such conditions may result in the identification of a second highest valency count for a given input chemical formula resulting in appropriate identification and / or enumeration thereof at operation 1106 prior to incrementing forward at operation 1108 and culmination at end operation 1112.

[0198] FIG. 12 illustrates an example chemical reaction, in accordance with an embodiment of the present invention. In the present embodiment, reaction 1200 may include a first and second reagent 1202, 1204, respectively, which yields product 1206 featuring CHNO group 1208 contained therein, where any one or more of the algorithms and / or methods discussed herein may be used to analyze, process, consider and / or assess any one or more of the chemical formulas, species, moieties, structures, reagents, products and / or the like of that shown in reaction 1200. An index of 22 may be ascribed to the CHNO group 1208 on account of tabulation via traditional means of an index number being equivalent to the atomic number of the constituent atoms of a given chemical group, etc. FIG. 13A-B illustrate an example structure of benzene, in accordance with an embodiment of the present invention. In the present embodiment, benzene is understood to be an organic chemical compound with the chemical formula C6H6. The benzene molecule is composed of six carbon atoms joined in a ring with one hydrogen atom attached to each. As it contains only carbon and hydrogen atoms, benzene is classed as a hydrocarbon.

[0199] Various depictions of benzene are shown for illustrative purposes including depiction 1300A and 1308A. Depiction 1300A includes chemical structures 1302A and 1304A showing various double bonds between constituent carbon atoms, where depiction 1308B more clearly emphasizes the uniform resonance structure 1306B of benzene. Any one or more of the algorithms discussed herein may calculate and / or otherwise tabulate appropriate index values for example chemical structures such as benzene within various defined or un-defined chemical spaces. Those skilled in the art will appreciate that shown as benzene is provided as an example only and that various other chemical structures may alternatively be searched for without departing from the scope and spirit of the disclosed embodiments.

[0200] FIG. 14 illustrates a table of search results to target benzene, in accordance with an embodiment of the present invention. In the present embodiment, input of benzene for enumeration and searching of a defined chemical space as may be associated with any one or more of the algorithms and / or methods presented herein may result in any one or more of the shown chemical structures and / or formulas, including: Spermine, Indanidine, Quipazine, Atipamezole, Napamezole, p-bisabolene, p-cadinene, d-capnellene. Such computations involve too many steps to list here even though a computer performs them in seconds.

[0201] FIG. 15 illustrates a flowchart of an exemplary method of a search for NAPQI, a toxic byproduct produced during the xenobiotic metabolism of the analgesic paracetamol, in accordance with an embodiment of the present invention. In the present embodiment, method 1500 may be conducted by any one or more of the algorithms and / or methods shown and discussed herein. Method 1500 may begin with start operation 1502 from which operation 1504 may perform at least: a search for NAPQI C8H7NO2 the toxin resulting from paracetamol overdose that includes C8H17N2O6S in the results which is a match for glutathione C10H17N3O6S with byproduct C2; the drug Acetylcysteine works by increasing the level of Glutathione, and is used as an antidote to paracetamol overdose. Next, operation 1508 may perform at least: searching enzymes for C6H4 assuming byproduct C2 results in a different list of 258 formulas C_H_N_O_ only 27 with available chemicals which include Glucuronic acid C6H1007, Carpacin C11 H1203; dipeptides Gly-Leu, Gly-Lle, Val-Ala, Ala- Thr, Cys-Ala and Ser-Ser all found in enzyme CYP2E1. Operations 1504 and 1508 may collectively be referred to as group operation 1506. Method 1500 may then culminate at end operation 1510. Those skilled in the art will appreciate that various modifications may be made to operations 1504 and 1508 without departing from the scope and spirit of the disclosed embodiments.

[0202] FIG. 16 illustrates a table of enzyme displayed in codified format, in accordance with an embodiment of the present invention. In the present embodiment, table 1600 may be considered by any one or more of the calculative procedures, algorithms, processes and / or methods discussed herein while searching chemical space for related chemical formulas, structures and / or the like relative to an input chemical formula. Those skilled in the art will appreciate that deviations may be made from that displayed in table 1600 without departing from the scope and spirit of the presently disclosed embodiments. For instance, various segments of the codified enzymes may be identified and considered for search-related organizational purposes.

[0203] Those skilled in the art will readily recognize, in light of and in accordance with the teachings of the present invention, that any of the foregoing steps and / or system modules may be suitably replaced, reordered, removed and additional steps and / or system modules may be inserted depending upon the needs of the particular application, and that the systems of the foregoing embodiments may be implemented using any of a wide variety of suitable pro- cesses and system modules, and is not limited to any particular computer hardware, software, middleware, firm- ware, microcode and the like. For any method steps described in the present application that may be carried out on a computing machine, a typical computer system may, when appropriately configured or designed, serve as a computer system in which those aspects of the invention may be embodied. Such computers referenced and / or described in this disclosure may be any kind of computer, either general purpose, or some specific purpose computer such as, but not limited to, a workstation, a mainframe, GPU, ASIC, etc. The programs may be written in C, or Java, Brew or any other suitable programming language. The programs may be resident on a storage medium, e.g., magnetic or optical, e.g., without limitation, the computer hard drive, a removable disk or media such as, without limitation, a memory stick or SD media, or other removable medium. The programs may also be run over a network, for example, with a server or other machine sending signals to the local machine, which allows the local machine to carry out the operations described herein.

[0204] Design Variations

[0205] Those skilled in the art will appreciate that any one or more of the algorithms, calculative procedures, values, identifications, data transformations, enumeration schemes and / or numerical assignments may be varied without limitation. For example, such variants may include at least: a variant of the input may accept an isomer in any representation such as InChi or parse a formula from text; a variant of the algorithm is given a reaction byproduct and searches against the remainder of the molecule; a common byproduct in antidotes and enzymes may be C2; deduction of an index of a byproduct from index of an input molecule; another variant of the algorithm finds protein sequences instead of general molecules; input may be to enumerate a list of indexes of each alpha amino acid instead of atomic numbers; valences may be set to always two; the free dipeptide Proline-Proline may be uniquely identified for Benzine; the enzyme CYP2E1 may be effectively fingerprinted by seven dipeptides identified for Benzine with byproduct C2; another variant of the algorithm may be to find drug resistance candidates, and to find drugs or protein sequences specifically targeting the drug resistance candidates.

[0206] Additional variants include: using a random isomer or more than one isomer in place of the canonical isomer; using coordinate representation or bracket representation or s p d f or other schemes in place of the canonical isomer; using a fictitious atom or radioactive atom to get around oxidation number or stability restrictions; using an equivalent index representation by multiplying or dividing by a factor; and. to repeat the algorithm over a database and or filter the output whether useful or not.

[0207] Another variant of the algorithm is to enumerate isomers and then compare the shape of the target molecule with the shape of each prospective isomer. The Euclidean shape spaces are particularly suited because there is a Le Bhavnagri distance formula [source: H. Le and B. Bhavnagri, On simplifying shapes by subjecting them to collinearity constraints, Mathematical Proceedings of the Cambridge Philosophical Society, Volume 122 no 2, September 1997, pp 315-323] for comparing shapes with different numbers of points. Pairwise consistency is weakly defined in terms of superimposition of Euclidean similarities always being one to one [source: B. Bhavnagri, An index of carcenogenesis using pairwise consistency, MODSIM 2013]; inconsistency means there is a pair of superimposed Euclidean similarities which are not one to one.

[0208] Yet another variant of the algorithm is to enumerate isomers and then compare the size and shape of the target molecule with the shape of each prospective isomer. This is different from the above variant in that size information is retained.

[0209] Integration with Client Server System

[0210] FIG. 17 is a block diagram depicting an exemplary client / server system which may be used by an exemplary web-enabled / networked embodiment of the present invention.

[0211] A communication system 1700 includes a multiplicity of clients with a sampling of clients denoted as a client 1702 and a client 1704, a multiplicity of local networks with a sampling of networks denoted as a local network 1706 and a local network 1708, a global network 1710 and a multiplicity of servers with a sampling of servers denoted as a server 1712 and a server 1714.

[0212] Client 1702 may communicate bi-directionally with local network 1706 via a communication channel 1716. Client 1704 may communicate bi-directionally with local network 1708 via a communication channel 1718. Local network 1706 may communicate bidirectionally with global network 1710 via a communication channel 1720. Local network 1708 may communicate bi-directionally with global network 1710 via a communication channel 1722. Global network 1710 may communicate bi-directionally with server 1712 and server 1714 via a communication channel 1724. Server 1712 and server 1714 may communicate bi-directionally with each other via communication channel 1724. Furthermore, clients 1702, 1704, local networks 1706, 1708, global network 1710 and servers 1712, 1714 may each communicate bi-directionally with each other.

[0213] In one embodiment, global network 1710 may operate as the Internet. It will be understood by those skilled in the art that communication system 1700 may take many different forms. Non-limiting examples of forms for communication system 1700 include local area networks (LANs), wide area networks (WANs), wired telephone net- works, wireless networks, or any other network supporting data communication between respective entities.

[0214] Clients 1702 and 1704 may take many different forms. Non-limiting examples of clients 1702 and 1704 include personal computers, personal digital assistants (PDAs), cellular phones and smartphones.

[0215] Client 1702 includes a CPU 1726, a pointing device 1728, a keyboard 1730, a microphone 1732, a printer 1734, a memory 1736, a mass memory storage 1738, a GUI 1740, a video camera 1742, an input / output interface 1744 and a network interface 1746.

[0216] CPU 1726, pointing device 1728, keyboard 1730, microphone 1732, printer 1734, memory 1736, mass memory storage 1738, GUI 1740, video camera 1742, input / output interface 1744 and network interface 1746 may communicate in a unidirectional manner or a bi-directional manner with each other via a communication channel 1748. Communication channel 1748 may be configured as a single communication channel or a multiplicity of communication channels.

[0217] CPU 1726 may be comprised of a single processor or multiple processors. CPU 1726 may be of various types including micro-controllers (e.g., with embedded RAM / ROM) and microprocessors such as programmable devices (e.g., RISC or SISC based, or CPLDs and FPGAs) and devices not capable of being programmed such as gate array ASICs (Application Specific Integrated Circuits) or general- purpose microprocessors.

[0218] As is well known in the art, memory 1736 is used typically to transfer data and instructions to CPU 1726 in a bi-directional manner. Memory 1736, as discussed previously, may include any suitable computer-readable media, intended for data storage, such as those described above excluding any wired or wireless transmissions unless specifically noted. Mass memory storage 1738 may also be coupled bi-directionally to CPU 1726 and provides additional data storage capacity and may include any of the computer-readable media described above. Mass memory storage 1738 may be used to store programs, data and the like and is typically a secondary storage medium such as a hard disk. It will be appreciated that the information retained within mass memory storage 1738, may, in appropriate cases, be incorporated in standard fashion as part of memory 1736 as virtual memory.

[0219] CPU 1726 may be coupled to GU1 1740. GUI 1740 enables a user to view the operation of computer operating system and software. CPU 1726 may be coupled to pointing device 1728. Non-limiting examples of pointing device 1728 include computer mouse, trackball and touchpad. Pointing device 1728 enables a user with the capability to maneuver a computer cursor about the viewing area of GUI 1740 and select areas or features in the viewing area of GUI 1740. CPU 1726 may be coupled to keyboard 1730. Keyboard 1730 enables a user with the capability to input alphanumeric textual information to CPU 1726. CPU 1726 may be coupled to microphone 1732. Microphone 1732 enables audio produced by a user to be recorded, processed and communicated by CPU 1726. CPU 1726 may be connected to printer 1734. Printer 1734 enables a user with the capability to print information to a sheet of paper. CPU 1726 may be connected to video camera 1742. Video camera 1742 enables video produced or captured by user to be recorded, processed and communicated by CPU 1726.

[0220] CPU 1726 may also be coupled to input / output interface 1744 that connects to one or more input / output devices such as such as CD-ROM, video monitors, track balls, mice, keyboards, microphones, touch-sensitive displays, transducer card readers, magnetic or paper tape readers, tablets, styluses, voice or handwriting recognizers, or other well-known input devices such as, of course, other computers.

[0221] Finally, CPU 1726 optionally may be coupled to network interface 1746 which enables communication with an external device such as a database or a computer or telecommunications or internet network using an external connection shown generally as communication channel 1716, which may be implemented as a hardwired or wireless communications link using suitable conventional technologies. With such a connection, CPU 1726 might receive information from the network, or might output information to a network in the course of performing the method steps described in the teachings of the present invention. FIG. 18 illustrates a block diagram depicting a conventional client / server communication system, which may be used by an exemplary web-enabled / networked embodiment of the present invention.

[0222] A communication system 1800 includes a multiplicity of networked regions with a sampling of regions denoted as a network region 1802 and a network region 1804, a global network 1806 and a multiplicity of servers with a sampling of servers denoted as a server device 1808 and a server device 1810.

[0223] Network region 1802 and network region 1804 may operate to represent a network contained within a geographical area or region. Non-limiting examples of representations for the geographical areas for the networked regions may include postal zip codes, telephone area codes, states, counties, cities and countries. Elements within network region 1802 and 1804 may operate to communicate with external elements within other networked regions or within elements contained within the same network region.

[0224] In some implementations, global network 1806 may operate as the Internet. It will be understood by those skilled in the art that communication system 1800 may take many different forms. Non-limiting examples of forms for communication system 1800 include local area networks (LANs), wide area networks (WANs), wired telephone net- works, cellular telephone networks or any other network supporting data communication between respective entities via hardwired or wireless communication networks. Global network 1806 may operate to transfer information between the various networked elements.

[0225] Server device 1808 and server device 1810 may operate to execute software instructions, store information, support database operations and communicate with other networked elements. Non-limiting examples of software and scripting languages which may be executed on server device 1808 and server device 1810 include C, C++, C# and Java.

[0226] Network region 1802 may operate to communicate bi-directionally with global network 1806 via a communication channel 1812. Network region 1804 may operate to communicate bi-directionally with global network 1806 via a communication channel 1814. Server device 1808 may operate to communicate bi-directionally with global network 1806 via a communication channel 1816. Server device 1810 may operate to communicate bidirectionally with global network 1806 via a communication channel 1818. Network region 1802 and 1804, global network 1806 and server devices 1808 and 1810 may operate to communicate with each other and with every other networked device located within communication system 1800.

[0227] Server device 1808 includes a networking device 1820 and a server 1822. Networking device 1820 may operate to communicate bi-directionally with global network 1806 via communication channel 1816 and with server 1822 via a communication channel 1824. Server 1822 may operate to execute software instructions and store information.

[0228] Network region 1802 includes a multiplicity of clients with a sampling denoted as a client 1826 and a client 1828. Client 1826 includes a networking device 1834, a processor 1836, a GUI 1838 and an interface device 1840. Non-limiting examples of devices for GUI 1838 include monitors, televisions, cellular telephones, smartphones and PDAs (Personal Digital Assistants). Non-limiting examples of interface device 1840 include pointing device, mouse, trackball, scanner and printer. Networking device 1834 may communicate bidirectionally with global network 1806 via communication channel 1812 and with processor 1836 via a communication channel 1842. GUI 1838 may receive information from processor 1836 via a communication channel 1844 for presentation to a user for viewing. Interface device 1840 may operate to send control information to processor 1836 and to receive information from processor 1836 via a communication channel 1846. Network region 1804 includes a multiplicity of clients with a sampling denoted as a client 1830 and a client 1832. Client 1830 includes a networking device 1848, a processor 1850, a GUI 1852 and an interface device 1854. Non-limiting examples of devices for GUI 1838 include monitors, televisions, cellular telephones, smartphones and PDAs (Personal Digital Assistants). Nonlimiting examples of interface device 1840 include pointing devices, mousse, trackballs, scanners and printers. Networking device 1848 may communicate bi- directionally with global network 1806 via communication channel 1814 and with processor 1850 via a communication channel 1856. GUI 1852 may receive information from processor 1850 via a communication channel 1858 for presentation to a user for viewing. Interface device 1854 may operate to send control information to processor 1850 and to receive information from processor 1850 via a communication channel 1860.

[0229] For example, consider the case where a user interfacing with client 1826 may want to execute a networked application. A user may enter the IP (Internet Protocol) address for the networked application using interface device 1840. The IP address information may be communicated to processor 1836 via communication channel 1846. Processor 1836 may then communicate the IP address information to networking device 1834 via communication channel 1842. Networking device 1834 may then communicate the IP address information to global network 1806 via communication channel 1812. Global network 1806 may then communicate the IP address information to networking device 1820 of server device 1808 via communication channel 1816. Networking device 1820 may then communicate the IP address information to server 1822 via communication channel 1824. Server 1822 may receive the IP address information and after processing the IP address information may communicate return information to networking device 1820 via communication channel 1824. Networking device 1820 may communicate the return information to global network 1806 via communication channel 1816. Global network 1806 may communicate the return information to networking device 1834 via communication channel 1812. Networking device 1834 may communicate the return information to processor 1836 via communication channel 1842. Processor 18186 may communicate the return information to GUI 18188 via communication channel 1844. User may then view the return information on GUI 1838.

[0230] Advantages

[0231] The presently disclosed embodiments provide algorithmic methods, executed at least partially by processors of a computer, allowing for the convenient navigation of vast chemical space based on the input of one or more identifying pieces of information, including chemical structures and / or the like. Iterations of the algorithms may be created in the form of computer software distributable with a commercial license, or be otherwise be made in trial and / or full versions on a free basis as freeware.

[0232] Moreover, iterations of the presently disclosed embodiments may at least consider or account for accepting input information and / or conditions regarding at least the following as commonly encountered in the field of, for example (but not limitation thereto): industrial chemistry, which may consider temperature, pressure, radiation and other energy barrier breaking methods used together with synthetic catalysts. Further, information concerning enzymes may also be input, where such enzymes may function under very mild conditions of temperature and pH without necessarily requiring physical condition manipulations. Enzymes may also be highly specific for their substrates, where the disclosed, methods may accommodate the convenient searching thereof.

[0233] Providing for robust computational and combinatorial techniques, the disclosed embodiments efficiently navigate the sheer vast size of chemical space, considering and / or reviewing huge numbers of natural and synthetic molecules, a diversity of carcinogens, and consider apparent lacks of anisotropy and so on and so forth. Disclosed embodiments further also consider enumerations and the numerical reduction thereof to identified integer values such as 0, 1 , and 2 to, for example (but not limitation thereto) evaluate consistency, as well as employing multiple nested loops to consider certain and / or all periods of the periodic table, etc.

[0234] Numerical patterns were also observed across a variety of chemical reactions to set offset and / or calculative measures, such as a step of 27, which may be of particular value for certain atoms and lower index alpha amino acids, but not others.

[0235] Trial-and-error computational training approaches applied to chemical formula fragments employing previous methods produced incorrect structures concerning searching carcinogens, thus application of 72 as an offset calculative numerical figure was derived to produce usable and quality solutions.

[0236] Considerations of representational consistency as developed earlier may find applications as disclosed herein to better characterize chemical compounds suitable for the treatment of ailments such as cancer such as that phosphorous usually reverses inconsistency and so on and so forth.

[0237] Utilising the method according to the present invention, it has been possible to enumerate all compositions with all atoms up to Calcium:

[0238] After enumerating formulas above, there may be very large numbers of isomers in one or all the formulas. The method for generating lead compounds is from representational consistency, but what is the representation? For a protein, be it human, animal, bacterial or viral, the index calculated may be a very large number. It is not currently possible to synthetically produce long peptide sequences. What small molecules or peptides may inhibit the protein? (e.g. to discover drugs for cancer, antibacterial and antiviral and other medicines).

[0239] Observe the two kinds of semi-conductors in Table 1 having lattices with the same Z number repeating, just one short of the 48-maximum allowed in the model.

[0240] Table 1

[0241] C_H_ for Z=48 is enumerated using the method for generating lead compounds, and find just two formulas C6H12 and C7H6. The first has only 25 isomers, the second with a

[0242] SUBSTITUTE SHEET (RULE 26) ring size 6 restriction has only 51 isomers. Note that the entire chemical space C_H_N_O_ for Z=47 has no formulas.

[0243] A photon arriving at 11 -cis-retinol starts the visual cycle in the eye. This molecule contains a ring with SMILES C1 CCC(=C(C1 (C)C)C)C. This ring contains seven of the C6H12 isomers.

[0244] CC(C)=C(C)C Yes

[0245] CCCCC=C Yes

[0246] CCC(C)C=C Yes

[0247] CC(C)CC=C No

[0248] CCC(=C)CC No

[0249] CCCC(C)=C Yes

[0250] CC(C)C(C)=C Yes

[0251] CC(C)(C)C=C Yes

[0252] CC\C=C\CC No

[0253] CCC\C=C\C No

[0254] C / C=C / C(C)C No

[0255] CC\C(C)=C / C No

[0256] CCC=C(C)C Yes

[0257] Excluding the Oxygen atom at the conforming end of 11 -cis-retinol this pattern is repeated. Aside from the opsin protein binding double bonded Oxygen, the entire 1 lis-retinol molecule CC1=C(C(CCC1)(C)C)C=CC(=CC=CC(=CCO)C)C is constructed from these C6H12 fragments.

[0258] In the Pharma Leads applet, Atomic Oxygen is listed as reactant and Lysine as enzyme, the algorithm confirms the reaction. Oxygen atom dissociates from 11-cis-retinal which binds to the opsin at Lysine symbol K in bold.

[0259] Next, is the question of which amino acids may be n-type or p-type. The amino acids do not contain a pentavalent atom, but may contain the trivalent N atom. The nitrogen atom has valence 3 but belongs in a periodic table column with pentavalent atoms like phosphorous.

[0260] Observe that CN has a combined valence of 5, and C(=O)N has a combined valence of 3. No combination of CS in an amino acid has these valences either. Internal bonds are omitted and count remaining valence. Iterating through Z from 18 to 24 enumerating with MOLGEN there are no other three atom trivalent structures that may be found within an amino acid. All amino acids are n-type so they don't function like an electronic semi-conductor with both n and p types.

[0261] There are 44 different formulas C_H_N_O with Z=48, but those with one N and one O may be compatible with amino acid structures.

[0262] When the peptide bond links two amino acids Free amino acids together C(=O)N is formed.

[0263] C(=O)OH+N(H)H— >C(=O)N(H)+H2O

[0264] OH is also removed as the by-product of the peptide bond is H2O. Now the dipeptide has CC(=O) NCC with Z=48, for any pair of the 20 amino acids. This is repeated in every protein at every peptide linkage.

[0265] The side chain or R-group of sixteen amino acids contributes an extra overlapping group with Z=48. Specifically, NC(CC)C=O is part of Asp, Glu, Pro, His, Arg, lie, Lys, Met, Phe, Gin, Trp, Tyr, Vai, Asn, Leu and Thr. The Gly, Ala, Cys, Ser amino acids do not contain this fragment and do not contain C4H9NO unless they are bound.

[0266] In an embodiment, a new component is added that may filter down to a few SMILES (i.e. specific structure diagrams). For example, the eye disease Glaucoma causes progressive loss of sight, that may end in total blindness, there are five new chemical structures / compounds. These are thiols and thiophanes related to P3HT, an eye injectable molecule undergoing human clinical trials for Retinitis Pigmentosa. There are several recent patents from Lanzani et al in Italy and in China which use P3HT.

[0267] The idea of using groups of atoms of a certain maximum number is previously disclosed. For example, FIG. 4b showed a four times nested loop for that.

[0268] A classic semiconductor is a lattice repeating groups of atoms one short of that maximum. I am referring to As-Si and Si-B(-Si)-Si in SMILES notation.

[0269] In some embodiments, an important molecule in the eye is 11 -cis-retinal which converts light into a chemical change. It binds to an Opsin protein, there are several of them. It always binds to a Lysine amino acid on the Opsin protein. The Oxygen atom on the 11 -cis-retinal binds to that Lysine within the Opsin protein. This interaction conforms exactly to this inventions FIG. 6. Atomic Oxygen is the reactant and Lysine is the enzyme / catalyst. In fact if you try any other amino acid with a different index, the method 16 / 572482 rejects it.

[0270] 11 -cis-retinal graph has been analyzed to see how many groups are near the previously mentioned 48 maxi- mum number. It turns out almost the whole molecule is at this maximum. Other molecules have been tried, such as, not a limitation, the amino acids. In their free form, some of the amino acids are neurotransmitters or have signaling functions in the brain. And other amino acids are not. The amino acids with such maximum groups are neurotransmitters. The other amino acids are not neurotransmitters and have few or no such groups of atoms. An algorithm is coded to parse a SMILES and count these groups of atoms. Input other neurotransmitters and made a list including "Free amino acids" and "Neurotransmitters". All of these have this exact same property.

[0271] 11-cis-retinal

[0272] Free amino acids

[0273] SUBSTITUTE SHEET (RULE 26) Neurotransmitters

[0274] FIG. 19 illustrates an exemplary flowchart configured to find a molecular formula / s with a new added component that may filter down to a few SMILES (i.e. specific structure diagrams), in accordance with an embodiment of the present invention. Preferably, up to three indices are determined utilising a SMILES string.

[0275] Accordingly, in this embodiment, the computational and / or combinatorial computer- implemented algorithmic search technique follows the sequence:

[0276] SUBSTITUTE SHEET (RULE 26)

[0277] A Step 1905 is the enumerate process above. A Step 1907 is a formula list. A Step 1910 is external because a prior art software is run like, not a limitation, MOLGEN or the new surge / nauty. This gives a list of SMILES strings one formula at a time in a Step 1915. In a Step 1920, the SMILES string is parsed into a graph of atoms and bonds. Then the new method is performed in a Step 1925, as explained above, which gives three counters in a Step 1930. The number of Z less than 47, the number of Z at 47 and the number of Z equal

[0278] SUBSTITUTE SHEET (RULE 26) 48. In a decision Step 1935, if all #Z<47, a YES branches to a Step 1945 that decides to discard the SMILES if the last two counters are zero and only the first counter is nonzero. The NO branch proceeds to a Step 1940 which displays the SMILES and the three counters.

[0279] The invention reduces the chemical space by some enormous numbers like a 118 trillion (billion US) times for twelve atoms, and this number increases with size. The mass filter only reduces 2-3 times. But it helped find something really unusual about P3HT (poly- 3-hexyl-thiophane). If starting with the maximum number and enumerate the formulas for the hydrocarbons (C and H atoms only), there are a lot of formulas and thousands of structures. But if adding a Sulfur atom and turning on the mass filter, there may be only one chemical formula. And, that may be contained inside the P3HT formula. In other words, part of P3HT is a unique analog of retinal. A unique analog is something extremely rare in a chemical space which may easily run into millions of formulas.

[0280] Poly 3 hexylthiophene (P3HT) is a polymer of 3-hexylthiophene, from the table below. You may see why P3HT is exactly the kind of molecule to find. P3HT fits the same profile as 11 -cis-retinal.

[0281] 3 -hexylthiophene

[0282] Novel thiophene analogs of P3HT

[0283] SUBSTITUTE SHEET (RULE 26) Novel thiophene analogs of P3HT

[0284] So, how to make more analogs of retinal that are novel to experiment with but not yet synthesized and patentable molecules? And, how to find and make more analogs of other neurotransmitters? And, more importantly how to discover the hidden structures that make the eye work?

[0285] There are 1455932 isomers of C10H14S but few contain thiophene C1=CSC=C1. In some embodiment, the starting point may be rotated to get a couple more SMILES for thiophene, C1SC=CC1= and C1C=CSC1. Then run the filter which lists nine isomers and five may be the best, none of these have ever been synthesized.

[0286] A simpler molecule is C=Cc1cscc1C which is not buyable, but may be made from available reactants C=C[Sn](CCCC)(CCCC)CCCC and Cc1cscc1 Br via the reaction C=C[Sn](CCCC)(CCCC)CCCC.Cc1cscc1 Br»C=Cc1cscc1C.

[0287] The periodic table shows atomic numbers but it also shows mass numbers. The invention extends the atomic number to an index for any molecule. But what about the mass? This is not easy the mass is an input into physical equations and nothing suggests a useable constraint. The rule of 5 does have a mass restriction but it is an absolute which has been exceeded in practice.

[0288] The FDA produces a book, called Orange Book, listing all active pharmaceutical ingredients. It is download- able as a file. So it was imported into the software. After a while, something was noticeably unusual about drug indexes versus non-drug indexes. The masses are computed of all the formulas as they were being enumerated. The drugs are clustered right at the center of the range of masses. Approximately 75% of drugs are between two measures of the center. So that is a mass filter.

[0289] FIG. 20 illustrates an exemplary flowchart 2000 that is configured to determine drug like formulas, in accordance with an embodiment of the present invention.

[0290] Accordingly, in this embodiment, the computational and / or combinatorial computer- implemented algorithmic search technique follows the sequence:

[0291] SUBSTITUTE SHEET (RULE 26)

[0292]

[0293] A decision Step 2005, decides if an atom corresponds to a mass being computed, or if it is an amino acid, DNA or RNA molecule including the backbone. On a Yes side, the mass is stored in an MW of the atom. On the No branch, the weight is stored in MW of an amino acid, DNA or RNA molecule. In a Step 2020, the mass is stored in an array. In a next step 2025, the formulas array may be retrieved. Then, in a Step 2030, variable "dformulas" is set to 0. In a Step 2035, index "i" is initialized to 0. Two loop initializations are performed before looping over the formulas. Within the two loops, the atoms are looped over in each formula.

[0294] In a decision Step 2055, if "i" is less than the number of atoms in the formula, Step 2040

[0295] SUBSTITUTE SHEET (RULE 26) calculates the mass of the formula from the known masses of its atoms, amino acids, DNA or RNA molecules, called formulamw in a Step 2045. FIG. 5 shows how to calculate an index by replacing Z(Zi) with MW(Zi), and replacing index with formulamw. After the loop limit "i" of the inner loop is reached, the flow may proceed to a Step 2060 to update three numbers; average mass (avgmw), minimum mass (minnow), maximum mass (maxmw). Then the loop limit of the outer loop may be checked in a decision Step 2065. If the loop limit is reached (YES in Step 2065), flow proceeds to a next Step 2070 that calculates lowmw, the first measure of centre of all formula masses. In a following Step 2075, avgmw, the second measure of centre of all formula masses is calculated. An inner loop in succeeding Steps 2080 through Steps 2097 may keep drug like formulas and an outer loop discard the others. The loop, in Step 2085, looks up formulamw to see if it is outside the two measures of centres lowmw and avgmw. The NO branch (inner loop) in Step 2085 keeps the formula as druglike in Step 2090 and the YES branch (outer loop) discards formula(s) that are not drug like. Step 2097 continually check if all the formulas are tested (NO side). If all formulas are tested (YES side), the program ends in a Step 2099.

[0296] The protein index is a different algorithm. FIG. 5 shows how to calculate an index, and FIG. 12 shows an example of a peptide bond. FIG. 15 dipeptides found in CYP2EI enzyme as a special case where an input parameter is 2. FIG. 16 shows a table of certain dipeptides in that enzyme, also improved to consider all dipeptides in the protein. At least one chemical formula, not a limitation, may be input and a search space to obtain a list of chemical formulas that might competitively inhibit the formula. This is improved because a protein may be input, and the search space may be automatically chosen. The above searches may be used twice to obtain a list of formulas such as, not a limitation, amino acids or proteins that may cause drug resistance. To do the search automatically, FIG. 6 may be used to perform multiple searches.

[0297] FIG. 21 illustrates an exemplary flowchart 2100 that is configured to select a drug formula to inhibit protein that may cause drug resistance, in accordance with an embodiment of the present invention.

[0298] Accordingly, in this embodiment, the method comprises; determining a first index such that the protein does not metabolise the target molecule. Preferably, the method further comprises determining a second index such that drug resistance from the protein is reduced or eliminated. More preferably, the method further comprises further comprising determining a third index such that the protein does not metabolise the lead compound. More preferably, the chemical space to be investigated is reduced to a protein, the DNA or RNA sequence thereof, or proteins generated from said DNA or RNA sequences, most preferably to a list of dipeptides.

[0299] Accordingly, in this embodiment, the computational and / or combinatorial computer- implemented algorithmic search technique follows the sequence: To illustrate, the above analysis was conducted on a number of Opsin proteins.

[0300] Humans have a total of nine opsins, most prominently found in photoreceptor cells of the retina. Five classical groups of opsins are involved in vision.

[0301] The indexes that were chosen specifically use the Germanium like series.

[0302] SUBSTITUTE SHEET (RULE 26) Starting from 32, the series of indexes are 32 + 72, 32 + 2X 72, and so on. The series links the semiconductors Silicon and Germanium to many peptides found in light sensitive proteins, most notably the opsin proteins.

[0303] There is however another distinct advantage of being able to identify light sensitive DNA coding regions or proteins. In the modern world, humans are bombarded by radiation of many kinds, especially microwave radiation and X-rays, and natural cosmic radiation. These have been linked to cancer.

[0304] Being able to pinpoint these specific DNA regions, peptides and proteins can be very helpful in combatting cancer.

[0305] Long Wave Opsin P04000

[0306] X chromosome

[0307] 154144284-154144395

[0308] 154150656-154150952

[0309] 154152940-154153108

[0310] 154154574-154154739

[0311] 154156294-154156533

[0312] 154158816-154158923 index 176 364 residues

[0313] 3..42 QW

[0314] 148..1492 WE

[0315] 31..33 3 NSN

[0316] 36..38 3 RGP

[0317] 185..187 3 PPI

[0318] 204..206 3 PDV

[0319] 317..319 3 NPV

[0320] Medium Wave Opsin P04001

[0321] X chromosome

[0322] 154182678-154182789

[0323] 154187770-154188066

[0324] 154190054-154190222

[0325] 154191688-154191853

[0326] 154193408-154193647

[0327] 154195930-154196037 1 st exon

[0328] 3..4 2 QW

[0329] 31..33 3 NSN

[0330] 2nd exon: not found

[0331] 3rd exon 8..92 WQ

[0332] 4th exon 11..13 3 PRG

[0333] 18..203 DCP

[0334] 36..38 3 LPP

[0335] 5th exon

[0336] 9..11 3 PLP

[0337] 10..12 3 LPP

[0338] 6th exon: not found

[0339] Short Wave Opsin P03999 Chromosome 7 128775439-128775781 128774986-128775154 128774498-128774663 128773649-128773888 128772543-128772659

[0340] Exon 1

[0341] 54..55 2 EW

[0342] 55..56 2 WE

[0343] 19..21 3 EDA

[0344] 20..22 3 DAE

[0345] 82..84 3 PIP

[0346] Exon 2

[0347] 3..5 3 PIP Not found on exons 3 to 5

[0348] The reason why none of the opsin proteins themselves have the index above as most frequent is that the more frequent peptide must be a dopant. The Si / Ge like peptides are the non-dopant.

[0349] In one embodiment of the present invention, there may be two parts to the search, not a limitation, one selects a drug to inhibit the protein, the second search asks the question, does the protein destroy such a drug. If so, it rejects it, and tries a less ranking alternate. The first protein step is shown in the left column of flowchart 2100.

[0350] In some embodiments, flowchart 2100 looks over the protein sequence for a drug that is an overall match. It must be given a number as parameter. If it is given a penicillin binding protein (PBP), it will discover all of the drugs in the penicillin family. The penicillin binding proteins vary in length and don't resemble each other. The first protein step always finds a penicillin index as you select different PBP proteins with number 3 as parameter. The penicillin family consists of the compounds Penicillin F, Penicillin G, Penicillin K, Penicillin 0, Penicillin X, Epicillin and Penicillin N.

[0351] With some proteins like COVID-19 there is nothing left after the second step does an exhaustive computation. But if we settle for the least possible resistance and choose a protein in the organism that is susceptible an existing cancer drug was identified for COVID- 19.

[0352] In other embodiments, a protein sequence is needed as input, in a Step 2102, which may either be obtained from an online database or from a sample through PCR and sequencer machines. If the sequence is a DNA or RNA sequence, it must be translated into a protein sequence by well-known methods. Secondly, a sublength is needed as input in a Step 2104. Before running the inputs, a Z is precomputed for each free amino acid. Please note Z may not be the same as the Z of the amino acid residue within the protein, because it is minus some water molecules. Also, before running, Z is precomputed for all the drugs in the FDA Orange Book. That will help get a picture of drug protein interactions. For example, a Penicillin Binding Protein Wl YKR2 with the sequence;

[0353] GNVRKASFNPRQQPQQQPAQQEQKDSDGVAGWIKDMFGSN, each letter in the sequence is an amino acid residue. The Z for each free amino acid may be obtained as previously demonstrated above. Summing the Z from each and subtracting Z=10 for each peptide bond (i.e. the water molecule byproduct of a peptide bond) gives Z=390 for the protein. For purposes of demonstration, choose a sublength of 2 in Step 2104. After running the left or first column of FIG. 21 , index "146" occurs 7 times. This is eliminated by the other two columns of flowchart 2100. Then index "140" occurs 3 times so that is the answer.

[0354] Another example is Penicillin Binding Protein K1 SCA6 with the sequence

[0355] MPENLQNAVIAVEDKDFRSEPGINVKRTIAAALNEFTGNALLGSKQGASTLEQQLVKNLTG DSEQDI LRKVREI FRALGLCN RYSKETI LEAYLNTI PLTGTI YGM EAGAQEYFGKSVEELSLA ECAELASITKNPKSFNPATNPENLLKRRNHVLA.

[0356] Summing the precomputed Z from each amino and subtracting Z=10 for each peptide bond (the water molecule byproduct of a peptide bond) gives Z=1560 for this protein. For purposes of demonstration choose a sublength of 2 in Step 2104. After running the left column of flowchart 2100, index "126" occurs 17 times. This is eliminated by the other two columns of flowchart 2100. Then index "110" occurs 11 times so it is the answer. Note that K1SCA6 is a human protein from the human gut microbiome.

[0357] In the following embodiments, some loop counter and internal variables in Steps 2106 and 2110 are initialized and three arrays created in a Step 2108, including, not a limitation, a Z array, a count array and resist array. The outer loop counter is variable "i". In W1YKR2 the outer loop counter selects, not a limitation, GN, NV, VR and so on ending with SN. The inner loop exemplifies FIG. 5. The inner loop counters are "j" and "npos". In a decision Step 2112, variable "j" is checked if "j" is pointing to the letter in the sequence and variable "npos" is checked if "npos" is pointing to the same letter in the subsequence. At first with GN, in a Step 2114, the inner loop counters selects G then N to obtain sumz= Z[G]+ Z[N] = 70 + 40. In a Step 2116 after the inner loop, sumz is amended from 110 to 100 by subtracting 10.

[0358] Then, in a Step 2120, the Z array is checked to see if it already contains the sumz 100. Prior Step 2118 ensures “sumz” is valid. The NO branch in Step 2120 proceeds to a Step 2124 that adds the “sumz” number to the Z array, adds 1 to the “countarray”, and adds 0 to the “resistarray”. The “countarray” stores the number of times the same number is found. Z array is

[0100] , count array is [1], resistarray is [0], Then the NO branch proceeds in a Step 2130 that increments the outer loop counter “i" and may reach the loop limit. The YES branch of Step 2120 moves to a Step 2122 that finds the place “ipos” in the Z array containing “sumz” and increments the “countarray” at the same location. Then a decision Step 2126 checks the number of times sumz 100 occurred and if it is more than “maxnum”. If YES, the new maxnum is set and sets “maxpos” to ipos in a Step 2128. Now maxnum = 100 and maxpos = 0. Then increments the outer loop counter “i" in Step 2130 and may reach the loop limit. Now the loop will do sumz = Z[N] + Z[V] = 70 + 64, subtract 10 from 134 setting sumz to 124 in Step 2114. If lookup Z array doesn’t contain 124, Step 2112 takes the NO branch. In Step 2108, Z array becomes [100, 124], count array [1 , 1] and resist [0, 0], Next the loop will do, in Step 2116, sumz = Z[V] + Z[R] = 64 + 94, subtract 10 to set sumz = 148. Z array becomes [100, 124, 148], count array [1 , 1 , 1], and resist [0, 0, 0] in Step 2108. The loop continues until SN, sumz = 116, Z array [100, 124, 148, 164, 118, 94, 134, 122, 146, 162, 130, ... , 116] and count array [3, 1 , 3, 1 , 2, 2, 1 , 1 , 7, 1 , 3, ... , 3] and maxnum = 146 with maxpos = 7 in Step 2128.

[0359] The loop limit ends the loop by testing the outer loop counter "i" in a Step 2132. In the case of W1YKR2 with sublength=2, the loop ends after SN has been pro- cessed. Then maximum 7 and Z array[maxpos]=146.

[0360] Instead with Wl YKR2 with sublength=3 the left column flowchart would start with GNV and end after GSN has been processed. It is computing Z[G]+Z[N]+Z[V]- 20 through to Z[G]+Z[S]+Z[N]- 20, and then computing which number repeats the most in Z array[maxpos] and how many times in maxnum.

[0361] Now, at this point if this is run with tripeptides of the many penicillin binding proteins, the index "186" occurs 36 times in each protein, despite considerable variation in the sequences. This is the index of Epicillin. Furthermore, the next few ranking indexes are from compounds Penicillin F, Penicillin G, Penicillin K, Penicillin 0, Penicillin X and Penicillin N.

[0362] There may be more indexes in proteins than their repetition. Referring to FIG. 6, if Targets are chosen on longer subsequences, for example in W1YKR2, the Targets of GNVR, NVRK, through to FGSN may give indexes. Also, the Targets of GNVRK, NVRKA, through to MFGSN may give indexes. The same number may be provided, many times. This may be continued longer than five (5) letters but there is a limit because of the step. The indexes may be out of range.

[0363] Why would the protein target itself? Why is the protein an enzyme for itself? The index contains many organic and other compounds other than this part of the protein. It is not targeting itself, but rather these analogs. If the protein may break such analogs down first, they will not affect the protein itself. The purpose of the next two columns of the flowchart is to eliminate such numbers as indexes for the protein. These steps work on the Z array which have already been built.

[0364] The branch testing maximum in a Step 2134 is just to check validity, expected to always be true. Then some initializations follow in a Step 2136. Variable "bResistant" is used as a termination condition later. Variable "ifreqind" is a frequent index being tested, starting with the one from the first column of the flowchart. Variable "ires" is a position inside the Z array. Then a loop counter "i" in a Step 2138 is initialized. In a Step 2140, (The branch applies FIG. 6) tests if the frequent index has a target in the Z array. The YES branch of Step 2140 proceeds to a Step 2142 that set variable “bResistant to true, increments "resist" at maxpos, and sets "ires" to this position of the Z array. The NO branch skips the initialization. The loop continues to a Step 2146 until the end of the Z array.

[0365] After the loop goes through the Z array, comes a test for "bResistant" in a Step 2148. The YES branch will proceed to look for longer sequences in a Step 2150. The variable "ilen" will be the length, and is initialized by dividing the enzyme index by 108, or whatever highest index amino acid is. Next comes a loop, in a Step 2152 that is initialised by creating another array "nextind" for "ilen" sequences. It is defined in the left column of the flowchart with "ilen" for the sublength parameter. In a Step 2154 (The branch applies FIG. 6) test, the frequent index is checked if the variable has a target in the "nextind" array. The YES branch proceeds to a Step 2156 that sets bResistant YES, increments resist array at "maxpos", and goes to the third column of the flowchart. The NO branch (of Step 2154) proceeds to increment the sequence length ("ilen") in a Step 2158, and may reach loop limit in a Step 2160. The loop limit checks if the "ilen" is within range. The upper limit on the sequence length ("ilen") is the enzyme index divided by 40, the least index amino acid. If the upper limit on the sequence length is reached, flow proceeds to the third column.

[0366] The third column, in a Step 2162, tests if not bResistant. If so (YES) terminates with the same index that was started with in a Step 2164. If bResistant (NO), then a next Step 2166 is to create a frequency dictionary, keyed by the count array. A dictionary is a standard algorithm and data structure. A next Step 2168 is to sort the dictionary. Now comes a loop (i.e. STEPS 2170-2180) over next most frequent index. The loop contains two loops like the two loops on the middle column of the flowchart. The first loop goes through the Z array for an enzyme. The second loop builds an array of indexes for longer sequences, and goes through that for an enzyme. In a Step 2182, if not bResistant, then the next most frequent index is displayed and terminates in a Step 2184. Otherwise, the limit of loop over next most frequent index is reached. The loop limit checks for the end of the dictionary in a Step 2186. After the loop ends either display the first Z array entry with minimum resist array value or nil in a Step 2188. If display nil there is no answer, every possible molecule is eliminated with this input parameter.

[0367] An example from a highly resistant and difficult organism is 2019-nCov aka COVID-19. With sub length 5 and proteins P0DTC1 to P0DTC9 the flowchart ends after exhaustive computation to display nil. The table shows some of its proteins have indexes.

[0368] A variation of the algorithm is to create a third array to count resistance, and output the first index with least resistance instead of nil.

[0369] Another variation is to print peptide sequences, or to lookup a peptide database for human peptides to filter out answers. Since peptides end in Hydrogen atoms at both ends, some substitutions are needed. V to P, T to P, C to P, I to D, L to D, M to E, K to E, H to K and Y to R.

[0370] FIG. 22 illustrates an exemplary group of compounds 2100 configured to be formulated in the form of, not a limitation, an intraocular injectable solution, in accordance with an embodiment of the present invention. In one embodiment, a composition comprising at least one of the compounds, and pharmaceutically acceptable excipients, may be formulated in the form of an intraocular injectable solution, such composition further comprising one or more active ingredients.

[0371] In other embodiment, a method for creating syn- thetic molecules that may consistently represent sensations of sight for a person whose visual system is impaired or damaged is provided. Where the compound is selected using the tabulated three counters so that not all belong to the first counter, and some of the second or third counter not zero. These counters have been described in paragraph

[0267] and are further referenced in the tables headed Groups Z<47, Groups Z=47 and Groups Z=48 and in FIG. 19. Such structures with a similar function to neurotransmitter molecules in the eye, brain and central nervous system. Aforesaid counters depending on structure diagrams and exact placement of Hydrogen atoms not usually shown in chemical structure diagrams.

[0372] SUBSTITUTE SHEET (RULE 26) In another embodiment, compounds 2100 may include a unique analog of repeating groups of Carbon, Hydrogen atoms from 11-cis-retinal. The analog may contain Sulfur, Carbon and Hydrogen atoms where the Sulfur atom being from the same column in periodic table as the solitary Oxygen in retinal. The analog meaning a chemical formula with the same index as previously invented.

[0373] In a further embodiment, there is provided a method for the treatment of an eye disease, the method comprising administering an effective amount of a compound to a patient in need, where the compound is selected from the group comprising of 5-0-6a, 5-0- 6b, 5-0-6c, 4-0-7a to 4-0-7e, 8-0-3, 10-0-1 a, 8-0-3b and 3-0-8a or any combination thereof.

[0374] The eye disease to be treated may be an eye disease of the macular. The macular eye disease may be selected from, without limitation, the group comprising of age-related macular degeneration (AMD), central serous chorioretinopathy, angioid streaks, myopic macular degeneration, macular hole, epiretinal macular membranes, traumatic maculopathy and macular dystrophies.

[0375] In another embodiment, eye disease to be treated may be an eye disease of the the peripheral retina. The retina eye disease may may be selected, without limitation, from the group comprising glaucoma, retinal detachment, retinopathy of prematurity, retinal degenerations or retinoschisis.

[0376] In a further embodiment, the eye disease to be treated may be selected from, without limitation, the group comprising diabetic retinopathy (proliferative and non-proliferative), retinal artery or vein occlusions, retinal arterial macroaneurysm, colour vision defects, benign (retinal angioma, astrocytic hamartomas) or malignant (retinoblastoma, lymphoma) tumours.

[0377] All the features disclosed in this specification, including any accompanying abstract and drawings, may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.

[0378] Having fully described at least one embodiment of the present invention, other equivalent or alternative methods of implementing novel computational and / or combinatorial computer-implemented algorithmic search techniques for chemical structures, moieties, formulas and / or the like for in-silica, e.g., performed via computer simulation in reference to biological or biochemical experiments, etc., lead generation according to the present invention will be apparent to those skilled in the art. Various aspects of the invention have been described above by way of illustration, and the specific embodiments disclosed are not intended to limit the invention to the particular forms disclosed. The particular implementation of the novel computational and / or combinatorial computer-implemented algorithmic search techniques may vary depending upon the particular context or application. By way of example, and not limitation, the novel computational and / or combinatorial computer- implemented algorithmic search techniques described in the fore- going were principally directed to chemical, biological, biochemical and related implementations; however, similar techniques may instead be applied to the field of genetics, physics, quantum theory and / or the like, which implementations of the present invention are contemplated as within the scope of the present invention. The invention is thus to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the following claims. It is to be further understood that not all of the disclosed embodiments in the foregoing specification will necessarily satisfy or achieve each of the objects, advantages, or improvements described in the foregoing specification.

[0379] The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

THE CLAIMS DEFINING THE INVENTION ARE AS FOLLOWS:

1. A method for selecting from a chemical space a chemical structure that reacts with, or catalyses, a target molecule utilising computational and / or combinatorial computer- implemented algorithmic search techniques to permit computer simulation of such a reaction or catalysis wherein the chemical space comprises a protein, the DNA or RNA sequence thereof, or a protein generated from said DNA or RNA sequences: which method comprises the steps of: analysing the protein to identify an index associated with the peptides present; inputting a peptide to search for and the protein associated index identified, into an executable program stored on a non-transitory computer-readable storage medium, wherein the program instructs one or more processors to perform a method comprising: steps for inputting a peptide to search for; steps for inputting a list of valences required for each atom; steps for inputting a list of atoms comprising the space to search; steps for calculating the index associated with the peptides present, a constant number index step; steps for enumerating all sums which add to precisely a constant number corresponding to the result of employing a partition algorithm based upon certain atomic numbers and said constant number index step; steps for determining the quantity of a first atom; steps for Subenumerating to choose the other atoms wherein said Sub-enumerating steps recursively calls itself; steps for branch testing iform in said Sub-enumerate steps, which defers H quantity to last; steps for calculating an H quantity in Isomer with a maximum hydrogen; steps for interpreting a formula as all non-fragment isomers of said formula, wherein bonds between two atoms are either single, double or triple, and Isomers with rings are allowed as well as non-cyclic isomers and isomers of any topology, and wherein a canonical isomer comprises a maximum number of H or valence 1 atoms; steps for configuring atoms in a line with highest valence atoms at both ends, single bonded to form a canonical isomer; steps for adding a double bond, triple bond or ring will reduce number of H by an even number; steps for branch testing maximum h, which compares canonical isomer to a putative partition, wherein if test false leaves odd number of H all isomers of this kind are optionally simultaneously be rejected, and if test true prints the formula with numbers of each atom specified; steps for calculating a maximum hydrogen number, wherein the first branch skips H itself and any omitted atoms, and wherein said maximum hydrogen number steps loops over other atoms to find maximum valence, incrementing said maximum hydrogen number in the loop, except valence 1 are decremented; steps for calculating a second highest valence, in which branches test if there is a solitary atom then determines that N has the second highestvalence, and in which a branch on i skips H and any omitted atoms once again; and steps for generating a final chemical structure, moieties, or formulas for in-silico analysis; and, filtering the final chemical structure, moieties, or formulas, based on a selected chemical structure exhibiting the same, or a similar index by mass.

2. A method according to claim 1, further comprising inputting the filtered chemical structure into a computer simulation to carry out biological or biochemical experiments as a means for lead generation.

3. A method according to claim 2, further comprising the steps for presenting the periodic table up to atomic number 48, being 24 spin up and 24 spin down.

4. A method according to claim 1, wherein the mass filtering step in the computational and / or combinatorial computer-implemented algorithmic search follows the sequence:

5. A method according to claim 1 , further comprising subjecting the filtered chemical structure to a SMILES string analysis.

6. A method according to claim 5, wherein the SMILES string analysis in the computational and / or combinatorial computer-implemented algorithmic search follows the sequence:SUBSTITUTE SHEET (RULE 26)7. A method according to claim 1 , wherein the chemical structure sought functions to inhibit a protein, which method comprises; determining a first index such that the protein does not metabolise the target molecule, and inputting the first index determined into the computational and / or combinatorial computer-implemented algorithmic search.SUBSTITUTE SHEET (RULE 26)8. A method according to claim 7, further comprising: determining a second index such that drug resistance from the protein is reduced or eliminated and inputting the second index determined into the computational and / or combinatorial computer-implemented algorithmic search.

9. A method according to claim 8, wherein the computational and / or combinatorial computer-implemented algorithmic search technique following the sequence:

10. A method according to claim 9, wherein the wherein the chemical space to be investigated is reduced to a list of peptides, preferably dipeptides or tripeptides.SUBSTITUTE SHEET (RULE 26)11. A method for selecting a chemical structure that reacts with, or catalyses, a target molecule that represents sensations of sight for a person whose visual system is impaired or damaged and exhibiting a similar function to neurotransmitter molecules in the eye, brain or central nervous system of a human,, from a chemical space comprising protein, the DNA or RNA sequence thereof, or a protein generated from said DNA or RNA sequences, utilising computational and / or combinatorial computer-implemented algorithmic search techniques to permit computer simulation of such a reaction or catalysis which method comprises the steps of: analysing the protein to identify an index associated with the peptides present; inputting a peptide to search for and the protein associated index identified, into an executable program stored on a non-transitory computer-readable storage medium, wherein the program instructs one or more processors to perform a method comprising: steps for inputting a peptide to search for; steps for inputting a list of valences required for each atom; steps for inputting a list of atoms comprising the space to search; steps for calculating the index associated with the peptides present, a constant number index step; steps for enumerating all sums which add to precisely a constant number corresponding to the result of employing a partition algorithm based upon certain atomic numbers and said constant number index step; steps for determining the quantity of a first atom; steps for Subenumerating to choose the other atoms wherein said Sub-enumerating steps recursively calls itself; steps for branch testing iform in said Sub-enumerate steps, which defers H quantity to last; steps for calculating an H quantity in Isomer with a maximum hydrogen; steps for interpreting a formula as all non-fragment isomers of said formula, wherein bonds between two atoms are either single, double or triple, and Isomers with rings are allowed as well as non-cyclic isomers and isomers of any topology, and wherein a canonical isomer comprises a maximum number of H or valence 1 atoms; steps for configuring atoms in a line with highest valence atoms at both ends, single bonded to form a canonical isomer; steps for adding a double bond, triple bond or ring will reduce number of H by an even number; steps for branch testing maximum h, which compares canonical isomer to a putative partition, wherein if test false leaves odd number of H all isomers of this kind are optionally simultaneously be rejected, and if test true prints the formula with numbers of each atom specified; steps for calculating a maximum hydrogen number, wherein the first branch skips H itself and any omitted atoms, and wherein said maximum hydrogen number steps loops over other atoms to find maximum valence, incrementing said maximum hydrogen number in the loop, except valence 1 are decremented; steps for calculating a second highest valence, in which branches test if there is a solitary atom then determines that N has the second highestvalence, and in which a branch on i skips H and any omitted atoms once again; and steps for generating a final chemical structure, moieties, or formulas for in-silico analysis; and, filtering the final chemical structure, moieties, or formulas, based on a selected chemical structure exhibiting the same, or a similar index by mass.

12. A method according to claim 11 , further comprising subjecting the filtered chemical structure to a SMILES string analysis.

13. A method according to claim 12, further comprising the steps of creating synthetic molecules that represent sensations of sight for a person whose visual system is impaired or damaged; selecting a compound using tabulated three indices, so that not all belong to a first index, and a second or third index not zero; such structures with a similar function to neurotransmitter molecules in the eye, brain and central nervous system; the aforesaid indices depending on structure diagrams and exact placement of Hydrogen atoms not usually shown in chemical structure diagrams.

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