FOG: Fragment optimized growth algorithm for the de novo generation of molecule: Occupying druglike chemical Space

Journal of Chemical Information and Modeling

Volumn 49, Issue 7, 2009, Pages 1630-1642

  Kutchukian, Peter S ^a   Lou, David ^a   Shakhnovich, Eugene I ^a  

^a HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL INDUSTRY; MARKOV CHAINS;

CHEMICAL SPACE; CLASSIFICATION ACCURACY; COMBINATORIAL EXPLOSION; ESSENTIAL FEATURES; GROWTH ALGORITHMS; NATURAL PRODUCTS; STABILITY IN WATERS; SYNTHETIC PRODUCTS;

MOLECULES;

BIOLOGICAL PRODUCT; DRUG;

ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; DRUG DESIGN; MOLECULAR LIBRARY; PROBABILITY;

ALGORITHMS; BIOLOGICAL PRODUCTS; DRUG DESIGN; MARKOV CHAINS; MOLECULAR STRUCTURE; PHARMACEUTICAL PREPARATIONS; SMALL MOLECULE LIBRARIES;

EID: 68149124133     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci9000458     Document Type: Article

References (79)

1. Mauser, H.; Guba, W. Recent developments in de novo design and scaffold hopping. Curr. Opin. Drue Discovery Dev. 2008, 11 (3), 365-74.
2. 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 (13), 2765-73.
3. Schneider, G.; Fechner, U. Computer-based de novo design of drug-like molecules. Nat. Rev. Drue Discovery 2005, 4 (8), 649-63.
4. Todorov, N. P.; Alberts, I. L.; Dean, P. M. De Novo Design. In Comprehensive Medicinal Chemistry, II; Triggle, D. J., Taylor, J. B., Eds.; Elsevier Science: Amsterdam, The Netherlands, 2006; Vol. 4, pp 283-305.
5. Cayley, A. On the Mathematical Theory of Isomers. Philos. Mag. 1874, 47, 444-446.
6. Trinajstic, N.; Nikolic, S.; Knop, J. V.; Müller, W. R.; Szymansky, K., Computational Graph Theory: Characterization, Enumeration and Generation of Chemical Structures by Computer Methods; Ellis Horwood: New York, 1991.
7. Bohacek, R. S.; McMartin, C.; Guida, W. C. The art and practice of structure-based drug design: a molecular modeling perspective. Med. Res. Rev. 1996, 16 (1), 3-50.
8. Fink, T.; Bruggesser, H.; Reymond, J. L. Virtual exploration of the small-molecule chemical universe below 160 Da. Angew. Chem. Int. Ed. Enel. 2005, 44 (10), 1504-8.
9. Fink, T.; Reymond, J. L. Virtual exploration of the chemical universe up to 11 atoms of C, N, O, F: assembly of 26.4 million structures (110.9 million stereoisomers) and analysis for new ring systems, stereochemistry, physicochemical properties, compound classes, and drug discovery. J. Chem. Inf. Model. 2007, 47 (2), 342-53.
10. Miranker, A.; Karplus, M. Functionality Maps of Binding-Sites - a Multiple Copy Simultaneous Search Method. Proteins: Struct. Funct., Genet. 1991, 11 (1), 29-34.
11. Gillet, V. J.; Johnson, A. P.; Mata, P.; Sike, S. Automated structure design in 3D. Tetrahedron Comput. Methodol. 1990, 3, 681-696.
12. Gillet, V.; Johnson, A. P.; Mata, P.; Sike, S.; Williams, P. SPROUT: a program for structure generation. J. Comput.-Aided Mol. Des. 1993, 7 (2), 127-53.
13. Gillet, V. J.; Newell, W.; Mata, P.; Myatt, G.; Sike, S.; Zsoldos, Z.; Johnson, A. P. SPROUT: recent developments in the de novo design of molecules. J. Chem. Inf. Comput. Sci. 1994, 34 (1), 207-17.
14. 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 (1), 61-78.
15. Verlinde, C. L.; Rudenko, G.; Hol, W. G. In search of new lead compounds for trypanosomiasis drug design: a protein structure-based linked-fragment approach. J. Comput.-Aided Mol. Des. 1992, 6 (2), 131-47.
16. Rotstein, S. H.; Murcko, M. A. GenStar: a method for de novo drug design. J. Comput.-Aided Mol. Des. 1993, 7 (1), 23-43.
17. Pearlman, D. A.; Murcko, M. A. Concepts - New Dynamic Algorithm for De-Novo Drug Suggestion. J. Comput. Chem. 1993, 14 (10), 1184-1193.
18. Clark, D. E.; Frenkel, D.; Levy, S. A.; Li, J.; Murray, C. W.; Robson, B.; Waszkowycz, B.; Westhead, D. R. PRO-LIGAND: an approach to de novo molecular design. 1. Application to the design of organic molecules. J. Comput.-Aided Mol. Des. 1995, 9 (1), 13-32.
19. DeWitte, R. S.; Shakhnovich, E. SMoG: de novo design method based on simple, fast and accurate free energy estimates. 1. Methodology and supporting evidence. J. Am. Chem. Soc. 1996, 118, 11733-11744.
20. Gehlhaar, D. K.; Moerder, K. E.; Zichi, D.; Sherman, C. J.; Ogden, R. C.; Freer, S. T. De novo design of enzyme inhibitors by Monte Carlo ligand generation. J. Med. Chem. 1995, 38 (3), 466-72.
21. Miranker, A.; Karplus, M. An automated method for dynamic ligand design. Proteins 1995, 23 (4), 472-90.
22. Roe, D. C.; Kuntz, I. D. BUILDER v. 2: improving the chemistry of a de novo design strategy. J. Comput. Aided. Mol. Des. 1995, 9 (3), 269-82.
23. Nishibata, Y.; Itai, A. Automatic Creation of Drug Candidate Structures Based On Receptor Structure - Starting Point For Artificial Lead Generation. Tetrahedron 1991, 47 (43), 8985-8990.
24. Nishibata, Y.; Itai, A. Confirmation of Usefulness of a Structure Construction Program Based on 3-Dimensional Receptor Structure for Rational Lead Generation. J. Med. Chem. 1993, 36 (20), 2921-2928.
25. Bohacek, R. S.; Mcmartin, C. Multiple Highly Diverse Structures Complementary to Enzyme Binding-Sites - Results of Extensive Application of a De-Novo Design Method Incorporating Combinatorial Growth. J. Am. Chem. Soc. 1994, 116 (13), 5560-5571.
26. Luo, Z. W.; Wang, R. X.; Lai, L. H. RASSE: A new method for structure-based drug design. J. Chem. Inf. Comput. Sci. 1996, 36 (6), 1187-1194.
27. Rotstein, S. H.; Murcko, M. A. GroupBuild: a fragment-based method for de novo drug design. J. Med. Chem. 1993, 36 (12), 1700-10.
28. Moon, J. B.; Howe, W. J. Computer design of bioactive molecules: a method for receptor-based de novo ligand design. Proteins 1991, 11 (4), 314-28.
29. Bohm, H. J. Towards the automatic design of synthetically accessible protein ligands: peptides, amides and peptidomimetics. J. Comput.-Aided Mol. Des. 1996, 10 (4), 265-72.
30. Corey, E. J.; Howe, W. J.; Orf, H. W.; Pensak, D. A.; Petersson, G. General methods of synthetic analysis. Strategic bond disconnections for bridged polycyclic structures. J. Am. Chem. Soc. 1975, 97 (21), 6116-6124.
31. Corey, E. J.; Jorgensen, W. L. Computer-assisted synthetic analysis. Generation of synthetic sequences involving sequential functional group interchanges. J. Am. Chem. Soc. 1975, 98 (1), 203-209.
32. Corey, E. J.; Jorgensen, W. L. Computer-assisted synthetic analysis. Synthetic strategies based on appendages and the use of reconnective transforms. J. Am. Chem. Soc. 1976, 98 (1), 189-203.
33. Corey, E. J.; Long, A. K.; Greene, T. W.; Miller, J. W. Computer-assisted synthetic analysis. Selection of protective groups for multistep organic synthesis. J. Org. Chem. 1985, 50 (11), 1920-1927.
34. Hendrickson, J. B. A general protocol for systematic synthesis design. Top. Curr. Chem. 1976, 62, 49-172.
35. Hendrickson, J. B. Approaching the Logic of Synthesis Design. Acc. Chem. Res. 1986, 19, 274-281.
36. Hendrickson, J. B.; Miller, T. M. Reaction Classification and Retrieval. A Linkage between Synthesis Generation and Reaction Databases. J. Am. Chem. Soc. 1991, 113, 902-910.
37. Hendrickson, J. B.; Parks, C. A. A Program for the Forward Generation of Synthetic Routes. J. Chem. Inf. Comput. Sci. 1992, 32, 209-215.
38. Hendrickson, J. B.; Walker, M. A. A two-component pericyclic reaction for synthesis of substituted benzofurans and aryl-quaternary carbon bonds. Org. Lett. 2000, 2 (18), 2729-31.
39. Hendrickson, J. B.; Wang, J. A new synthesis of lysergic acid. Org. Lett. 2004, 6 (1), 3-5.
40. Gillet, V. J.; Myatt, G.; Zsoldos, Z.; Johnson, A. P. SPROUT, HIPPO and CAESA: tools for de novo structure generation and estimation of synthetic accessibility. Perspect. Drug Discovery Des. 1995, 3, 34-50.
41. Boda, K.; Scidel, T.; Gasteiger, J. Structure and reaction based evaluation of synthetic accessibility. J. Comput.-Aided Mol. Des. 2007, 21 (6), 311-25.
42. Makino, S.; Ewing, T. J.; Kuntz, I. D. DREAM++: flexible docking program for virtual combinatorial libraries. J. Comput.-Aided Mol. Des. 1999, 13 (5), 513-32.
43. 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 (5), 487-94.
44. Jorgensen, W. L.; Ruiz-Caro, J.; Tirado-Rives, J.; Basavapathruni, A.; Anderson, K. S.; Hamilton, A. D. Computer-aided design of nonnucleoside inhibitors of HIV-1 reverse transcriptase. Bioorg. Med. Chem. Lett. 2006, 16 (3), 663-7.
45. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Delivery Rev. 1997, 23, 3-25.
46. Wang, R.; Gao, Y.; Lai, L. LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design. J. Mol. Model. 2000, 6, 498-516.
47. Frimurer, T. M.; Bywater, R.; Naerum, L.; Lauritsen, L. N.; Brunak, S. Improving the odds in discriminating "drug-like" from "non drug-like" compounds. J. Chem. Inf. Comput. Sci. 2000, 40 (6), 1315-24.
48. Takaoka, Y.; Endo, Y.; Yamanobe, S.; Kakinuma, H.; Okubo, T.; Shimazaki, Y.; Ota, T.; Sumiya, S.; Yoshikawa, K. Development of a method for evaluating drug-likeness and ease of synthesis using a data set in which compounds are assigned scores based on chemists' intuition. J. Chem. Inf. Comput. Sci. 2003, 43 (4), 1269-75.
49. Schneider, N.; Jackels, C.; Andres, C.; Hutter, M. C. Gradual in silico filtering for druglike substances. J. Chem. Inf. Model. 2008, 48 (3), 613-28.
50. Harper, G.; Bradshaw, J.; Gittins, J. C.; Green, D. V.; Leach, A. R. Prediction of biological activity for high-throughput screening using binary kernel discrimination. J. Chem. Inf. Comput. Sci. 2001, 41 (5), 1295-300.
51. Chen, B.; Harrison, R. F.; Pasupa, K.; Willett, P.; Wilton, D. J.; Wood, D. J.; Lewell, X. Q. Virtual screening using binary kernel discrimination: effect of noisy training data and the optimization of performance. J. Chem. Inf. Model. 2006, 46 (2), 478-86.
52. Sadowski, J.; Kubinyi, H. A scoring scheme for discriminating between drugs and nondrugs. J. Med. Chem. 1998, 41 (18), 3325-9.
53. Frimurer, T. M.; By water, R.; Naerum, L.; Lauritsen, L. N.; Brunak, S. Improving the odds in discriminating "drug-like" from "non drug-like" compounds. J. Chem. Inf. Comput. Sci. 2000, 40 (6), 1315-24.
54. Murcia-Soler, M.; Perez-Gimenez, F.; Garcia-March, F. J.; Salabert-Salvador, M. T.; Diaz-Villanueva, W.; Castro-Bleda, M. J. Drugs and nondrugs: an effective discrimination with topological methods and artificial neural networks. J. Chem. Inf. Comput. Sci. 2003, 43 (5), 1688-702.
55. Lang, S. A.; Kozyukov, A. V.; Balakin, K. V.; Skorenko, A. V.; Ivashchenko, A. A.; Savchuk, N. P. Classification scheme for the design of serine protease targeted compound libraries. J. Comput. Aided. Mol. Des. 2002, 16 (11), 803-7.
56. Balakin, K. V.; Tkachenko, S. E.; Lang, S. A.; Okun, I.; Ivashchenko, A. A.; Savchuk, N. P. Property-based design of GPCR-targeted library. J. Chem. Inf. Comput. Sci. 2002, 42 (6), 1332-42.
57. Balakin, K. V.; Lang, S. A.; Skorenko, A. V.; Tkachenko, S. E.; Ivashchenko, A.A.; Savchuk, N. P. Structure-based versus property-based approaches in the design of G-protein-coupled receptor-targeted libraries. J. Chem. Inf. Comput. Sci. 2003, 43 (5), 1553-62.
58. Muresan, S.; Sadowski, J. "In-house likeness": comparison of large compound collections using artificial neural networks. J. Chem. Inf. Model. 2005, 45 (4), 888-93.
59. Ajay, A.; Walters, W. P.; Murcko, M. A. Can we learn to distinguish between "drug-like" and "nondrug-like" molecules. J. Med. Chem. 1998, 41 (18), 3314-24.
60. Ajay, A.; Bemis, G. W.; Murcko, M. A. Designing libraries with CNS activity. J. Med. Chem. 1999, 42 (24), 4942-51.
61. Niwa, T. Prediction of biological targets using probabilistic neural networks and atom-type descriptors. J. Med. Chem. 2004, 47 (10), 2645-50.
62. Murcia-Soler, M.; Perez-Gimenez, F.; Garcia-March, F. J.; Salabert-Salvador, M. T.; Diaz-Villanueva, W.; Castro-Bleda, M. J.; Villanueva-Pareja, A. Artificial neural networks and linear discriminant analysis: a valuable combination in the selection of new antibacterial compounds. J. Chem. Inf. Comput. Sci. 2004, 44 (3), 1031-41.
63. Engkvist, O.; Wrede, P.; Rester, U. Prediction of CNS activity of compound libraries using substructure analysis. J. Chem. Inf. Comput. Sci. 2003, 43 (1), 155-60.
64. Hutter, M. C. Separating drugs from nondrugs: a statistical approach using atom pair distributions. J. Chem. Inf. Model. 2007, 47 (1), 186-94.
65. ChemBank. http://chembank.broad.harvard.edu/welcome.htm (accessed July 6, 2006).
66. NCI Open Database. http://cactus.nci.nih.gov/ncidb2/download.html (accessed July 6, 2006).
67. Daylight Theory Manual. In Daylight Chemical Information Systems, Inc.: Aliso Viejo, CA, 2008.
68. ChemAxon. http://www.chemaxon.com (accessed July 6, 2006).
69. de Silva, K. M.; Goodman, J. M. What is the smallest saturated acyclic alkane that cannot be made. J. Chem. Inf. Model. 2005, 45 (1), 81-7.
70. Weininger, D. Smiles, a Chemical Language and Information-System 0.1. Introduction to Methodology and Encoding Rules. J. Chem. Inf. Comput. Sci. 1988, 28 (1), 31-36.
71. Badger, G. M. The Structures and Reactions of the Aromatic Compounds; Cambridge University Press: Cambridge, 1954.
72. Veber, D. F.; Johnson, S. R.; Cheng, H. Y.; Smith, B. R.; Ward, K. W.; Kopple, K. D. Molecular properties that influence the oral bioavail-ability of drug candidates. J. Med. Chem. 2002, 45 (12), 2615-23.
73. Ho, C. M.; Marshall, G. R. DBMAKER: a set of programs to generate three-dimensional databases based upon user-specified criteria. J. Comput.-Aided Mol. Des. 1995, 9 (1), 65-86.
74. Nilakantan, R.; Bauman, N.; Venkataraghavan, R. A Method for Automatic-Generation of Novel Chemical Structures and Its Potential Applications to Drug Discovery. J. Chem. Inf. Comput. Sci. 1991, 31 (4), 527-530.
75. Cosgrove, D. A.; Kenny, P. W. BOOMSLANG: a program for combinatorial structure generation. J. Mol. Graph. 1996, 14 (1), 1-5, 23.
76. Zheng, W.; Cho, S. J.; Tropsha, A. Rational combinatorial library design. 1. Focus-2D: a new approach to the design of targeted combinatorial chemical libraries. J. Chem. Inf. Comput. Sci. 1998, 38 (2), 251-8.
77. Clark, D. E.; Firth, M. A.; Murray, C. W. MOLMAKER: De novo generation of 3D databases for use in drug design. J. Chem. Inf. Comput. Sci. 1996, 36 (1), 137-145.
78. Pirok, G.; Mate, N.; Varga, J.; Szegezdi, J.; Vargyas, M.; Dorant, S.; Csizmadia, F. Making "real" molecules in virtual space. J. Chem. Inf. Model. 2006, 46 (2), 563-8.
79. Cramer, R. D.; Soltanshahi, F.; Jilek, R.; Campbell, B. AllChem: generating and searching 10(20) synthetically accessible structures. J. Comput.-Aided Mol. Des. 2007, 21 (6), 341-50.