Iterative refinement of a binding pocket model: Active computational steering of lead optimization

Journal of Medicinal Chemistry

Volumn 55, Issue 20, 2012, Pages 8926-8942

  Varela, Rocco ^a   Walters, W Patrick ^b   Goldman, Brian B ^b   Jain, Ajay N ^a  

^a San Francisco   (United States)

^b VERTEX PHARMACEUTICALS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GYRASE INHIBITOR;

ARTICLE; BINDING AFFINITY; COMPUTER ANALYSIS; COMPUTER PREDICTION; CONTROLLED STUDY; LEAD OPTIMIZATION; PROCESS OPTIMIZATION; STRUCTURE ACTIVITY RELATION; SYNTHESIS;

ADENOSINE TRIPHOSPHATE; BACTERIAL PROTEINS; BENZIMIDAZOLES; BINDING SITES; COMPUTER SIMULATION; DNA GYRASE; DRUG DESIGN; MOLECULAR DOCKING SIMULATION; PROTEIN BINDING; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84867834357     PISSN: 00222623     EISSN: 15204804     Source Type: Journal    
DOI: 10.1021/jm301210j     Document Type: Article

References (21)

1. Hansch, C.; Leo, A. Substituent Constants for Correlation Analysis in Chemistry and Biology; Wiley: New York, 1979.
2. Langham, J. J.; Cleves, A. E.; Spitzer, R.; Kirshner, D.; Jain, A. N. Physical binding pocket induction for affinity prediction J. Med. Chem. 2009, 52, 6107-6125
3. Jain, A. N. QMOD: Physically meaningful QSAR J. Comput. Aided Mol. Des. 2010, 24, 865-878
4. Jain, A.; Cleves, A. Does your model weigh the same as a Duck? J. Comput. Aided Mol. Des. 2012, 26, 57-67
5. Charifson, P.; Grillot, A.; Grossman, T.; Parsons, J.; Badia, M.; Bellon, S.; Deininger, D.; Drumm, J.; Gross, C.; LeTiran, A. Novel dual-targeting benzimidazole urea inhibitors of DNA gyrase and topoisomerase IV possessing potent antibacterial activity: intelligent design and evolution through the judicious use of structure-guided design and stucture- activity relationships J. Med. Chem. 2008, 51, 5243-5263
6. Dietterich, T.; Lathrop, R.; Lozano-Pérez, T. Solving the multiple instance problem with axis-parallel rectangles Artif. Intell. 1997, 89, 31-71
7. Jain, A. N.; Dietterich, T. G.; Lathrop, R. H.; Chapman, D.; Critchlow, J., R. E.; Bauer, B. E.; Webster, T. A.; Lozano-Perez, T. A Shape-Based Machine Learning Tool for Drug Design J. Comput. Aided Mol. Des. 1994, 8, 635-652
8. Jain, A. N.; Koile, K.; Chapman, D. Compass: Predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark J. Med. Chem. 1994, 37, 2315-2327
9. Jain, A. N.; Harris, N. L.; Park, J. Y. Quantitative binding site model generation: Compass applied to multiple chemotypes targeting the 5-HT1a receptor J. Med. Chem. 1995, 38, 1295-1308
10. Jain, A. N. Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities J. Comput. Aided Mol. Des. 1996, 10, 427-440
11. Pham, T. A.; Jain, A. N. Parameter estimation for scoring protein-ligand interactions using negative training data J. Med. Chem. 2006, 49, 5856-5868
12. Pham, T. A.; Jain, A. N. Customizing scoring functions for docking J. Comput. Aided Mol. Des. 2008, 22, 269-286
13. Breiman, L. Random forests Mach. Learn. 2001, 45, 5-32
14. Svetnik, V.; Liaw, A.; Tong, C.; Culberson, J.; Sheridan, R.; Feuston, B. Random forest: A classification and regression tool for compound classification and QSAR modeling J. Chem. Inf. Comput. Sci. 2003, 43, 1947-1958
15. Chen, B.; Sheridan, R.; Hornak, V.; Voigt, J. Comparison of random forest and Pipeline Pilot Naive Bayes in prospective QSAR predictions J. Chem. Inf. Model 2012, 52, 792-803
16. Kell, D. Scientific discovery as a combinatorial optimization problem: How best to navigate the landscape of possible experiments? BioEssays 2012, 34, 236-244
17. Warmuth, M.; Liao, J.; Rätsch, G.; Mathieson, M.; Putta, S.; Lemmen, C. Active learning with support vector machines in the drug discovery process J. Chem. Inf. Comput. Sci. 2003, 43, 667-673
18. Fujiwara, Y.; Yamashita, Y.; Osoda, T.; Asogawa, M.; Fukushima, C.; Asao, M.; Shimadzu, H.; Nakao, K.; Shimizu, R. Virtual screening system for finding structurally diverse hits by active learning J. Chem. Inf. Model. 2008, 48, 930-940
19. Spitzer, R.; Cleves, A. E.; Jain, A. N. Surface-based protein binding pocket similarity Proteins 2011, 79, 2746-63
20. Brown, S.; Muchmore, S. Large-scale application of high-throughput molecular mechanics with Poisson-Boltzmann surface area for routine physics-based scoring of protein-ligand complexes J. Med. Chem. 2009, 52, 3159-3165
21. Durant, J.; Leland, B.; Henry, D.; Nourse, J. Reoptimization of MDL keys for use in drug discovery J. Chem. Inf. Comput. Sci. 2002, 42, 1273-1280