266results about "Chemical structure search" patented technology

A method and system for multi-scale anatomical and functional modeling of coronary circulation is disclosed. A patient-specific anatomical model of coronary arteries and the heart is generated from medical image data of a patient. A multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model. Blood flow is simulated in at least one stenosis region of at least one coronary artery using the multi-scale function model of coronary circulation. Hemodynamic quantities, such as fractional flow reserve (FFR), are computed to determine a functional assessment of the stenosis, and virtual intervention simulations are performed using the multi-scale function model of coronary circulation for decision support and intervention planning.

The invention disclosed herein concerns a data processing means for user tunable and selectable searching of a database wherein the data contained therein have associated descriptive properties capable of being expressed in numeric form. A quantized vector representative of the descriptive properties is created for each item in the database. This quantized vector becomes the fingerprint for each data item. The user submits a query item to be matched against the database for similarity. A fingerprint is calculated for the query item. The user may then assign weights to the individual descriptive properties based upon perceived importance. A newly weighted fingerprint for the query item is then compared with the weighted fingerprints for all the data in the database. A list of results sorted in order of decreasing similarity is presented to the user. The user may then change the previously assigned weights and then re-run the similarity search. This may be done as often as necessary to achieve the desired results. The invention describes similarity searching in a generic database. However, this invention is particularly desirable in databases containing chemical compound structure data or biological response screening result data. The process described herein may be run stand alone or as a preliminary screening search in a large database. If used for screening, it can greatly reduce the amount of data required for exactly matching a query item to the data in the database.

An extension of the vector space model for computing chemical similarity using textual and chemical descriptors is described. The method uses a chemical and/or textual description of a molecule/chemical and a decomposes a molecule/chemical descriptor matrix by a suitable technique such as singular value decomposition to create a low dimensional representation of the original descriptor space. Similarities between a user probe and the textual and/or chemical descriptors are then computed and ranked.

Techniques for similarity searching are provided. In one aspect, a method of searching structural data in a database against one or more structural queries comprises the following steps. A desired minimum degree of similarity between the one or more queries and the structural data in the database is first specified. One or more indices are then used to exclude from consideration any structural data in the database that does not share the minimum degree of similarity with one or more of the queries.

The invention discloses a lead compound virtual screening method and device. The method includes the steps of generation of molecular fingerprints of lead compounds on drug targets and bioactivity prediction of interaction between the lead compounds and the drug targets. The generation of the molecular fingerprints includes a molecular fingerprint part based on a module unit, a weighting molecularfingerprint part and a bioactivity part. During the bioactivity prediction, ligand molecular fingerprints and bioactivity values are utilized to serve as input of a random forest regression model, and a prediction model is constructed. Additionally, the device includes a universal tool for virtual screening on the basis of ligands, a prediction tool for the bioactivity generated when the lead compounds take effects on the drug targets, and a generation tool of the molecular fingerprints of the lead compounds on the drug targets. At present, molecular fingerprints which are excellent in performance and are used for the bioactivity prediction are often greater in length, and however, by adopting a designed deep learning algorithm, molecular fingerprints which are excellent in performance and smaller in length can be generated so that the best bioactivity prediction model of drug target ligands can be obtained.

The present invention relates generally to searching substructures in virtual combinatorial libraries. More precisely, it describes a method of operating a computer for searching substructures in large, non-enumerated virtual combinatorial libraries. Advantageously, the method can return matching products as non-enumerated substructures.

A forward synthetic method is described that utilizes recursive application of established organic chemical reactions to derive more complex synthons from available reagents than are available from the reagent synthons themselves. The product of each reaction serves as the starting point for further reactions thereby permitting the generation of multiple complex molecular structures. This synthon generation procedure typically yields 20 ? 30 new structures within the limits of easily accessible syntheses based upon each starting reagent. More complex syntheses yield even more structures. The generated synthons are characterized with a molecular structural descriptor possessing a neighborhood property and can be further characterized with features. The synthons are searched for three dimensional shape and feature similarity to molecular fragments derived from query molecules, typically pharmacological molecules of interest. Identified synthons can be assembled into molecules possessing the same three dimensional shape and likely activity as the molecule of interest.

A content recommendation apparatus and method gives users a peer-to-peer, highly personal way to discover new content by being introduced to one or more similar users. A similar user is a user that has a correlation to another user based on their preferences and behaviors (e.g., downloaded content, frequency of use, content currently have on device, browsing behaviors, content organizational habits, etc.). A catalog of content, or a designated portion thereof, can be used at least in part for finding matches and for identifying content to suggest to another. Data about user behavior can serve to connect the user to similar individuals for the purpose of discovering new content.

The present invention relates to malodor reduction compositions and methods of making and using same. The malodor reduction compositions are suitable for use in a variety of applications, including use in consumer products, for example, air freshening compositions, laundry detergents, fabric enhancers, surface cleaners, beauty care products, dish care products, diapers, feminine protection articles, and plastic films for garbage bags. Such malodor control technologies do not unduely interfere with the scent of the perfumed or unperfumed situs that is treated with the malodor control technology.

The invention provides a molecule attribute prediction method based on an artificial neural network. The molecule attribute prediction method based on the artificial neural network comprises the following steps: S1) preprocessing of molecule data: acquiring atomic space representation and atomic composition representation through a method for data structure representation of graphs; S2) model establishment: acquiring representation of different stages of molecules from the atomic space representation and the atomic composition representation through a multilayered convolutional neural network,and combining the representations of the different stages of the molecules to obtain a model; and S3) predicting the molecule attribute according to the model. Compared with the prior art, the molecule attribute prediction method based on the artificial neural network has the advantages that the multistage convolutional neural network is used, the relation between the molecule attribute and spacecomposition can be learnt from information of known data and the multistage structure of the molecules, and is used for predicting the related attributes of unknown molecules, and therefore, the speed and the precision are good.

Disclosed is an FCM fuel effective multigroup cross section acquiring method. The FCM fuel effective multigroup cross section acquiring method comprises, in a resonant energy section and based on a superfine group method, solving a TRISO (tristructure isotropic) particle and matrix material containing one-dimensional sphere model to obtain superfine group defect factors; through the superfine group defect factors, correcting the superfine group cross section of all nuclides to homogenize particles and matrix; through Dancoff factor equivalence, acquiring the equivalent one-dimensional rod model of every fuel rod of an FCM fuel, solving the superfine group slowing-down equation of the one-dimensional rod models to acquire the effective self-shielding cross section of the resonant energy section; in a heat energy section, through penetration probability and collision probability equivalence, acquiring multigroup defect factors, correcting the multigroup cross sections of all the nuclidesthrough the multigroup defect factors to homogenize fuel and matrix and to acquire the effective multigroup cross sections of the heat energy section. The FCM fuel effective multigroup cross sectionacquiring method can help effectively process the dual heterogenous effects of the FCM fuel to acquire a precise effective self-screening cross section.

A vectorization process is employed in which chemical identifier strings are converted into respective vectors. These vectors may then be searched to identify molecules that are identical or similar to each other. The dimensions of the vector space can be defined by sequences of symbols that make up the chemical identifier strings. The International Chemical Identifier (InChI) string defined by the International Union of Pure and Applied Chemistry (IUPAC) is particularly well suited for these methods.

A computer system comprising a database (100) having a plurality of records, is provided. Each record comprises a filed point representation representing field extrema for a conformation of a chemical structure. The database may include records for multiple conformations of the same chemical structure. Each record can have a searchable index of the filed point representation. In one embodiment the index is bit string. An indexing mechanism for generating an index, a searching mechanism for searching the database and a graphical user interface to enable a user to interface with the database (100) are also provided.

Disclosed herein is a pharmacophore model for inhibiting Botulinum neurotoxin A metalloprotease activity which comprises a first plane A, a second plane B, a first hydrophobic moiety C, a second hydrophobic moiety D and a positive ionizable substituent E. The pharmacophore model may further comprise a heteroatom in the first plane A. In some embodiments, the distance between the center of the first plane A and the center of the second plane B is about 6.5 to about 9.5 Å. In some embodiments, the distance between the center of the first hydrophobic moiety C and the center of the second hydrophobic moiety D is about 8.0 to about 16.0 Å. In some embodiments, the distance between the center of the first plane to the center of the first hydrophobic moiety C is about 3.0 to about 5.0 Å. In some embodiments, the distance between the center of the second plane to the center of the second hydrophobic moiety C is about 3.0 to about 5.0 Å. In some embodiments, the distance between the center of the first plane to the center of the positive ionizable substituent is about 6.5 to about 9.5 Å.

The present invention relates to antiperspirant and deodorant compositions comprising malodor reduction compositions and methods of making and using such antiperspirant and deodorant compositions. Such antiperspirant and deodorant compositions comprising the malodor control technologies disclosed herein provide malodor control without leaving an undesirable scent and when perfume is used to scent such compositions, such scent is not unduely altered by the malodor control technology.

The present invention relates to delivery systems comprising malodor reduction compositions, methods of making such delivery systems and consumer products made with such delivery systems. Such delivery systems do not unduely interfere with the scent of the perfumed or unperfumed delivery system, perfumed or unperfumed products comprising such delivery systems and any perfumed or unperfumed situs that is treated with such products.