De novo design of drug-like molecules by a fragment-based molecular evolutionary approach

Journal of Chemical Information and Modeling

Volumn 54, Issue 1, 2014, Pages 49-56

  Kawai, Kentaro ^a   Nagata, Naoya ^a   Takahashi, Yoshimasa ^b  

^a KAKEN PHARMACEUTICAL CO LTD   (Japan)

^b TOYOHASHI UNIVERSITY OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

SCAFFOLDS;

ACTIVE MOLECULES; CHEMICAL SPACE; COMPUTER EXPERIMENT; DE NOVO DESIGN; DRUG DISCOVERY; EVOLUTIONARY APPROACH; INDIVIDUAL STRUCTURES; SIDE-CHAINS;

MOLECULES;

ADENOSINE A2A RECEPTOR; LIGAND; SEROTONIN 1A RECEPTOR;

ALGORITHM; ANIMAL; BIOLOGY; CHEMICAL MODEL; CHEMICAL STRUCTURE; COMPUTER SIMULATION; DIRECTED MOLECULAR EVOLUTION; DRUG DATABASE; DRUG DESIGN; DRUG DEVELOPMENT; DRUG EFFECTS; HUMAN; MUTATION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RAT; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, PHARMACEUTICAL; DIRECTED MOLECULAR EVOLUTION; DRUG DESIGN; DRUG DISCOVERY; HUMANS; LIGANDS; MODELS, CHEMICAL; MOLECULAR STRUCTURE; MUTATION; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RATS; RECEPTOR, ADENOSINE A2A; RECEPTOR, SEROTONIN, 5-HT1A;

EID: 84893405448     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci400418c     Document Type: Article

References (37)

1. Jenkins, J. L.; Glick, M.; Davies, J. W. A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes J. Med. Chem. 2004, 47, 6144-6159
2. Oyarzabal, J.; Howe, T.; Alcazar, J.; Andrés, J. I.; Alvarez, R. M.; Dautzenberg, F.; Iturrino, L.; Martínez, S.; Van der Linden, I. Novel approach for chemotype hopping based on annotated databases of chemically feasible fragments and a prospective case study: new melanin concentrating hormone antagonists J. Med. Chem. 2009, 52, 2076-2089
3. Bahl, A.; Barton, P.; Bowers, K.; Caffrey, M. V.; Denton, R.; Gilmour, P.; Hawley, S.; Linannen, T.; Luckhurst, C. A.; Mochel, T.; Perry, M. W.; Riley, R. J.; Roe, E.; Springthorpe, B.; Stein, L.; Webborn, P. Scaffold-hopping with zwitterionic CCR3 antagonists: identification and optimization of a series with good potency and pharmacokinetics leading to the discovery of AZ12436092 Bioorg. Med. Chem. Lett. 2012, 22, 6694-6699
4. Stellwagen, J. C.; Adjabeng, G. M.; Arnone, M. R.; Dickerson, S. H.; Han, C.; Hornberger, K. R.; King, A. J.; Mook, R. A., Jr.; Petrov, K. G.; Rheault, T. R.; Rominger, C. M.; Rossanese, O. W.; Smitheman, K. N.; Waterson, A. G.; Uehling, D. E. Development of potent B-RafV600E inhibitors containing an arylsulfonamide headgroup Bioorg. Med. Chem. Lett. 2011, 21, 4436-4440
5. Rheault, T. R.; Stellwagen, J. C.; Adjabeng, G. M.; Hornberger, K. R.; Petrov, K. G.; Waterson, A. G.; Dickerson, S. H.; Mook, R. A.; Laquerre, S. G.; King, A. J.; Rossanese, O. W.; Arnone, M. R.; Smitherman, K. N.; Kane-Carson, L. S.; Han, C.; Moorthy, G. S.; Moss, K. G; Uehling, D. E. Discovery of dabrafenib: a selective inhibitor of Raf kinases with antitumor activity against B-Raf-driven tumors ACS Med. Chem. Lett. 2013, 4, 358-362
6. Nishibata, Y.; Itai, A. Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation Tetrahedron 1991, 47, 8885-8990
7. Bohm, H. J. The computer program LUDI: A new method for the de novo design of enzyme inhibitors J. Comput.-Aided Mol. Des. 1992, 6, 61-78
8. Gillet, V.; Johnson, A. P.; Mata, P.; Sike, S.; Williams, P. SPROUT: A program for structure generation J. Comput.-Aided Mol. Des. 1993, 7, 127-153
9. Douguet, D.; Munier-Lehmann, H.; Labesse, G.; Pochet, S. LEA3D: a computer-aided ligand design for structure-based drug design J. Med. Chem. 2005, 48, 2457-2468
10. Wang, R.; Gao, Y.; Lai, L. A multi-purpose program for structure-based drug design J. Mol. Model. 2000, 6, 498-516
11. Yuan, Y.; Pei, J.; Lai, L. LigBuilder 2: A practical de novo drug design approach J. Chem. Inf. Model. 2011, 51, 1083-1091
12. Vinkers, H. M.; de Jonge, M. R.; Daeyaert, F. F.; Heeres, J.; Koymans, L. M.; van Lenthe, J. H.; Lewi, P. J.; Timmerman, H.; Van Aken, K.; Janssen, P. A. SYNOPSIS: synthesize and optimize system in silico J. Med. Chem. 2003, 46, 2765-2773
13. Schneider, G.; Lee, M. L.; Stahl, M.; Schneider, P. De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks J. Comput.-Aided Mol. Des. 2000, 14, 487-494
14. Brown, N.; McKay, B.; Gilardoni, F.; Gasteiger, J. A graph-based genetic algorithm and its application to the multiobjective evolution of median molecules J. Chem. Inf. Comput. Sci. 2004, 44, 1079-1087
15. Fechner, U.; Schneider, G. Flux (1): A virtual synthesis scheme for fragment-based de novo design J. Chem. Inf. Model. 2006, 46, 699-707
16. Fechner, U.; Schneider, G. Flux (2): Comparison of molecular mutation and crossover operators for ligand-based de novo design J. Chem. Inf. Model. 2007, 47, 656-667
17. Lameijer, E. W.; Kok, J. N.; Bäck, T.; Ijzerman, A. P. The molecule evoluator. An interactive evolutionary algorithm for the design of drug-like molecules J. Chem. Inf. Model. 2006, 46, 545-552
18. Huang, Q.; Li, L. L.; Yang, S. Y. PhDD: a new pharmacophore-based de novo design method of drug-like molecules combined with assessment of synthetic accessibility J. Mol. Graph. Model. 2010, 28, 775-787
19. Damewood, J. R., Jr.; Lerman, C. L.; Masek, B. B. NovoFLAP: A ligand-based de novo design approach for the generation of medicinally relevant ideas J. Chem. Inf. Model. 2010, 50, 1296-1303
20. Kawai, K.; Yoshimaru, K.; Takahashi, Y. Generation of target-selective drug candidate structures using molecular evolutionary algorithm with SVM classifiers J. Comput. Chem. Jpn. 2011, 10, 79-87
21. Gillet, V.; Johnson, A. P.; Mata, P.; Sike, S.; Williams, P. SPROUT: A program for structure generation J. Comput.-Aided Mol. Des. 1993, 7, 127-153
22. Eisen, M. B.; Wiley, D. C.; Karplus, M.; Hubbard, R. E. HOOK: A program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site Proteins 1994, 19, 199-221
23. Bohacek, R. S.; McMartin, C. Multiple highly diverse structures complementary to enzyme binding sites: Results of extensive application of de novo design method incorporating combinatorial growth J. Am. Chem. Soc. 1994, 116, 5560-5571
24. Pearlman, D. A.; Murcko, M. A. CONCERTS: Dynamic connection of fragments as an approach to de novo ligand design J. Med. Chem. 1996, 39, 1651-1663
25. Beccari, A. R.; Cavazzoni, C.; Beato, C.; Costantino, G. LiGen: A High Performance Workflow for Chemistry Driven de Novo Design J. Chem. Inf. Model. 2013, 53, 1518-1527
26. Schneider, G.; Fechner, U. Computer-based de novo design of drug-like molecules Nat. Rev. Drug Discov. 2005, 4, 649-663
27. Dey, F.; Caflisch, A. Fragment-based de novo ligand design by multiobjective evolutionary optimization J. Chem. Inf. Model. 2008, 48, 679-690
28. Wang, J.; Krudy, G.; Xie, X. Q.; Wu, C.; Holland, G. Genetic Algorithm-Optimized QSPR Models for Bioavailability, Protein Binding, and Urinary Excretion J. Chem. Inf. Model. 2006, 46, 2674-2683
29. Jones, G.; Gao, Y.; Sage, C. R. Elucidating molecular overlays from pairwise alignments using a genetic algorithm J. Chem. Inf. Model. 2009, 49, 1847-1855
30. Walters, W. P.; Green, J.; Weiss, J. R.; Murcko, M. A. What do medicinal chemists actually make? A 50-year retrospective J. Med. Chem. 2011, 54, 6405-6416
31. GPCR SARfari. https://www.ebi.ac.uk/chembl/sarfari/gpcrsarfari (accessed Mar 8, 2013).
32. Gaulton, A.; Bellis, L. J.; Bento, A. P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J. P. ChEMBL: a large-scale bioactivity database for drug discovery Nucleic Acids Res. 2012, 40, D1100-1107
33. O'Boyle, N. M.; Banck, M.; James, C. A.; Morley, C.; Vandermeersch, T.; Hutchison, G. R. Open Babel: An open chemical toolbox J. Cheminf. 2011, 3, 33
34. Takahashi, Y.; Ohoka, H.; Ishiyama, Y. Structural Similarity Analysis Based on Topological Fragment Spectra. In Advances in Molecular Similarity; Carbo, R.; Mezey, P., Eds.; JAI Press: Greenwich, CT, 1998; Vol. 2, pp 93-104.
35. Kawai, K.; Fujishima, S.; Takahashi, Y. Predictive activity profiling of drugs by topological-fragment-spectra-based support vector machines J. Chem. Inf. Model. 2008, 48, 1152-1160
36. Takahashi, Y. Chemical data mining based on non-terminal vertex graph. In 2004 IEEE International Conference on Systems, Man and Cybernetics, The Hague, Oct 10-13; IEEE: Piscataway, NJ, 2004; Vol. 5, pp 4583-4587.
37. St. Jean, D. J., Jr.; Fotsch, C. Mitigating heterocycle metabolism in drug discovery J. Med. Chem. 2012, 55, 6002-6020