Benchmark data sets for structure-based computational target prediction

Journal of Chemical Information and Modeling

Volumn 54, Issue 8, 2014, Pages 2261-2274

  Schomburg, Karen T ^a   Rarey, Matthias ^a  

^a UNIVERSITY OF HAMBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; LIGANDS; PROTEINS;

BIOACTIVE COMPOUNDS; EVALUATION STRATEGIES; PERFORMANCE METRICS; PROTEIN STRUCTURES; PROTEIN-LIGAND DOCKING; SCREENING EXPERIMENTS; STATISTICAL EVALUATION; TARGET IDENTIFICATION;

INVERSE PROBLEMS;

ENZYME INHIBITOR; HISTONE DEACETYLASE; LIGAND; MOLECULAR LIBRARY; PHOSPHODIESTERASE; PROTEIN BINDING; SERINE PROTEINASE;

ALGORITHM; BINDING SITE; CHEMISTRY; HUMAN; INFORMATION PROCESSING; MOLECULAR DOCKING; MOLECULAR LIBRARY; PROTEIN CONFORMATION; QUALITY CONTROL; STRUCTURE ACTIVITY RELATION; THERMODYNAMICS; X RAY CRYSTALLOGRAPHY;

ALGORITHMS; BENCHMARKING; BINDING SITES; CRYSTALLOGRAPHY, X-RAY; DATASETS AS TOPIC; ENZYME INHIBITORS; HISTONE DEACETYLASES; HUMANS; LIGANDS; MOLECULAR DOCKING SIMULATION; PHOSPHORIC DIESTER HYDROLASES; PROTEIN BINDING; PROTEIN CONFORMATION; SERINE PROTEASES; SMALL MOLECULE LIBRARIES; STRUCTURE-ACTIVITY RELATIONSHIP; THERMODYNAMICS;

EID: 84906568966     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci500131x     Document Type: Article

References (50)

1. Jenkins, J. L.; Bender, A.; Davied, J. W. In silico target fishing: Predicting biological targets from chemical structure Drug Discovery Today 2006, 3 (4) 413-421
2. Ekins, S.; Mesters, J.; Testa, B. In silico pharmacology for drug discovery applications to targets and beyond Br. J. Pharmacol. 2007, 152, 21-37
3. Rognan, D. Chemogenomic approaches to rational drug design Br. J. Pharmacol. 2007, 152, 38-52
4. Hopkins, A. L. Network pharmacology: The next paradigm in drug discovery Nat. Chem. Biol. 2008, 4 (11) 682-690
5. Rognan, D. Structure-based approaches to target fishing and ligand profiling Mol. Inf. 2010, 29, 176-187
6. Tanrikulu, Y.; Krüger, B.; Proschak, E. The holistic integration of virtual screening in drug discovery Drug Discovery Today 2013, 18, 358-364
7. Rognan, D. Structure-based approaches to target fishing and ligand profiling Mol. Inf. 2010, 29, 176-187
8. Scior, T.; Bender, A.; Tresadern, G.; Medina-Franco, J. L.; Martinez-Mayorga, K.; Langer, T.; Cuanalo-Contreras, K.; Agrafiotis, D. K. Recognizing pitfalls in virtual screening: A critical review J. Chem. Inf. Model. 2012, 52, 867-881
9. Jain, A. N.; Nicholls, A. Recommendations for evaluation of computational methods J. Comput.-Aided Mol. Des. 2008, 22, 133-139
10. Truchon, J.-F.; Bayly, C. I. Evaluating virtual screening methods: Good and bad metrics for the early recognition" problem J. Chem. Inf. Model. 2007, 47, 488-508
11. Kirchmair, J.; Markt, P.; Distinto, S.; Wolber, G.; Langer, T. Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection-What can we learn from earlier mistakes? J. Comput.-Aided Mol. Des. 2008, 22, 213-228
12. Chen, Y. Z.; Ung, C. Y. Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach J. Mol. Graph. Model. 2001, 20 (3) 199-218
13. Chen, Y. Z.; Zhi, D. G. Ligand-protein inverse docking and its potential use in the computer search of protein targets of a small molecule Proteins 2001, 43 (2) 217-226
14. Li, H.; Gao, Z.; Kang, L.; Zhang, H.; Yang, K.; Yu, K.; Luo, X.; Zhu, W.; Chen, K.; Shen, J.; Wang, X.; Jiang, H. TarFisDock: A Web server for identifying drug targets with docking approach Nucleic Acids Res. 2006, 34, W219-W224
15. Hartshorn, M. J.; Verdonk, M. L.; Chessari, G.; Brewerton, S. C.; Mooij, W.; Mortenson, P. N.; Murray, C. W. Diverse, high-quality test set for the validation of protein-ligand docking performance J. Med. Chem. 2007, 50 (4) 726-741
16. Huang, N.; Shoichet, B. K.; Irwin, J. J. Benchmarking sets for molecular docking J. Med. Chem. 2006, 49 (23) 6789-6801
17. Koutsoukas, A.; Lowe, R.; KalantarMotamedi, Y.; Mussa, H. Y.; Klaffke, W.; Mitchell, J. B. O.; Glen, R. C.; Bender, A. In silico target predictions: Defining a benchmarking dataset and comparison of performance of the multiclass naïve bayes and Parzen-Rosenblatt window J. Chem. Inf. Model. 2013, 53 (8) 1957-1966
18. Paul, N.; Kellenberger, E.; Bret, G.; Müller, P.; Rognan, D. Recovering the true targets of specific ligands by virtual screening of the protein data bank Proteins. 2004, 54 (4) 671-680
19. Kellenberger, E.; Foata, N.; Rognan, D. Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems J. Chem. Inf. Model. 2008, 48 (5) 1014-1025
20. Meslamani, J.; Li, J.; Sutter, J.; Stevens, A.; Bertrand, H.-O.; Rognan, D. Protein-ligand-based pharmacophores: Generation and utility assessment in computational ligand profiling J. Chem. Inf. Model. 2012, 52 (4) 943-955
21. Meslamani, J.; Rognan, D.; Kellenberger, E. sc-PDB: A database for identifying variations and multiplicity of 'druggable' binding sites in proteins Bioinformatics. 2011, 27 (9) 1324-1326
22. Schomburg, K. T.; Bietz, S.; Briem, H.; Henzler, A.; Urbaczek, S.; Rarey, M. Facing the challenges of structure-based target prediction by inverse virtual screening J. Chem. Inf. Model. 2014, 54, 1676-1686
23. Czodrowski, P.; Sotriffer, P. A.; Klebe, G. Protonation changes upon ligand binding to trypsin and thrombin: Structural interpretation based on pka calculations and itc experiments J. Mol. Biol. 2007, 367 (5) 1347-1356
24. Di Fenza, A.; Heine, A.; Koert, U.; Klebe, G. Understanding binding selectivity toward trypsin and factor Xa: The role of aromatic interactions ChemMedChem. 2007, 2 (3) 297-308
25. Nar, H.; Bauer, M.; Schmid, A.; Stassen, J.-M.; Wienen, W.; Priepke, H. V. M; Kaufmann, I. K.; Ries, U. J.; Hauel, N. H. Structural basis for inhibition promiscuity of dual specific thrombin and factor Xa blood coagulation inhibitors Structure 2001, 9 (1) 29-37
26. Glinca, S.; Klebe, G. Cavities tell more than sequences: Exploring functional relationships of proteases via binding pockets J. Chem. Inf. Model. 2013, 53 (8) 2082-2092
27. Spina, D. PDE4 inhibitors: Current status Br. J. Pharmacol. 2008, 155 (3) 308-315
28. Wright, P. J. Comparison of phosphodiesterase type 5 (PDE5) inhibitors Int. J. Clin. Pract. 2006, 60 (8) 967-975
29. Dokmanovic, M.; Clarke, C.; Marks, P. A. Histone deacetylase inhibitors: Overview and perspectives Mol. Cancer Res. 2007, 5 (10) 981-989
30. Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, B. E. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235-242
31. Wishart, D. S.; Knox, C.; Guo, A. C.; Shrivastava, S.; Hassanali, M.; Stothard, P.; Chang, Z.; Woolsey, J. Drugbank: A comprehensive resource for in silico drug discovery and exploration Nucleic Acids Res. 2006, 34, D668-D672
32. Schomburg, I.; Chang, A.; Placzek, S.; Söhngen, C.; Rother, M.; Lang, M.; Munaretto, C.; Ulas, S.; Stelzer, M.; Grote, A.; Scheer, M.; Schomburg, D. BRENDA in 2013: Integrated reactions, kinetic data, enzyme function data, improved disease classification: New options and contents in BRENDA Nucleic Acids Res. 2013, 41, D764-D772
33. Bolton, E. E.; Wang, Y.; Thiessen, P. A.; Bryant, S. H. Pubchem: Integrated platform of small molecules and biological activities Annu. Rep. Comput. Chem. 2008, 4, 217-241
34. ftp://cheminfo.u-strasbg.fr (accessed January 2013).
35. Hilbig, H.; Urbaczek, S.; Groth, I.; Heuser, S.; Rarey, M. MONA-Interactive manipulation of molecule collections J. Cheminform. 2013, 5, 38
36. Urbaczek, S.; Kolodzik, A.; Groth, I.; Heuser, S.; Rarey, M. Reading PDB: Perception of molecules from 3D atomic coordinates J. Chem. Inf. Model. 2012, 53 (1) 76-87
37. Rogers, D.; Hahn, M. Extended-connectivity fingerprints J. Chem. Inf. Model. 2010, 50 (5) 742-754
38. Velankar, S.; Dana, J. M.; Jacobsen, J.; Van Ginkel, G.; Gane, P. J.; Luo, J.; Oldfield, T. J.; O'Donovan, C.; Martin, M.-J.; Kleywegt, G.-J. Sifts: Structure integration with function, taxonomy and sequences resource Nucleic Acids Res. 2013, 41, D483-D489
39. Venkatraman, V.; Pérez-Nueno, V.; Mavridis, L.; Ritchie, D. W. Comprehensive comparison of ligand-based virtual screening tools against the DUD dataset reveals limitations of current 3D methods J. Chem. Inf. Model. 2010, 50, 2079-2093
40. Riniker, S.; Landrum, G. A. Open-source platform to benchmark fingerprints for ligand-based virtual screening J. Cheminform. 2013, 5, 26
41. Schlosser, J.; Rarey, M. Beyond the virtual screening paradigm: Structure-based searching for new lead compounds J. Chem. Inf. Model. 2009, 49, 800-809
42. Schärfer, C.; Schulz-Gasch, T.; Hert, J.; Heinzerling, L.; Schulz, B.; Inhester, T.; Stahl, M.; Rarey, M. CONFECT: Conformations from an expert collection of torsion patterns ChemMedChem. 2013, 8 (10) 1690-1700
43. Altschul, S. F.; Madden, T. L.; Schäffer, A. A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D. J. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs Nucleic Acids Res. 1997, 25, 3389-3402
44. Osborne, M. J.; Schnell, J.; Benkovic, S. J.; Dyson, H. J.; Wright, P. E. Backbone dynamics in dihydrofolate reductase complexes: Role of loop flexibility in the catalytic mechanism Biochemistry. 2001, 40 (33) 9846-9859
45. Hagley, R. D.; Watlington, C. O. Down-regulation of the mineralocorticoid receptor by dexamethasone in an amphibian kidney cell line (A6) Endocr. Res. 1996, 22 (3) 221-235
46. Marshall, D. R.; Gus Rodriguez, G.; Thomson, D. S.; Nelson, R.; Capolina, A. α-Methyltryptamine sulfonamide derivatives as novel glucocorticoid receptor ligands Bioorg. Med. Chem. Lett. 2007, 17, 315-319
47. Hudson, A. R.; Roach, S. L.; Higuchi, R. I.; Philipps, D. P.; Bissonnette, R. P.; Lamph, W. W.; Yen, J.; Li, Y.; Adams, M. E.; Valdez, L. J.; Vassar, A.; Cuervo, C.; Kallel, E. A.; Gharbaoui, C. J.; Mais, D. E.; Miner, J. N.; Marshke, K. B.; Rungta, D.; Negro-Vilar, A.; Zhi, L. Synthesis and characterization of nonsteroidal glucocorticoid receptor modulators for multiple myeloma J. Med. Chem. 2007, 50 (19) 4699-4709
48. Jaroch, S.; Berger, M.; Huwe, C.; Krolikiewicz, K.; Rehwinkel, H.; Schäcke, H.; Schmees, N.; Skuballa, W. Discovery of quinolines as selective glucocorticoid receptor agonists Bioorg. Med. Chem. Lett. 2010, 20 (19) 5835-5838
49. Regan, J.; Lee, T. W.; Zindell, R. M.; Bekkali, Y.; Bentzien, J.; Gilmore, T.; Hammach, A.; Kirrane, T. M.; Kukulka, A. J.; Kuzmich, D.; Nelson, R. M.; Proudfoot, J. R.; Ralph, M.; Pelletier, J.; Souza, D.; Zuvela-Jelaska, L.; Nabozny, G.; Thomson, D. S. Quinol-4-ones as steroid A-ring mimetics in nonsteroidal dissociated glucocorticoid agonists J. Med. Chem. 2006, 49, 7887-7896
50. Ahmed, M.; Rocha, J. B. T.; Mazzanti, C. M.; Hassan, W.; Morsch, V. M.; Loro, V. L.; Thome, G.; Schetinger, M.R. C. Comparative study of the inhibitory effect of antidepressants on cholinesterase activity in Bungarussindanus (krait) venom, human serum and rat striatum J. Enzyme Inhib. Med. Chem. 2008, 23 (6) 912-917