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Frontiers Section Editor (Bioinformatics and Biophysics) for the Current Drug Targets ISSN: 1873-5592

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Section Editor (Bioinformatics in Drug Design and Discovery) for the Current Medicinal Chemistry ISSN: 1875-533X

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Section Editor (Combinatorial/Medicinal Chemistry) for the Combinatorial Chemistry & High Throughput Screening ISSN: 1875-5402

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Member of the Editorial Board for the PeerJ ISSN: 2167-8359

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Member of the Editorial Board for the Current Bioinformatics ISSN: 2212-392X (Online) ISSN: 1574-8936 (Print)

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Member of the Editorial Board for the Organic & Medicinal Chemistry International Journal ISSN: 2474-7610

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Section Editor in Chief (Bioinformatics) for Bioengineering International. ISSN 2668-7119

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Member of the Editorial Board for the PeerJ Physical Chemistry

 

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Protein-Ligand Interacions

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Molecular Docking

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Bioinspired Computing

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Computational Systems Biology

 

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da Silva AD et al. J Comput Chem. 2020; 41(1): 69-73.

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Volkart PA et al. Curr Drug Targets. 2019;20(7):716-726

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Russo S, De Azevedo WF. Curr Med Chem 2019. 26(10):1908-1919

Receptor-Ligand Systems Database

Here we have searchable datasets with biological systems to be used to develop targeted-scoring functions (Seifert, 2009). We used the SAnDReS program (Xavier et al., 2016) to generate the datasets and the AutoDockTools (Morris et al., 2009) to create PDBQT files. We obtained the crystallographic structures from the Protein Data Bank (PDB) (Berman et al., 2000) and binding affinity data from BindingDB (Chen et al., 2001), Binding MOAD (Benson et al., 2008), and PDBbind (Wang et al., 2004).

Quick Instructions 

To search this database, you have only to type a keyword related to the system of your research on the field "Search our systems..." indicated below. Once found the dataset, click on the ZIP icon (on the right) to download the structures and the binding affinity data. Each zipped folder has the binding/thermodynamic data and the crystallographic structures (lig.pdbqt and receptor.pdbqt) for the PDBs in the dataset. The binding affinity (e.g. Ki) or thermodynamic (e.g. DeltaG) data are available in the chklig.in file (last column) found in the unzipped folder. The second column of chklig.in file indicates the PDB access code, the following columns indicate the data related to the active ligand bound to the structure.

 

 

 

 

 

 

 

 

 

 

 

 

Biological systems

Systems ZIP
AutoDock Dataset

 

1DWB,1ETR,1ETS,1ETT,1FKF,1HVJ,1HVR,1MBI,1RBP,1TLP,

1TMN,1ULB,2CPP,2ER6,2GBP,2IFB,2MCP,2XIS,2YPI,3CPA,

3PTB,4CNA,4DFR,4HMG,4HVP,4TLN,4TMN,5HVP,5TMN,6CPA

 

In this dataset, we have 30 structures used to obtain the regression weights for the AutoDock 3 scoring function (Morris et al., 1998).

These structures might be employed as benchmark to test the predictive performance of new scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Automated docking; binding affinity; drug design; scoring function; AutoDock

References

Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ. Automated Docking Using a Lamarckian Genetic Algorithm and an Empirical Binding Free Energy Funtion. J Comput Chem. 1998; 19(14):1639-1662.

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Beta Galactosidase with Inhibition Constant (Ki) Data

 

1JYX,1JZ7,1PX4,1UWT,1UWU,2CEQ,2CER,3DYO,3I3B,3I3D,

3MUZ,3MV0,3T08,3T09,3T0B,3T0D,3T2P,3T2Q,3VD4,3VD7,

3VD9,3VDB,3VDC,3WEZ

 

In this dataset, we have 24 crystallographic structures of beta galactosidase (EC 3.2.1.23) with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for beta galactosidase. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

beta galactosidase; binding affinity; drug design; scoring function; inhibition constant

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase with Half Maximal Inhibitory Concentration (IC50) Data

 

1DI8,1DM2,1E9H,1FVT,1FVV,1GII,1H00,1H07,1H0W,1H1Q,

1H1R,1JVP,1KE5,1KE6,1KE7,1KE8,1KE9,1OGU,1OI9,1OIQ,

1OIR,1OIT,1OIU,1OIY,1P2A,1PXI,1PXL,1PYE,1R78,1UNG,

1UNH,1URW,1V1K,1VYW,1VYZ,1W0X,1WCC,1Y8Y,1Y91,1YKR,

2A0C,2B52,2B53,2B54,2BHE,2BKZ,2BPM,2BTS,2C4G,2C5N,

2C5O,2C5Y,2C68,2C69,2C6I,2C6K,2C6L,2C6M,2DS1,2DUV,

2G9X,2I40,2IW6,2IW9,2R3F,2R3G,2R3H,2R3I,2R3J,2R3K,

2R3L,2R3M,2R3N,2R3O,2R3P,2R64,2UUE,2UZB,2UZD,2UZE,

2UZL,2UZN,2UZO,2VTA,2VTH,2VTI,2VTJ,2VTL,2VTM,2VTN,

2VTO,2VTP,2VTQ,2VTR,2VTS,2VTT,2VU3,2VV9,2W05,2W06,

2W17,2W1H,2WEV,2WIH,2WXV,3BHT,3BHU,3BHV,3BLR,3DDP,

3DDQ,3DOG,3EZR,3EZV,3FZ1,3IG7,3IGG,3LE6,3LFN,3LFS,

3LQ5,3NS9,3O0G,3PJ8,3PXZ,3PY0,3QQK,3QTR,3QTS,3QTU,

3QTW,3QTX,3QTZ,3QU0,3R8U,3R8V,3R8Z,3R9D,3R9H,3R9N,

3R9O,3RAH,3RAL,3RGF,3RJC,3RK5,3RK7,3RK9,3RKB,3RMF,

3RNI,3RPR,3RPV,3RPY,3RZB,3S00,3S0O,3S1H,3S2P,3TI1,

3TIY,3TIZ,3TN8,3ULI,3UNJ,3UNK,3WBL,4AU8,4AUA,4BGH,

4CFN,4CFW,4ERW,4EZ3,4GCJ,4LYN

 

In this dataset, we have 176 crystallographic structures of cyclin-dependent kinase (CDK) (EC 2.7.11.22) with half maximal inhibitory concentration (IC50) data.

These structures can be applied to develop targeted-scoring functions for CDK. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase; CDK; cell cycle progression; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase 2 with Half Maximal Inhibitory Concentration (IC50) Data

 

1DI8,1DM2,1E9H,1FVT,1FVV,1GII,1H00,1H07,1H0W,1H1Q,

1H1R,1JVP,1KE5,1KE6,1KE7,1KE8,1KE9,1OGU,1OI9,1OIQ,

1OIR,1OIT,1OIU,1OIY,1P2A,1PXI,1PXL,1PYE,1R78,1URW,

1V1K,1VYW,1VYZ,1W0X,1WCC,1Y8Y,1Y91,1YKR,2A0C,2B52,

2B53,2B54,2BHE,2BKZ,2BPM,2BTS,2C4G,2C5N,2C5O,2C5Y,

2C68,2C69,2C6I,2C6K,2C6L,2C6M,2DS1,2DUV,2G9X,2I40,

2IW6,2IW9,2R3F,2R3G,2R3H,2R3I,2R3J,2R3K,2R3L,2R3M,

2R3N,2R3O,2R3P,2R64,2UUE,2UZB,2UZD,2UZE,2UZL,2UZN,

2UZO,2VTA,2VTH,2VTI,2VTJ,2VTL,2VTM,2VTN,2VTO,2VTP,

2VTQ,2VTR,2VTS,2VTT,2VU3,2VV9,2W05,2W06,2W17,2W1H,

2WEV,2WIH,2WXV,3BHT,3BHU,3BHV,3DDP,3DDQ,3DOG,3EZR,

3EZV,3FZ1,3IG7,3IGG,3LE6,3LFN,3LFS,3NS9,3PJ8,3PXZ,

3PY0,3QQK,3QTR,3QTS,3QTU,3QTW,3QTX,3QTZ,3QU0,3R8U,

3R8V,3R8Z,3R9D,3R9H,3R9N,3R9O,3RAH,3RAL,3RJC,3RK5,

3RK7,3RK9,3RKB,3RMF,3RNI,3RPR,3RPV,3RPY,3RZB,3S00,

3S0O,3S1H,3S2P,3TI1,3TIY,3TIZ,3ULI,3UNJ,3UNK,3WBL,

4BGH,4CFN,4CFW,4ERW,4EZ3,4GCJ,4LYN

 

In this dataset, we have 167 crystallographic structures of cyclin-dependent kinase 2 (CDK2) (EC 2.7.11.22) with half maximal inhibitory concentration (IC50) data.

These structures can be applied to develop targeted-scoring functions for CDK2. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase2; CDK2; cell cycle progression; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase (except CDK2) with Half Maximal Inhibitory Concentration (IC50) Data

 

1UNG,1UNH,3BLR,3LQ5,3O0G,3RGF,3TN8,4AU8,4AUA

 

In this dataset, we have 9 crystallographic structures of cyclin-dependent kinase (CDK) (EC 2.7.11.22) with half maximal inhibitory concentration (IC50) data.

This dataset doesn't bring CDK2 structures.

These structures can be applied to develop targeted-scoring functions for non-CDK2 structure. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase2; CDK2; cell cycle progression; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase 2 (without cyclin) with Half Maximal Inhibitory Concentration (IC50) Data

 

1DI8,1DM2,1FVT,1GII,1H00,1H07,1H0W,1JVP,1KE5,1KE6,

1KE7,1KE8,1KE9,1OIQ,1OIR,1OIT,1P2A,1PXI,1PXL,1PYE,

1R78,1URW,1V1K,1VYZ,1W0X,1WCC,1Y8Y,1Y91,1YKR,2A0C,

2B52,2B53,2B54,2BHE,2BTS,2C5Y,2C68,2C69,2C6I,2C6K,

2C6L,2C6M,2DS1,2DUV,2R3F,2R3G,2R3H,2R3I,2R3J,2R3K,

2R3L,2R3M,2R3N,2R3O,2R3P,2R64,2UZN,2UZO,2VTA,2VTH,

2VTI,2VTJ,2VTL,2VTM,2VTN,2VTO,2VTP,2VTQ,2VTR,2VTS,

2VTT,2VU3,2VV9,2W05,2W06,2W17,2W1H,3EZR,3EZV,3FZ1,

3IG7,3IGG,3LE6,3LFN,3LFS,3NS9,3PJ8,3PXZ,3PY0,3QQK,

3QTR,3QTS,3QTU,3QTW,3QTX,3QTZ,3QU0,3R8U,3R8V,3R8Z,

3R9D,3R9H,3R9N,3R9O,3RAH,3RAL,3RJC,3RK5,3RK7,3RK9,

3RKB,3RMF,3RNI,3RPR,3RPV,3RPY,3RZB,3S00,3S0O,3S1H,

3S2P,3TI1,3TIY,3TIZ,3ULI,3UNJ,3UNK,3WBL,4BGH,4ERW,

4EZ3,4GCJ,4LYN

 

In this dataset, we have 133 crystallographic structures of cyclin-dependent kinase 2 (CDK2) (without cyclin partner) (EC 2.7.11.22) with half maximal inhibitory concentration (IC50) data.

These structures can be applied to develop targeted-scoring functions for CDK2. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase2; CDK2; cell cycle progression; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase 2 (with cyclin) with Half Maximal Inhibitory Concentration (IC50) Data

 

1E9H,1FVV,1H1Q,1H1R,1OGU,1OI9,1OIU,1OIY,1VYW,2BKZ,

2BPM,2C4G,2C5N,2C5O,2G9X,2I40,2IW6,2IW9,2UUE,2UZB,

2UZD,2UZE,2UZL,2WEV,2WIH,2WXV,3BHT,3BHU,3BHV,3DDP,

3DDQ,3DOG,4CFN,4CFW

 

In this dataset, we have 34 crystallographic structures of cyclin-dependent kinase 2 (CDK2) (with cyclin partner) (EC 2.7.11.22) with half maximal inhibitory concentration (IC50) data.

These structures can be applied to develop targeted-scoring functions for CDK2 in complex with cyclin. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase2; CDK2; Cyclin; cell cycle progression; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase 2 with Inhibition Constant (Ki) Data

 

1E1V,1E1X,1H1S,1JSV,1OGU,1PXM,1PXN,1PXO,1PXP,1PYE,

1V1K,2CLX,2EXM,2FVD,2XMY,2XNB,3DDQ,3LFN,3LFS,3MY5,

4ACM,4BCK,4BCM,4BCN,4BCO,4BCP,4BCQ,4EOP,4NJ3,5D1J

 

In this dataset, we have 30 crystallographic structures of cyclin-dependent kinase 2 (CDK2) (EC 2.7.11.22) with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for CDK2. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase 2; CDK2; cell cycle progression; binding affinity; drug design; scoring function; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Cyclin-Dependent Kinase with Inhibition Constant (Ki) Data

 

1E1V,1E1X,1H1S,1JSV,1OGU,1PXM,1PXN,1PXO,1PXP,1PYE,

1V1K,2CLX,2EXM,2FVD,2XMY,2XNB,3BLR,3DDQ,3LFN,3LFS,

3MY5,4ACM,4BCK,4BCM,4BCN,4BCO,4BCP,4BCQ,4EOP,4NJ3,

5D1J

 

In this dataset, we have 31 crystallographic structures of cyclin-dependent kinase (CDK) (EC 2.7.11.22) with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for CDK. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Cyclin-dependent kinase; CDK; cell cycle progression; binding affinity; drug design; scoring function; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

DHQD with Inhibition Constant (Ki) Data

 

1GU1,1H0S,1V1J,2BT4,2C4V,2C4W,2CJF,2XB8,2XD9,2XDA,

2Y71,2Y76,2Y77,3N8K,3N8N,3N86,3N87,4B6Q,4B6R,4B6S,

4CIW,4CIY

 

In this dataset, we have 22 crystallographic structures of 3-dehydroquinate dehydratase (DHQD) (EC 4.2.1.10) with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for 3-dehydroquinate dehydratase. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

3-dehydroquinate dehydratase; DHQD; shikimate pathway; binding affinity; drug design; scoring function; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Enoyl Reductase with Inhibition Constant (Ki) Data

 

1NHG,1NHW,1NNU,1P45,1UH5,1V35,2B35,2B36,2B37,2NTJ,

2PR2,2X23,2Z6J,3AM3,3AM5,3LT0,3LT1,3LT2,3LT4,3NRC,

3ZU4,3ZU5,4CV3,4OHU,4OIM,4OXK,4OXY,4OYR

 

In this dataset, we have 28 crystallographic structures of enoyl-[acyl-carrier-protein] reductase (EC 1.3.1.9) with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for enoyl-[acyl-carrier-protein] reductase. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Enoyl-[acyl-carrier-protein] reductase; InhA; ENR, binding affinity; drug design; scoring function; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Estrogen Receptor Alpha with Half Maximal Inhibitory Concentration (IC50) Data

 

1A52,1ERE,1ERR,1G50,1GWR,1PCG,1QKT,1QKU,1X7R,1ZKY,

2AYR,2B1V,2BJ4,2FAI,2JF9,2JFA,2OCF,2POG,2Q70,2QA8,

2QE4,2QXS,2R6W,2R6Y,2YJA,3ERD,3ERT,3L03,3UUD,4PP6,

4PXM,4Q50

 

In this dataset, we have 32 crystallographic structures of estrogen receptor alpha with half maximal inhibitory concentration (IC50) data.

These structures can be applied to develop targeted-scoring functions for estrogen receptor alpha. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Estrogen receptor alpha; binding affinity; drug design; scoring function; half maximal inhibitory concentration (IC50)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

HIV1-Protease with DeltaG (ΔG) Data

 

1HXB,1K6C,1KZK,1MSM,1MSN,1SDT,1SDU,1SDV,1SGU,2AVO,

2AVS,2AVV,2BPX,2NMY,2NMZ,2NNK,2NNP,3CYX,3D1X,3D1Y,

3EKQ,3EL4,3K4V,3N3I,3NDT,3NDU,3OXC,3PWR,3S56,3TKG,

3TL9

 

In this dataset, we have 31 crystallographic structures of HIV1-protease with DeltaG (ΔG) data.

These structures can be applied to develop targeted-scoring functions for estrogen receptor alpha. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

HIV1-protease; HIV; Aids; binding affinity; drug design; scoring function; Gibbs free energy

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

HIV1-Protease with Inhibition Constant (Ki) Data

 

1A8G,1AJV,1AJX,1BWB,1D4H,1D4I,1D4J,1D4K,1D4L,1D4Y,

1EBW,1EBY,1EBZ,1EC0,1EC1,1EC2,1EC3,1G35,1HIH,1HPO,

1HVH,1HXW,1IIQ,1MTR,1ODW,1ODY,1PRO,1TCX,1VIK,1W5V,

1W5W,1W5X,1W5Y,1XL2,1XL5,1ZJ7,1ZSF,2AID,2AVM,2AVS,

2BPV,2BPY,2BQV,2CEJ,2CEM,2CEN,2HS1,2PYN,2RKG,2UPJ,

2UXZ,2UY0,2WKZ,3AID,3D1Y,3MXD,3MXE,3OXX,3QAA,3UPJ,

4CP7,4FE6,4HE9,4U8W,4UPJ,5UPJ,6UPJ,7UPJ

 

In this dataset, we have 68 crystallographic structures of HIV1-protease with inhibition constant (Ki) data.

These structures can be applied to develop targeted-scoring functions for estrogen receptor alpha. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

HIV1-protease; HIV; Aids; binding affinity; drug design; scoring function; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures with DeltaG (ΔG) Data

 

1A9T,1AJ6,1GFW,1HXD,1KZK,1SG0,1T64,1US0,1YHS,1ZND,

1ZNG,1ZNH,1ZNK,2AVS,2BIK,2BYA,2C3I,2DM5,2FZD,2G1O,

2G1R,2G1S,2I4Q,2IKH,2IKO,2IKU,2IL2,2NMZ,2O3P,2O9A,

2PDK,2PZN,2Q6B,2QX8,2UXI,2UXP,2UXU,3AKM,3CCT,3CCW,

3CCZ,3K8Q,3M4H,4LCE,4QA0,4QOG,4RXD,5A14

 

In this dataset, we have 48 high-resolution structures with DeltaG (ΔG) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; scoring function; protein-ligand interactions; Gibbs free energy

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures with Inhibition Constant (Ki) Data

 

1BXO,1BXQ,1C1R,1C1T,1C5P,1C5Q,1C5S,1C5U,1E6Q,1E6S,

1F8D,1F8E,1GHZ,1GI1,1GI4,1GI6,1GYX,1GYY,1HYO,1K3Y,

1KZK,1ME3,1ME4,1MPL,1MQI,1O2P,1O2R,1O2W,1O33,1O35,

1O3D,1O3J,1O3L,1O8B,1PZP,1R5Y,1RMZ,1SQN,1T7R,1TBF,

1TF9,1U3W,1X1Z,1XOZ,1Y59,1Y5A,1ZQ5,1ZUA,2AH4,2ARM,

2AVS,2AW1,2BVR,2BVS,2BZZ,2C01,2C6Z,2CF8,2CN0,2CTC,

2F7O,2F7P,2HB3,2HDS,2HDU,2HS1,2HW2,2HXM,2HZY,2JEW,

2JKH,2NMZ,2NNG,2NNO,2QCF,2QD7,2QNN,2QNP,2QO8,2VEZ,

2W9H,2WEJ,2X9G,2X9N,2X9V,2Y5F,2Y5G,2Y5H,2YIV,2YR6,

2Z7K,2ZFF,3A2O,3ACX,3AYI,3B3C,3B3S,3B7E,3B9G,3BLB,

3C31,3CV2,3D4Z,3DD0,3DDF,3DJK,3DK1,3DX1,3DX2,3DX3,

3DX4,3DXH,3EJP,3EJQ,3EJR,3EPW,3EX6,3F17,3F5L,3FED,

3FF3,3FS6,3FX5,3G2Y,3G32,3G34,3G35,3GBA,3GC5,3HS4,

3HVH,3HVI,3HVK,3I6O,3IOF,3IOG,3IOI,3IUT,3K5X,3KKU,

3KL6,3L14,3LJG,3M0I,3M1K,3M2Y,3M8T,3MHW,3MI2,3MOE,

3NU3,3NXO,3NXX,3NYD,3O9I,3OCZ,3OE4,3OKV,3OYQ,3OZS,

3OZT,3P17,3P3C,3P58,3P5A,3PB7,3PB8,3PB9,3PC0,3PO6,

3PRS,3QAA,3QX5,3QYK,3RM0,3RM2,3RMO,3SI4,3SLZ,3ST5,

3SU0,3SU6,3SV2,3SV6,3T42,3T74,3T8F,3TJM,3TLL,3U98,

3V7X,3VBD,3VF5,3VH9,3WJX,3ZCL,4AZ6,4BF1,4BPS,4BS0,

4BT3,4BT5,4CAE,4CQ0,4CYN,4DDS,4DDY,4DE0,4DE1,4DE2,

4DE3,4DFG,4DJP,4DJQ,4DO4,4DRI,4DXH,4DZ7,4E49,4E4A,

4EZ8,4FCF,4FH2,4G95,4GE6,4GQL,4GQR,4GR3,4GR8,4H6Q,

4HE9,4HJS,4HZM,4I71,4I8H,4IGT,4JFI,4JFJ,4JFM,4JQA,

4JXH,4KB9,4KWO,4KWP,4KZ4,4KZ5,4KZ7,4KZB,4LBT,4LBU,

4LEQ,4LM3,4LM4,4NG5,4NUA,4NUC,4NUD,4NUE,4OHA,4P5E,

4Q4S,4Q7W,4Q8T,4Q8Y,4QOG,4R3N,4RUX,4RUY,4TW6,4TW7,

4TX0,4U8W,4UA4,4YW9,4YZU,4ZIP,5BYI,8A3H

 

In this dataset, we have 278 high-resolution structures with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures (Oxidoreductases) with Inhibition Constant (Ki) Data

 

1U3W,1ZQ5,1ZUA,2W9H,2X9G,2X9N,2X9V,2YIV,2YR6,3AYI,

3FS6,3M0I,3NXO,3NXX,3T42,4DXH,4G95,4H6Q,4JQA,4NG5,

4QOG,4R3N

 

In this dataset, we have 22 high-resolution structures (Oxidoreductases)(EC 1. -. -.-) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions specific for oxydoreductases. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; oxidoreductases; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures (Transferases) with Inhibition Constant (Ki) Data

 

1K3Y,1R5Y,2HW2,2VEZ,2Z7K,3ACX,3CV2,3D4Z,3GC5,3HVH,

3HVI,3HVK,3IOI,3OE4,3OZS,3OZT,3PB7,3PB8,3PB9,3TJM,

3TLL,3ZCL,4CAE,4CYN,4EZ8,4KWO,4KWP,4LBU,4LEQ,4NUA,

4Q4S,4Q8T

 

In this dataset, we have 32 high-resolution structures (Transferases)(EC 2. -. -.-) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions specific for oxydoreductases. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; transferases; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures (Hydrolases) with Inhibition Constant (Ki) Data

 

1BXO,1BXQ,1C1R,1C1T,1C5P,1C5Q,1C5S,1C5U,1E6Q,1E6S,

1F8D,1F8E,1GHZ,1GI1,1GI4,1GI6,1HYO,1KZK,1ME3,1ME4,

1MPL,1O2P,1O2R,1O2W,1O33,1O35,1O3D,1O3J,1O3L,1PZP,

1RMZ,1TBF,1TF9,1XOZ,1Y59,1Y5A,2AH4,2ARM,2AVS,2BVR,

2BVS,2BZZ,2C01,2C6Z,2CF8,2CN0,2CTC,2F7O,2F7P,2HB3,

2HDS,2HDU,2HS1,2HXM,2HZY,2JEW,2JKH,2NMZ,2QD7,2QNN,

2QNP,2Y5F,2Y5G,2Y5H,2ZFF,3A2O,3B3C,3B3S,3B7E,3B9G,

3BLB,3DDF,3DJK,3DK1,3DX1,3DX2,3DX3,3DX4,3DXH,3EJP,

3EJQ,3EJR,3EPW,3F17,3F5L,3FED,3FF3,3FX5,3G2Y,3G32,

3G34,3G35,3I6O,3IOF,3IOG,3IUT,3K5X,3KKU,3KL6,3LJG,

3MHW,3NYD,3P17,3P3C,3PRS,3QX5,3RM0,3RM2,3RMO,3SI4,

3ST5,3SU0,3SU6,3SV2,3T74,3T8F,3U98,3VH9,4AZ6,4BPS,

4BS0,4DDS,4DDY,4DE0,4DE1,4DE2,4DE3,4DFG,4DJP,4DJQ,

4DO4,4FCF,4FH2,4GE6,4GQL,4GQR,4GR3,4GR8,4HE9,4HZM,

4I71,4I8H,4KB9,4KZ4,4KZ5,4KZ7,4KZB,4LBT,4LM3,4LM4,

4P5E,4U8W,4YZU,4ZIP,8A3H

 

In this dataset, we have 155 high-resolution structures (Hydrolases)(EC 3. -. -.-) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions specific for oxydoreductases. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; hydrolases; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures (Lyases) with Inhibition Constant (Ki) Data

 

1X1Z,2AW1,2NNG,2NNO,2QCF,2QO8,2WEJ,3DD0,3HS4,3L14,

3M1K,3M2Y,3MI2,3MOE,3NU3,3OKV,3OYQ,3P58,3P5A,3PC0,

3PO6,3QYK,3V7X,3VBD,3WJX,4BF1,4BT3,4BT5,4CQ0,4DZ7,

4E49,4E4A,4Q7W,4Q8Y,4RUX,4RUY,4YW9,5BYI

 

In this dataset, we have 38 high-resolution structures (Lyases)(EC 4. -. -.-) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions specific for oxydoreductases. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; lyases; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

High-Resolution Structures (Isomerases) with Inhibition Constant (Ki) Data

 

1GYX,1GYY,1O8B,4DRI,4JFI,4JFJ,4JFM,4TW6,4TW7,4TX0

 

In this dataset, we have 10 high-resolution structures (Isomerases)(EC 5. -. -.-) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions specific for oxydoreductases. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; isomerases; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Kinase with DeltaG (ΔG) Data

 

1A07,1A1B,1A1C,1A1E,1F1W,1FMK,1KC2,1KSW,1NZL,1NZV,

1P13,1SHA,1SHB,1SHD,1SPS,1XWS,1YHS,1YI6,2BIK,2BIL,

2C3I,2H8H,2O3P,3DQW,4LMU,5A14

 

In this dataset, we have 26 structures of kinase with DeltaG (ΔG) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Drug design; kinase; scoring function; protein-ligand interactions; Gibbs free energy

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Purine Nucleoside Phosphorylase with Inhibition Constant (Ki) Data

 

1A69,1B8N,1B8O,1C3X,1G2O,1K9S,1PF7,1PR1,1PR5,1PWY,

1RT9,1V41,1V48,1VFN,2A0W,2A0X,2A0Y,2I4T,2OC4,2OC9,

2ON6,2P4S,2Q7O,3BGS,3FUC,3K8O,3K8Q,3PHB,4EAR,4EB8,

5ETJ

 

In this dataset, we have 31 structures of purine nucleoside phosphorylase (EC: 2.4.2.1) with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Purine nucleoside phosphorylase; PNP; drug design; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Shikimate Pathway Enzymes with Inhibition Constant (Ki) Data

 

4UMA,4UMC,4BQS,1V1J,2C4V,2XB8,2XB9,3N76,3N7A,3N86,

3N87,3N8K,3N8N,4B6O,4B6P,4B6S,4CIW,4CIY,4UMB,1GU1,

1H0R,2BT4,2C4W,4B6R

 

In this dataset, we have 24 structures of shikimate pathway enzymes with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

Shikimate pathway; drug design; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

U-Plasminogen Activator with Inhibition Constant (Ki) Data

 

1C5X,1C5Y,1EJN,1F5K,1F5L,1F92,1GI7,1GI8,1GI9,1GJ7,

1GJ8,1GJ9,1GJA,1GJC,1GJD,1O3P,1O5A,1O5C,1OWD,1OWH,

1OWK,1SC8,1SQA,1SQO,1SQT,1VJ9,1VJA,1W0Z,1W10,1W11,

1W12,1W13,1W14,2O8W,2R2W,2VNT,3KGP,3KHV,3KID,3MHW,

4FU7,4FU8,4FU9,4FUD,4FUE,4FUF,4FUG,4FUH,4FUJ,4H42

 

In this dataset, we have 50 structures of U-plasminogen activator with inhibition constant (Ki) data.

These structures can be applied to develop novel scoring functions. We generated PDBQT files using AutoDockTool4 (Morris et al., 2009).

Keywords

U-plasminogen activator; drug design; scoring function; protein-ligand interactions; inhibition constant (Ki)

Reference

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30(16):2785-2791.

Datasets

 The major application of the data available here is the development of targeted-scoring functions making use of machine-learning techniques such as the ones available in the programs SAnDReS (Xavier et al., 2016) and Taba (da Silva et al., 2020). We expect to use this structural and binding information to explore the scoring function space (Heck et al., 2017; Bitencourt-Ferreira & de Azevedo, 2019) and design scoring functions targeted to each of the datasets available here.  

Cover imageWe used these datasets to evaluate the predictive performance of the Taba program (da Silva et al., 2020). Taba is an acronym for Tool to Analyze the Binding Affinity. This program uses a physical mass-spring model to generate machine-learning models to predict binding affinity based on the atomic coordinates of protein-ligand complexes. We applied it to a dataset of the cyclin-dependent kinase (EC 2.7.11.22) with inhibition constant (Ki) data. This dataset is available below (Cyclin-Dependent Kinase with Inhibition Constant (Ki) Data).

References

Benson ML, Smith RD, Khazanov NA, Dimcheff B, Beaver J, Dresslar P, Nerothin J, Carlson HA. Binding MOAD, a high-quality protein-ligand database. Nucleic Acids Res. 2008; 36(Database issue): D674–D678.   PubMed   

Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res., 2000; 28(1): 235–242.   PubMed   

Bitencourt-Ferreira G, de Azevedo WF Jr. Exploring the Scoring Function Space. Methods Mol Biol. 2019; 2053: 275–281.   PubMed   

Chen X, Liu M, Gilson MK. BindingDB: a web-accessible molecular recognition database. Comb Chem High Throughput Screen. 2001; 4(8): 719–725.   PubMed   

da Silva AD, Bitencourt-Ferreira G, de Azevedo WF Jr. Taba: A Tool to Analyze the Binding Affinity. J Comput Chem. 2020; 41(1): 69–73.   PubMed   


Heck GS, Pintro VO, Pereira RR, de Ávila MB, Levin NMB, de Azevedo WF. Supervised Machine Learning Methods Applied to Predict Ligand-Binding Affinity. Curr Med Chem. 2017; 24(23): 2459–2470.   PubMed   

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.  2009; J Comput Chem 30: 2785–2791.   PubMed   

Seifert MH. Targeted scoring functions for virtual screening. Drug Discov Today. 2009;14(11-12):562–569.   PubMed   

Wang R, Fang X, Lu Y, Wang S. The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. J Med Chem. 2004; 47(12): 2977–2980.   PubMed   

Xavier MM, Heck GS, de Avila MB, Levin NM, Pintro VO, Carvalho NL, Azevedo WF Jr. SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions. Comb. Chem. High Throughput Screen. 2016; 19(10): 80112.   PubMed    PDF    GitHub