A combinatorial chemistry molecular database CCSMD for screening small molecules with anticancer activity and its application

Abstract

The present invention belongs to the field of medicine, and specifically relates to a method for building a library through intelligent combination, and using this library to discover small molecules with anti-cancer activity. The present invention establishes a virtual database of 12,904 molecules. The virtual molecules in this database are assembled using Python from existing and commercially available molecular building blocks. The conditions for intelligent combination are mature and simple reaction conditions. Therefore, the small molecules in this database are easy to synthesize and have greater practical significance. Using this database for virtual screening and synthesizing the screened molecules can obtain small molecules with high anti-cancer activity. These molecules are essentially non-toxic to normal gastric mucosal cells and have significant therapeutic effects on gastric cancer, and their therapeutic effects are better than cisplatin, thus having good application prospects.

Description

Technical Field

[0001] The present invention belongs to the field of medicine, and in particular relates to a combinatorial chemical molecular database CCSMD for screening small molecules with anti-cancer activity and its application. Background Art

[0002] At present, most of the new drugs approved for marketing each year are various small molecule inhibitor compounds. Small molecule anticancer drugs occupy an important position among them. The use of small molecule databases and computer-aided medicine (CADD) is a powerful and promising technology that can be used for faster, cheaper and more effective drug design. Using public databases and CADD to screen active compounds has become a common method. However, compounds screened in public molecular databases often face the result that they are difficult to synthesize or cannot be purchased. In addition, there are a large number of small molecule fragments (such as monocyclic aromatic hydrocarbons, polycyclic aromatic hydrocarbons, short-chain aliphatic hydrocarbons, etc.) in public databases, which are usually difficult to use. Therefore, it is necessary to find a better way to utilize the relevant resources in public databases to solve the above problems.

[0003] Combinatorial chemistry offers a method for better utilizing public databases and addressing these challenges. Screening databases can be established in two ways: actual combinatorial chemistry databases and virtual combinatorial chemistry databases. However, each approach has its own advantages and disadvantages. Actual combinatorial chemistry databases are screened using chemical reaction tanks to generate a large number of compounds, which are then screened using true screening methods such as high-throughput screening (HTS). This approach is expensive, slower, and non-targeted. Virtual combinatorial chemistry databases, on the other hand, are often constructed around existing framework molecules. Once a virtual molecule library is established, virtual screening methods are used to predict how compounds interact with a given target protein. However, this method can only be used with fixed frameworks and is not widely applicable. Therefore, it is necessary to establish a virtual small molecule database that can utilize existing small molecule fragments, is easy to synthesize, has a wide range of applications, and can be used by the public to discover new active small molecules through CADD.

[0004] This invention utilizes Python to combine existing and commercially available molecular building blocks, thereby establishing a large database of combinatorial molecules. Furthermore, because the conditions for intelligent combination are mature and simple reaction conditions, the small molecules in this database are easy to synthesize, making them more practical. This allows the discovery of various active small molecules with anti-cancer properties. Summary of the Invention

[0005] In response to the above technical problems, the present invention aims to provide a combinatorial chemistry database (CCSMD) for screening small molecules with anticancer activity and its application, which specifically includes the following contents:

[0006] In a first aspect, the present invention provides a combinatorial chemical molecular database CCSMD for screening small molecules with anti-cancer activity, wherein the method for constructing the combinatorial chemical molecular database CCSMD is as follows:

[0007] (1) Collect acid and amine compounds mainly composed of amine or acetic acid, and convert the collected molecules from structural formula to SMILE format;

[0008] (2) Using the intelligent reaction module, chemically splice the acid and amine compounds in the SMILE format, output the SMILE format of the synthesized molecules, convert them into molecular structure formulas, and store them in SDF format to preliminarily build a small molecule database;

[0009] (3) Use the ligand molecule energy minimization module to minimize the energy of all small molecules in the small molecule database, and delete molecules with minimized energy higher than 10,000; calculate the properties of the remaining combined small molecules separately; summarize all the data to form the combinatorial chemical molecule database CCSMD; the properties include molecular weight, number of rotatable bonds, hydrogen bond acceptors, hydrogen bond donors, topological polar surface area and octanol / water partition coefficient.

[0010] Preferably, the software used for converting the molecular structure formula into the Smile format in steps (1) and (2) is Openbabel.

[0011] Preferably, the intelligent reaction module in step (2) is derived from the intelligent reaction module in the RDKIT program in PYTHON; and the properties of the combined small molecules are calculated using the RDKIT program in PYTHON in step (3).

[0012] Preferably, the ligand molecule energy minimization module in step (3) is the ligand molecule energy minimization module of Autodock.

[0013] In a second aspect, the present invention provides the combinatorial chemical molecular database CCSMD described in the first aspect or its use in screening small molecules with anti-cancer activity.

[0014] In a third aspect, the present invention provides a retrieval system for screening small molecules with anti-cancer activity, wherein the system comprises:

[0015] Constructing the combinatorial chemical molecular database CCSMD described in the first aspect above, wherein the combinatorial chemical molecular database CCSMD is used to store attribute data of compounds, wherein the compound attributes include molecular weight, number of rotatable bonds, hydrogen bond acceptors, hydrogen bond donors, topological polar surface area, and octanol / water partition coefficient;

[0016] Generate a search model based on the input compound attributes;

[0017] Based on the retrieval model, the compounds to be searched entered by the user are searched in the combinatorial chemical molecule database CCSMD. If a compound with the properties consistent with the compound entered by the user is retrieved, the retrieved compound combination molecule result is fed back to the user; if a compound with the properties consistent with the compound entered by the user is not retrieved, the conclusion that no matching compound was retrieved is fed back to the user.

[0018] In a fourth aspect, the present invention provides the use of the retrieval system described in the third aspect in screening small molecules with anti-cancer activity.

[0019] In a fifth aspect, the present invention provides a method for screening small molecules with anti-cancer activity, the method comprising the following steps:

[0020] (1) constructing the combinatorial chemical molecule database CCSMD described in the first aspect or the retrieval system described in the third aspect;

[0021] (2) Selecting any one or more of the following: molecular weight, number of rotatable bonds, hydrogen bond acceptors, hydrogen bond donors, topological polar surface area, and octanol / water partition coefficient as search objects and generating a search model; obtaining target compounds through searching the combinatorial chemical molecular database CCSMD;

[0022] (3) The searched target compounds were docked with the human cyclophosphokinase-dependent kinase 6 protein structure using molecular docking software to screen and obtain a high-scoring combination of molecules;

[0023] (4) synthesizing corresponding small molecule compounds based on the obtained high-scoring combinatorial molecule set;

[0024] (5) Through in vitro MTT activity evaluation, small molecules with anticancer activity were screened and obtained.

[0025] Preferably, the molecular docking software in step (3) is selected from the open source molecular docking software Autodock vina.

[0026] In a sixth aspect, the present invention provides the use of a compound obtained by screening according to the method described in the fifth aspect in the preparation of an anti-tumor drug.

[0027] In a seventh aspect, the present invention provides a compound having anti-tumor activity obtained by screening according to the method described in the fifth aspect, wherein the structural formula of the compound is shown in the following formulas (I)-(II):

[0028]

[0029] In an eighth aspect, the present invention provides use of the compound described in the seventh aspect or a pharmaceutically acceptable salt thereof in the preparation of an anti-tumor drug.

[0030] Preferably, the tumor is gastric cancer.

[0031] In a ninth aspect, the present invention provides a compound or a pharmaceutically acceptable salt thereof as described in the seventh aspect, which is added to a pharmaceutically acceptable carrier and / or excipient to prepare any dosage form of tablets, sprays, granules, capsules, oral solutions, injections, and suspensions.

[0032] In a tenth aspect, the present invention provides a method for preparing the compound described in the seventh aspect, which comprises: heating the raw acid in thionyl chloride to 75° C. and stirring for 2 hours; then concentrating and evaporating the thionyl chloride to dryness to obtain a white solid acyl chloride intermediate, adding the acyl chloride to THF in an ice bath and stirring for 5 minutes, then adding the raw amine, stirring for 3 hours, and concentrating the system under reduced pressure. The residue is purified by silica gel column chromatography to obtain the intermediate.

[0033] The beneficial effects of the present invention are as follows: the present invention first utilizes the method of intelligent virtual combinatorial chemistry to construct a huge combinatorial chemical molecular database CCSMD; the database uses commercially available, cheap and easily available molecular building blocks as a basis, and adopts simple chemical reactions as conditions for synthesis and splicing, which not only has a large order of magnitude, but also can be easily self-synthesized, and thus has the characteristics of high cost performance; the molecular structure obtained by virtual screening using the database of the present invention can be obtained at a low price and easily; and the database of the present invention can be used to screen and obtain compounds with low μM activity against cancer, the compounds have good safety, are basically non-toxic to normal gastric mucosal cells, and have significant effects in treating gastric cancer; at the same time, the compounds are easy to synthesize, are more practical, and therefore have good application prospects

[0034] Figures in the specification

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 Database construction and compound screening flow chart;

[0037] Figure 2 Web page information related to the database CCSMD; A is the search page in CCSMD, where you can use the icon search bar to limit the range of ClogP and molecular weight to filter out molecules; B shows the relevant computational chemical properties of the searched molecules; C shows the ratio of each chemical property at different orders of magnitude;

[0038] Figure 3 The specific process from establishing a database to using the database, where A is the main process of establishing the database; B is the step of virtual screening;

[0039] Figure 4 Results of virtual screening of selected proteins using CCSMD; A shows CDK6 (PDB: 5L2I) as the target protein, with a box (Center x = 12.46, Center y = 29.63, Center z = 13.28, Size x = 17.34, Size y = 14.67, Size z = 25.11) selected as the positioning box; B shows the docking results of CCSMD using a heat map, with the score of deleted unsuitable molecules defined as 0 and the score of synthesized composite molecules defined as 14, allowing for intuitive observation of the positions of the synthesized molecules. The remaining molecules are output as score results (the chart is limited to -14 to 14); C shows all compounds as score results to increase the contrast of all scoring results, with the score of undocked compounds being 0 (the chart is limited to -14 to -7);

[0040] Figure 5 The docking results of compounds (I) and (II) binding to the target protein; A is the hydrophobic surface of CDK6, red is hydrophobic, blue is hydrophilic; B and C are the docking results of the screened compounds (I) and (II) CDK6, showing that the ligand molecule All amino acid residues of proteins in the range are marked in yellow; the dark blue line in D is the force between the amino acid residues of CDK6 and the screened compound (I);

[0041] Figure 6 Cell viability of compounds (I) and (II); where A is the 48-hour inhibitory activity of compound (I) against AGS. B is the 48-hour inhibitory activity of compound (I) against GES-1. C is the 48-hour inhibitory activity of compound (II) against AGS. D is the 48-hour inhibitory activity of compound (II) against GES-1. E is the 48-hour inhibitory activity of cisplatin against AGS. F is the 48-hour inhibitory activity of cisplatin against GES-1. G is a comparison of the viability of the three compounds against AGS. H is a comparison of the viability of the three compounds against GES-1. DETAILED DESCRIPTION

[0042] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be described clearly and completely below. Where specific conditions are not specified in the embodiments, the experiments were carried out under conventional conditions or conditions recommended by the manufacturer. Reagents or instruments used, for which the manufacturer is not specified, are all commercially available conventional products.

[0043] Example 1 Construction and Screening of the Combinatorial Chemical Molecular Database CCSMD

[0044] The flow chart of database construction and compound screening is as follows Figure 1 The database search process is as shown in Figure 2 As shown;

[0045] Collect thousands of unique small molecule building blocks and commercial molecular building blocks. Contains CAS numbers, chemical formulas, molecular structures, and other information for various commercial building block molecules and clinical drug fragments.

[0046] The integrated data is accessed via a web interface that indirectly generates MySQL queries. This interface supports query functions such as "molecular weight range" and "ClogP range." Basic statistics and visualizations are also available for customized analysis. Interested authors are provided with links to articles for verification or further research.

[0047] The CCSMD system includes all molecules in SMILE format and their respective physicochemical properties. The database is constructed by the intelligent module of RDKIRT, which combines two different molecular building blocks into a new small molecule through a simple chemical reaction. This chemical reaction can be completed by simple conditions. All the collected small molecule building blocks were combined to preliminarily construct a small molecule database with a total of 12,992. However, there are many unreasonable molecular structures in this database, so the ligand molecule energy minimization module of Autodock was used to minimize the energy of all small molecules. All molecules with minimized energy higher than 10,000 were deleted, and the total number of remaining molecules was 12,908. Available Molecules accounted for 99.35% of all molecules. The remaining combined small molecules used the RDKIT program to calculate the following properties: molecular weight (MW), number of rotatable bonds (RB), hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), topological polar surface area (TPSA), and octanol / water partition coefficient (ClogP). All the above processes can be done in Figure 2 Indicated by A in the middle.

[0048] The crystal structure of human Cyclin-dependent kinase 6 (CDK6) and Palbociclib (PDB: 5L2I) was used as the target protein structure, and a box that completely enclosed the ligand was selected as the docking site (e.g. Figure 4 The ligand database was used, as shown in Figure 2. The widely recognized open-source molecular docking software Autodock vina was used for docking. The docking results were visualized and examined using the Chimera 1.14 visualization tool for the top 100 molecules. Compounds with potential to bind to the protein pocket were proposed and prepared for synthesis.

[0049] Example 2 Synthesis of the compounds obtained by screening and activity verification experiments

[0050] The structural formulas of the compounds screened from the database are shown in the following formulas (I)-(II):

[0051]

[0052]

[0053] 1. Synthesis of compounds (I) and (II)

[0054] Compound (I): (9H-fluoren-9-yl)methyl (S)-(1-((4-chloro-2,5-dimethylphenyl)amino)-1-oxo-4-yn-2-yl)carbamate.

[0055] Synthesis method: The starting material (S)-2-((((9H-fluoren-9-yl)methoxy)carbonyl)amino)pent-4-ynoic acid (50.0 mg, 0.149 mmol) was added to 5 mL of thionyl chloride and stirred at 75°C for 2 hours. The reaction mixture was then concentrated under reduced pressure until a white solid was produced, yielding the intermediate (9H-fluoren-9-yl)methyl (S)-(1-chloro-1-oxo-4-yn-2-yl)carbamate. This intermediate was then added to THF. The starting materials 4-chloro-2,5-dimethylaniline (23.1 mg, 0.148 mmol) and DIPEA (77.0 mg, 0.596 mmol) were then added to THF and stirred in an ice bath for 3 hours. The reaction mixture was then concentrated under reduced pressure, and the residue was purified by silica gel column chromatography. The product was then purified with petroleum ether / ethyl acetate (4:1) to afford Compound (I) (46.5 mg, 66% yield) as a white solid. Compound (Ⅰ); yield, 66%; white solid; 1 H NMR (400MHz, DMSO-d6) δ9.47 (s, 1H), 7.85 (d, J = 7.5Hz, 2H), 7.76 (d, J = 8.0Hz, 1 H),7.70(d,J=7.4Hz,2H),7.37(t,J=7.4Hz,2H),7.31(s,1H),7.30–7.24(m,2H ),7.23(s,1H),4.36(q,J=7.4Hz,1H),4.28(t,J=7.1Hz,2H),4.20(t,J=6.9Hz, 1H), 2.90 (s, 1H), 2.58 (qd, J = 17.6, 16.4, 7.0Hz, 2H), 2.22 (s, 3H), 2.10 (s, 3H).

[0056] Compound (II): (9H-fluoren-9-yl)methyl (S)-(1-((6-bromonaphthalen-2-yl)amino)-1-oxo-4-yn-2-yl)carbamate.

[0057] Synthesis method: The starting material (S)-2-((((9H-fluoren-9-yl)methoxy)carbonyl)amino)pent-4-ynoic acid (50.0 mg, 0.149 mmol) was added to 5 mL of thionyl chloride and stirred at 75°C for 2 hours. The mixture was then concentrated under reduced pressure until a white solid was produced, yielding the intermediate (9H-fluoren-9-yl)methyl (S)-(1-chloro-1-oxo-4-yn-2-yl)carbamate. This intermediate was then added to THF. The starting materials 6-bromonaphthalene-2-amine (32.8 mg, 0.148 mmol) and DIPEA (77.0 mg, 0.596 mmol) were then added to THF and stirred in an ice bath for 3 hours. The mixture was then concentrated under reduced pressure, and the residue was purified by column chromatography on silica gel. The product was then purified with petroleum ether / ethyl acetate (3:1) to afford Compound (II) (58.7 mg, 73% yield) as a white solid. Compound (II); yield, 73%; white solid; 1 H NMR(400MHz,DMSO-d6)δ10.40(s,1H),8.30(s,1H),8.08(s,1H),7.91–7.73(m,5H), 7.70(d,J=7.4Hz,2H),7.62(dd,J=8.9,2.1Hz,1H),7.54(dd,J=8.8,2.1Hz,1H),7.3 7(t,J=6.4Hz,2H),7.28(td,J=7.5,3.6Hz,2H),4.36(q,J=8.0Hz,1H),4.33–4.16(m ,3H),2.89(t,J=2.6Hz,1H),2.70–2.60(m,1H),2.55(ddd,J=16.7,8.4,2.6Hz,1H).

[0058] 2. Docking results of compounds (I) and (II) binding to target proteins

[0059] Methods: Use Chimera 1.14 to open the CDK6 protein structure file (PDB: 5L2I), remove the protein ligand in the file, open the previously docked docking result file on this basis, find the target molecule in the target protein docking site, show the hydrogen bond between the molecule and the target protein, and observe the binding relationship between the molecule and the protein. All protein molecules within are revealed for observation.

[0060] Results: The docking results of compound (I) binding to the target protein are as follows Figure 5As shown in C and D, it can be seen that hydrogen bonding and hydrophobic interactions are the most critical for the binding of (I). The hydroxyl group on the skeleton of the 37Tyr 24 residue can form hydrogen bonds with the oxygen atom and hydrogen atom of (I) respectively. The peptide bonds of Gln 149 and Asn 150 form hydrogen bonds with the hydrogen atoms of (I). The tricyclic structure of (I) is masked by some hydrophobic residues, such as Phe 98, Val 77, Val 101Leu 152, Ala 162, Val 27 and Ile 17, forming a hydrophobic pocket, which makes (I) and CDK6 form a strong hydrophobic interaction, further stabilizing the binding of (I). The docking results of compound (II) binding to the target protein are shown in Figure 2. Figure 5 Figure B. Similar to (I), (II) also has an Fmoc group on one side. The Fmoc group in the tricyclic structure is a hydrophobic group, so it can bind well to the hydrophobic pocket of CDK6. The other binding sites are similar to (I).

[0061] 3. Antitumor activity testing of compounds (I) and (II)

[0062] Methods: The MTT assay (Sigma) was used to measure viable cells via mitochondrial dehydrogenase activity. Cells were plated in 96-well plates at 10,000 cells / 100 μL / well. After 24 hours, cells were treated with the compounds in fresh culture medium at the following concentrations. After 48 hours, 10 μL of MTT solution (5 mg / mL) was added to each well. The culture medium was removed, and 100 μL of DMSO was added as a lysis buffer. After shaking the wells, the absorbance was measured at 490 nm.

[0063] Results: The anti-tumor activity of compounds (I) and (II) and cisplatin were tested as follows Figure 6 The results show that the inhibition rate of compounds (I) and (II) against AGS increases with increasing concentration, while there is no obvious gradient inhibitory effect on GES-1. The compounds (I) and (II) described in the present invention can significantly inhibit the proliferation of gastric cancer cells, with an effect superior to cisplatin, and have little effect on normal cells.

Claims

1. A compound having anti-tumor activity, wherein the structural formula of the compound is shown in the following formula (I) or formula (II):

Images