Genetic algorithms in molecular modelling: a review

Data Handling in Science and Technology

Volumn 23, Issue C, 2003, Pages 109-139

  Maiocchi, Alessandro ^a  

^a Milano Research Centre   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 27944439211     PISSN: 09223487     EISSN: None     Source Type: Book Series    
DOI: 10.1016/S0922-3487(03)23004-5     Document Type: Review

References (113)

1. Allen F.H., Davies J.E., Galloy J.J., Johnson O., Kennard O., Macrae C.F., Mitchell E.M., Mitchell G.F., Smith J.M., and Watson D.G. The development of Versions 3 and 4 of the Cambridge structural database system. J Chem. Inf. Comput. Sci. 31 (1991) 187-204
2. Allinger N.L. Conformational Analysis.130.MM2. A hydrocarbon force field utilizing V1 and V2 torsional terms. J. Am. Chem. Soc. 99 (1977) 8127-8134
3. Anfinsen C.B. Principles that govern the folding of protein chains. Science 181 (1973) 223-230
4. Baylay M.J., Jones G., Willet P., and Williamson M.P. GENFOLD: a genetic algorithm for folding protein structure using NMR restraints. Protein Sci. 7 (1998) 491-499
5. Barnum D., Greene J., Smellie A., and Sprague P. Identification of common functional configurations among molecules. J. Chem. Inf. Comput. Sci. 36 (1996) 563-571
6. Beckers M.L.M., Buydens L.M.C., Pikkemaat J.A., and Altona C. Application of a genetic algorithm in the conformational analysis of methylene-acetal-linked thymine dimers in DNA: comparison with distance geometry calculations. J. Biomol. NMR 9 (1997) 25-34
7. Blundell T.L., Sibanda B.L., Sternberg M.J.E., and Thornton J.M. Knowledge-based prediction of protein structures and the design of novel molecules. Nature (London) 326 (1987) 347-352
8. Böhm H.J. LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads. J. Comput.-Aided Mol. Des. 6 (1992) 593-606
9. Böhm H.J. The development of a simple scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure. J Comput.-Aided Mol. Des. 8 (1994) 243-256
10. Böhm H.J., and Stahl M. The use of scoring functions in drug discovery applications. In: Lipkowitz K.B., and Boyd D.B. (Eds). Chapter 2 in Reviews in Computational Chemistry Vol. 17 (2002), Wiley-VCH, New York
11. Bowie J.U., and Eisenberg D. An evolutionary approach to folding small α-helical proteins that use sequence information and an empirical guiding fitness function. Proc. Natl Acad. Sci. USA 91 (1994) 4436-4440
12. Brodmeier T., and Pretsch E. Application of genetic algorithms in molecular modelling. J. Comput. Chem. 15 (1994) 588-595
13. Brooks B.R., Bruccoleri R.E., Olafson B.D., States D.J., Swaminathan S., and Karplus M. CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J. Comput. Chem. 4 (1983) 187-217
14. Budin N., Majeux N., and Caflisch A. Fragment-based flexible ligand docking by evolutionary optimization. Biol. Chem. 382 (2001) 1365-1372
15. Clark K.P., and Ajay J. Flexible ligand docking without parameter adjustment across four ligand-receptor complexes. J. Comput. Chem. 16 (1995) 1210-1226
16. Clark M., Cramer III R.D., and Van Opdenbosch N. Validation of the general purpose TRIPOS 5.2 force field. J. Comput. Chem. 10 (1989) 982-1012
17. Clark D.E., Jones G., Willet P., and Kenny P.W. Pharmacophoric pattern matching in files of three-dimensional chemical structures: use of bounded distance matrices for the representation and searching of conformationally-flexible molecules. J. Mol. Graphics 10 (1992) 194-204
18. Clark D.E., Jones G., Willet P., Kenny P.W., and Glen R.C. Pharmacophoric pattern matching in files of three-dimensional chemical structures: comparison of conformational-searching algorithms for flexible searching. J. Chem. Inf. Comput. Sci. 34 (1994) 197-206
19. Crippen G.M. Rapid calculations of coordinates from distance matrices. J. Comput. Phys. 26 (1978) 449-452
20. Cui Y., Chen R.S., and Wong W.H. Protein folding simulation with genetic algorithm and supersecondary structure constraints. Proteins: Struct. Funct. Genet. 31 (1998) 247-257
21. Dandekar T., and Argos P. Folding the main-chain of small proteins with the genetic algorithm. J. Mol. Biol. 236 (1994) 844-861
22. Dandekar T., and Argos P. Identifying the tertiary fold of small proteins with different topologies from sequence and secondary structure using the genetic algorithm and extended criteria specific for strand regions. J. Mol. Biol. 256 (1996) 645-660
23. Davis L. Handbook of Genetic Algorithms (1991), Van Nostrand Reinhold, New York
24. Davis L. Handbook of Genetic Algorithms (1991), Van Nostrand Reinhold, New York
25. Dewar M.J.S., Zoebisch E.G., Healy E.F., and Stewart J.J.P. Austin model 1, newly parameterized MNDO version. J. Am. Chem. Soc. 107 (1985) 3902-3909
26. Dennis J.E., and Torczon V.J. Direct search methods on parallel machines. SIAM J. Optimization 1 (1991) 448-474
27. th European Symposium on Structure-Activity Relationships: QSAR and Molecular Modelling (1993), ESCOM Science Publishers, Leiden, The Nederlands 412-413
28. Fesik S.W. NMR studies of molecular complexes as a tool in drug design. J. Med. Chem. 34 (1991) 2937-2945
29. Flury B. Principal Component Analysis and Related Multivariate Models (1988), Wiley, New York
30. Forrest S. Genetic algorithms: principles of natural selection applied to computation. Science 261 (1993) 872-878
31. Gehlhaar D.K., Verkhivker G.M., Rejto P.A., Sherman C.J., Fogel D.B., Fogel L.J., and Freer S.T. Molecular recognition of the inhibitor AG-1343 by HIV-1 protease. Conformationally flexible docking by evolutionary programming. Chem. Biol. 2 (1995) 317-324
32. Goldberg D.E. Genetic Algorithms in Search Optimization & Machine Learning (1989), Addison-Wesley, Reading, MA
33. Goldberg D.E. Genetic Algorithms in Search Optimization & Machine Learning (1989), Addison-Wesley, Reading, MA
34. Hasel W., Hendrickson T.F., and Still W.C. A rapid approximation to the solvent accessible surface areas of atoms. Tetrahedron Comput. Meth. 1 (1988) 103-116
35. Havel T.F. An evaluation of computational strategies for use in the determination of protein structure from distance restraints obtained by nuclear magnetic resonance. Prog. Biophys. Mol. Biol. 56 (1991) 43-78
36. Hermann F., and Suhai S. Energy minimization of peptide analogues using genetic algorithms. J. Comput. Chem. 16 (1995) 1434-1444
37. Hurst T. Flexible 3D searching: the directed tweak technique. J. Chem. Inf. Comp. Sci. 34 (1994) 190-196
38. Jin A.Y., Leung F.Y., and Weaver D.F. Three variations of genetic algorithm for searching biomolecular conformation space: Comparison of GAP 1.0, 2.0 and 3.0. J. Comput. Chem. 20 (1999) 1329-1342
39. Jones G., Willett P., and Glen R.C. A genetic algorithm for flexible molecular overlay and pharmacophore elucidation. J. Comput.-Aided Mol. Des. 9 (1995) 532-549
40. Jones G., Willett P., and Glen R.C. Molecular recognition of receptor sites using a genetic algorithm with a description of solvation. J. Mol. Biol. 254 (1995) 43-53
41. Jones G., Willett P., and Glen R.C. Genetic algorthms for chemical structure handling and molecular recognition. In: Devillers J. (Ed). Chapter 9 in Genetic Algorithms in Molecular Modeling (1996), Academic Press, London 211-242
42. Jones G., Willett P., Glen R.C., Leach A.R., and Taylor R. Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol. 267 (1997) 727-748
43. Jorgensen W.L., and Tirado-Rives J. The OPLS (optimized potentials for liquid simulations) potential functions for proteins, energy minimizations for crystal of cyclic peptides and crambin. J. Am. Chem. Soc. 110 (1988) 1657-1666
44. Jorgensen W.L., Maxwell D.S., and Tirado-Rives J. Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J. Am. Chem. Soc. 118 (1996) 11225-11236
45. Judson R.S. Genetic algorithms and their use in chemistry. In: Lipkowitz K.B., and Boyd D.B. (Eds). Chapter 1 in Reviews in Computational Chemistry Vol. 10 (1997), VCH Publishers, New York
46. Judson R.S., Colvin M.E., Meza J.C., Huffer A., and Gutierrez D. Do intelligent configuration search techniques outperform random search for large molecules. Int. J. Quantum Chem. 44 (1992) 277-290
47. Judson R.S., Jaeger E.P., Treasurywala A.M., and Peterson M.L. Conformational searching methods for small molecules II. Genetic algorithm approach. J. Comput. Chem. 14 (1993) 1407-1414
48. Judson R.S., Jaeger E.P., and Treasurywala A.M. A genetic algorithm based method for docking flexible molecules. J. Mol. Struct. (THEOCHEM) 308 (1994) 191-206
49. Judson R.S., Tan Y.T., Mori E., Melius C., Jaeger E.P., Treasurywala A.M., and Mathiowetz A. Docking flexible molecules: a case study of three proteins. J. Comput. Chem. 16 (1995) 1405-1419
50. van Kampen A.H.C., Buydens L.M.C., Lucasius C.B., and Blommers M.J.J. Optimization of metrics matrix embedding by genetic algorithms. J. Biomol. NMR 7 (1996) 214-224
51. van Kampen A.H.C., and Buydens L.M.C. The ineffectiveness of recombination in genetic algorithm for the structure elucidation of a heptapeptide in torsion angle space. A comparison to simulated annealing. Chemom. Intell. Lab. Syst. 36 (1997) 141-152
52. Kim P.S., and Baldwin R.L. Intermediates in the folding reactions of small proteins. Annu. Rev. Biochem. 59 (1990) 631-660
53. Kirkpatrick S., Gelatt C.D., and Vecchi M.P. Optimization by simulated annealing. Science 220 (1983) 671-680
54. König R., and Dandekar T. Improving genetic algorithms for protein folding simulations by systematic crossover. BioSystems 50 (1999) 17-25
55. Kuntz I.D. Structure-based strategies for drug design and discovery. Science 257 (1992) 1078-1082
56. Lau K.F., and Dill K.A. Theory for protein mutability and biogenesis. Proc. Natl. Acad. Sci. USA 87 (1990) 638-642
57. Lawler E., and Wood D. Branch and bound methods: a survey. Oper. Res. 14 (1966) 699-719
58. Leach A.R. In: Lipkowitz K.B., and Boyd D.B. (Eds). A Survey of Methods for Searching the Conformational Space of Small and Medium-Sized Molecules vol. 2 (1991), VCH, New York
59. Levinthal C. Are there pathways to protein foldings. J. Chem. Phys. 65 (1968) 44-45
60. Lybrand T.P. Ligand-protein docking and rational drug design. Curr. Opin. Struct. Biol. 5 (1995) 224-228
61. Lucasius C.B., and Kateman G. Understanding and using genetic alghoritms. Part 2. Representation, configuration and hybridization. Chemom. Intell. Lab. Syst. 25 (1994) 99-146
62. Majeux N., Scarsi M., Apostolakis J., Ehrhardt C., and Caflisch A. Exhaustive docking of molecular fragments on protein binding sites with electrostatic solvation. Proteins. Struct. Funct. Genet. 37 (1999) 88-105
63. Majeux N., Scarsi M., and Caflisch A. Efficient electrostatic solvation model for protein-fragment docking. Proteins: Struct. Funct. Genet. 42 (2001) 256-268
64. Markley J.L. Two-dimensional nuclear magnetic resonance spectroscopy of proteins: an overview. Meth. Enzymol. 176 (1989) 12-64
65. Martin Y., Bures M., Dahaner E., DeLazzer J., Lico I., and Pavlik P. A fast approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists. J. Comput.-Aided Mol. Des. 7 (1993) 83-102
66. McGarrah D.B., and Judson R.S. Analysis of the genetic algorithm method of molecular conformation determination. J. Comput. Chem. 14 (1993) 1385-1395
67. Mekenyan O., Dimitrov D., Nikolova N., and Karabunarliev S. Conformational coverage by a genetic algorithm. J. Chem. Inf. Comput. Sci. 39 (1999) 997-1016
68. Metropolis N., Rosenbluth A., Rosenbluth A., Teller A., and Teller E. Equation of state calculations by fast computing machines. J. Chem. Phys. 21 (1953) 1087-1092
69. Meza J.C., Judson R.S., Faulkner T.R., and Treasurywala A.M. A comparison of a direct search method and a genetic algorithm for conformational searching. J. Comput. Chem. 17 (1996) 1142-1151
70. Mohamadi F., Richards N.J.G., Guida W.G., Liskamp R., Lipton M., Caufield C., Chang G., Hendrickson T., and Still W.C. MacroModel-an integrated software system for modeling organic and bioinorganic molecules using molecular mechanics. J. Comput. Chem. 11 (1990) 440-467
71. Morris G.M., Goodsell D.S., Halliday R.S., Huey R., Hart W.E., Belew R.K., and Olson A.J. Automated docking using a Lamarckian genetic algorithm and empirical binding free energy function. J. Comput. Chem. 19 (1998) 1639-1662
72. Muegge I., and Rarey M. Small molecule docking and scoring. In: Lipkowitz K.B., and Boyd D.B. (Eds). Chapter 1 in Reviews in Computational Chemistry Vol. 17 (2001), Wiley-VCH, New York
73. Nicholls A., and Hönig B. A rapid finite difference algorithm, utilizing successive over-relaxation to solve Poisson-Boltzmann equations. J. Comput. Chem. 12 (1991) 435-445
74. Nissink J.W.M., Murray C., Hartshorn M., Verdonk M.L., Cole J.C., and Taylor R. A new test set for validating predictions of protein-ligand interaction. Proteins: Struct. Funct. Genet. 49 (2002) 457-471
75. Oprea T.I., and Marshall G.R. Receptor based prediction of binding affinities. Perspect. Drug Disc. Des. 9-11 (1998) 35-61
76. Orr W.J.C. Statistical treatment of polymer solutions at infinite dilution. Trans. Faraday Soc. 43 (1947) 12-27
77. Oshiro C.M., Kuntz I.D., and Dixon J.S. Flexible ligand docking using a genetic algorithm. J. Comput.-Aided Mol. Des. 9 (1995) 113-130
78. Pak Y., and Wang S.J. Application of a molecular dynamics simulation method with a generalized effective potential to the flexible molecular docking problems. J. Phys. Chem. B. 104 (2000) 354-359
79. Patel Y., Gillet V.J., Bravi G., and Leach A.R. A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP. J. Comput-Aided Drug Des. 16 (2002) 653-681
80. Payne A.W.R., and Glen R.C. Molecular recognition using a binary genetic search algorithm. J. Mol. Graphics 11 (1993) 74-91
81. Pedersen J.T., and Moult J. Ab initio structure prediction for small polypeptides and protein fragments using genetic algorithms. Proteins: Struct. Funct. Genet. 23 (1995) 454-460
82. Pedersen J.T., and Moult J. Protein folding simulation with genetic algorithms and a detailed molecular description. J. Mol. Biol. 269 (1997) 249-269
83. Pearlman D.A., Case D.A., Caldwell J.W., Ross W.S., Cheatham III T.E., DeBolt S., Ferguson D., Seibel G., and Kollman P. AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput. Phys. Commun. 91 (1995) 1-41
84. Plackett R.L., and Burman J.P. The design of optimum multifactorial experiments. Biometrika 33 (1946) 305-325
85. Priestle J.P., and Paris C.G. Experimental techniques and data banks. In: Cohen N.C. (Ed). Chapter 5 in Guidebook on Molecular Modeling in Drug Design (1996), Academic Press, New York 139-149
86. Rarey M., Kramer B., Lengauer T., and Klebe G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol. 261 (1996) 470-489
87. Ring C.S., and Cohen F.E. Conformational sampling of loop structures using genetic algorithms. Isr. J. Chem. 34 (1994) 245-252
88. Rooman M.J., Kocher J.-P.A., and Wodak S.J. Prediction of protein backbone conformation based on seven structural assignements. J. Mol. Biol. 22 (1991) 1961-1979
89. Sanctuary B.C. Structure determination by NMR spectroscopy. In: Mannhold R., Kubinyi H., and Timmerman H. (Eds). Chapter 10 in Evolutionary Algorithms in Molecular Design. Methods and Principles in Medicinal Chemistry Vol. 8 (2000), Wiley-VCH, Weinheim
90. Sanderson P.N., Glen R.C., Payne A.W.R., Hudson B.D., Heide C., Tranter G.E., Doyle P.M., and Harris C.J. Characterization of the solution conformation of a cyclic RGD peptide analogue by NMR spectroscopy allied with a genetic algorithm approach and constrained molecular dynamics. Int. J. Pept. Protein Res. 43 (1994) 588-596
91. Solis F.J., and Wets J.B. Minimisation by random search techniques. Math. Oper. Res. 6 (1981) 19-30
92. Stewart J.J. MOPAC: a semiempirical molecular orbital program. J. Comput.-Aided Mol. Des. 4 (1990) 1-105
93. Sun S. Reduced representation model of protein structure prediction: statistical potential and genetic algorithms. Protein Sci. 2 (1993) 762-785
94. Sun S. A genetic algorithm that seeks native states of peptides and proteins. Biophys J. 69 (1995) 340-355
95. Sun S., Thomas P.D., and Dill K.A. A simple protein folding algorithm using a binary code and secondary structure constraints. Protein Engng 8 (1995) 769-778
96. Sun Z., Rao X., Peng L., and Xu D. Prediction of protein supersecondary structures based on the artificial neural network method. Protein Engng 10 (1997) 763-769
97. Sun Z., Xia X., Guo Q., and Xu D. Protein structure prediction in a 210-type lattice model: parameter optimization in the genetic algorithm using orthogonal arrays. J. Protein Chem. 18 (1998) 39-46
98. Taketomi H.H., and Ueda Y.G.N. Studies on protein folding, unfolding, and fluctuations by computer simulation. Int. J. Pept. Protein. Res. 7 (1975) 445-459
99. Taylor J.S., and Burnett R.M. DARWIN: a program for docking flexible molecules. Proteins: Struct. Funct. Genet. 41 (2000) 173-191
100. Taylor R.D., Jewsbury P.J., and Essex J.W. A review of protein-small molecule docking methods. J. Comput-Aided Mol. Des. 16 (2002) 151-166
101. Tuffery P., Etchebest C., Hazout S., and Laverly R. A new approach to the rapid determination of protein side-chain conformations. J. Biomol. Struct. Dyn. 8 (1991) 1267-1289
102. Tuffery P., Etchebest C., Hazout S., and Laverly R. A critical comparison of search algorithms applied to the optimization of protein side-chain conformations. J. Comput. Chem. 14 (1993) 790-798
103. Unger R., and Moult J. Genetic algorithms for protein folding simulations. J. Mol. Biol. 231 (1993) 75-81
104. Vedani A., Zbinden P., Snyder J.P., and Greenidge P.A. Pseudoreceptor modeling: the construction of three-dimensional receptor surrogates. J. Am. Chem. Soc. 117 (1995) 4987-4994
105. Verkhivker G., Appelt K., Freer S.T., and Villafranca J.E. Empirically free energy calculations of ligand-protein crystallographic complexes: I. Knowledge-based ligand-protein interaction potentials applied to the prediction of HIV-1 protease binding affinity. Prot. Engng 8 (1995) 677-691
106. Vieth M., Hirst J.D., Dominy B.N., Daigler H., and Brooks C.L. Assessing search strategies for flexible docking. J. Comput. Chem. 19 (1998) 1623-1631
107. Wallqvist A., Jerningan R.L., and Covell D.G. A preference-based free-energy parameterization of enzyme-inhibitor binding: application to HIV-1 protease inhibitor design. Protein Sci. 4 (1995) 1881-1903
108. Wang J., Hou T., Chen L., and Xu X. Automated docking of peptides and proteins by genetic algorithm. Chemom. Intell. Lab. Syst. 45 (1999) 281-286
109. Weiner S.J., Kollman P.A., Case D.A., Singh U.C., Ghio C., Alagona G., Profeta Jr. S., and Weiner P. A new force field for molecular mechanical simulation of nucleic acids and proteins. J. Am. Chem. Soc. 106 (1984) 765-784
110. Weiner S.J., Kollman P.A., Nguyen D.T., and Case D.A. New force field for simulations of proteins and nucleic acids. J. Comput. Chem. 7 (1986) 230-252
111. Wehrens R., Pretsch E., and Buydens L.M.C. Quality Criteria of Genetic Algorithms for Structure Optimization. J. Chem. Inf. Comput. Sci. 38 (1998) 151-157
112. Wehrens R., Pretsch E., and Buydens L.M.C. The quality of optimization by genetic algorithms. Anal. Chim. Acta 388 (1999) 265-271
113. Westhead D.R., Clark D.E., and Murray C.W. A comparison of heuristic search algorithms for molecular docking. J. Comput.-Aided Mol. Des. 11 (1997) 209-228