PRO_LIGAND: An approach to de novo molecular design. 3. A genetic algorithm for structure refinement

SummaryRecently, the development of computer programs which permit the de novo design of molecular structures satisfying a set of steric and chemical constraints has become a burgeoning area of research and many operational systems have been reported in the literature. Experience with PRO_LIGAND—the de novo design methodology embodied in our in-house molecular design and simulation system PRO-METHEUS—has suggested that the addition of a genetic algorithm (GA) structure refinement procedure can ‘add value’ to an already useful tool. Starting with the set of designed molecules as an initial population, the GA can combine features from both high- and low-scoring structures and, over a number of generations, produce individuals of better score than any of the starting structures. This paper describes how we have implemented such a procedure and demonstrates its efficacy in improving two sets of molecules generated by different de novo design projects.

[1]  M Karplus,et al.  HOOK: A program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site , 1994, Proteins.

[2]  Hans-Joachim Böhm,et al.  LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads , 1992, J. Comput. Aided Mol. Des..

[3]  Kenneth M. Merz,et al.  The application of the genetic algorithm to the minimization of potential energy functions , 1993, J. Glob. Optim..

[4]  R C Glen,et al.  Molecular recognition using a binary genetic search algorithm. , 1993, Journal of molecular graphics.

[5]  Valerie J. Gillet,et al.  SPROUT: A program for structure generation , 1993, J. Comput. Aided Mol. Des..

[6]  G. Marshall.  Computer-aided drug design. , 1987, Annual review of pharmacology and toxicology.

[7]  G. Klebe.  The use of composite crystal-field environments in molecular recognition and the de novo design of protein ligands. , 1994, Journal of molecular biology.

[8]  Y. Martin.  Computer-assisted rational drug design. , 1991, Methods in enzymology.

[9]  P Argos,et al.  Folding the main chain of small proteins with the genetic algorithm. , 1994, Journal of molecular biology.

[10]  R. Leardi.  Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection , 1994 .

[11]  J. S. Dixon,et al.  Computer-aided drug design: getting the best results. , 1992, Trends in biotechnology.

[12]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[13]  Richard S. Judson,et al.  Analysis of the genetic algorithm method of molecular conformation determination , 1993, J. Comput. Chem..

[14]  Richard S. Judson,et al.  Conformational searching methods for small molecules. II. Genetic algorithm approach , 1993, J. Comput. Chem..

[15]  C. Wermuth,et al.  Trends in QSAR and Molecular Modelling 92 , 1993 .

[16]  M. Karplus,et al.  Functionality maps of binding sites: A multiple copy simultaneous search method , 1991, Proteins.

[17]  Barry Robson,et al.  PRO_LIGAND: An approach to de novo molecular design. 1. Application to the design of organic molecules , 1995, J. Comput. Aided Mol. Des..

[18]  K. Humbel,et al.  Chemical Applications of Topology and Graph Theory, R.B. King (Ed.). Elsevier Science Publishers, Amsterdam (1983), (ISBN 0-444-42244-7). XII + 494 p. Price Dfl. 275.00 , 1985 .

[19]  Hans-Joachim Böhm,et al.  The computer program LUDI: A new method for the de novo design of enzyme inhibitors , 1992, J. Comput. Aided Mol. Des..

[20]  Gareth Jones,et al.  Pharmacophoric pattern matching in files of three-dimensional chemical structures: Comparison of conformational-searching algorithms for flexible searching , 1994, J. Chem. Inf. Comput. Sci..

[21]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[22]  Andrew R. Leach,et al.  A ring‐bracing approach to computer‐assisted ligand design , 1994, J. Comput. Chem..

[23]  N. Cohen,et al.  The NEWLEAD program: a new method for the design of candidate structures from pharmacophoric hypotheses. , 1993, Journal of medicinal chemistry.

[24]  C. B. Lucasius,et al.  Understanding and using genetic algorithms Part 1. Concepts, properties and context , 1993 .

[25]  Chris M. W. Ho,et al.  SPLICE: A program to assemble partial query solutions from three-dimensional database searches into novel ligands , 1993, J. Comput. Aided Mol. Des..

[26]  R C Glen,et al.  Characterisation of the solution conformation of a cyclic RGD peptide analogue by NMR spectroscopy allied with a genetic algorithm approach and constrained molecular dynamics. , 2009, International journal of peptide and protein research.

[27]  M. Murcko,et al.  GroupBuild: a fragment-based method for de novo drug design. , 1993, Journal of medicinal chemistry.

[28]  R. Judson.  Teaching polymers to fold , 1992 .

[29]  Joseph B. Moon,et al.  Recent advances in de novo molecular design , 1993 .

[30]  H. L. Morgan.  The Generation of a Unique Machine Description for Chemical Structures-A Technique Developed at Chemical Abstracts Service. , 1965 .

[31]  P. Argos,et al.  Potential of genetic algorithms in protein folding and protein engineering simulations. , 1992, Protein engineering.

[32]  David T. Jones,et al.  De novo protein design using pairwise potentials and a genetic algorithm , 1994, Protein science : a publication of the Protein Society.

[33]  A Itai,et al.  Confirmation of usefulness of a structure construction program based on three-dimensional receptor structure for rational lead generation. , 1993, Journal of medicinal chemistry.

[34]  W. Howe,et al.  Computer design of bioactive molecules: A method for receptor‐based de novo ligand design , 1991, Proteins.

[35]  Juan C. Meza,et al.  Do intelligent configuration search techniques outperform random search for large molecules , 1992 .

[36]  D. Walters,et al.  Genetically evolved receptor models: a computational approach to construction of receptor models. , 1994, Journal of medicinal chemistry.

[37]  Andrew R. Leach,et al.  Automated molecular design: A new fragment-joining algorithm , 1994, J. Comput. Aided Mol. Des..

[38]  S. Sun,et al.  Reduced representation model of protein structure prediction: Statistical potential and genetic algorithms , 1993, Protein science : a publication of the Protein Society.

[39]  Valerie J. Gillet,et al.  SPROUT: Recent developments in the de novo design of molecules , 1994, J. Chem. Inf. Comput. Sci..

[40]  R Unger,et al.  Genetic algorithms for protein folding simulations. , 1992, Journal of molecular biology.

[41]  Anton J. Hopfinger,et al.  Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships , 1994, J. Chem. Inf. Comput. Sci..

[42]  Akiko Itai,et al.  Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation , 1991 .

[43]  G. B. Wetherill,et al.  Hitch-hiker's guide to genetic algorithms , 1993 .

[44]  David A. Pearlman,et al.  CONCEPTS: New dynamic algorithm for de novo drug suggestion , 1993, J. Comput. Chem..

[45]  Pierre Tufféry,et al.  A critical comparison of search algorithms applied to the optimization of protein side‐chain conformations , 1993, J. Comput. Chem..

[46]  A. Treasurywala,et al.  A genetic algorithm based method for docking flexible molecules , 1994 .

[47]  R. Ruthen.  The Frustrations of a Quark Hunter , 1992 .

[48]  C. B. Lucasius,et al.  Conformational analysis of a dinucleotide photodimer with the aid of the genetic algorithm , 1992, Biopolymers.

[49]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[50]  M. Karplus,et al.  Multiple copy simultaneous search and construction of ligands in binding sites: application to inhibitors of HIV-1 aspartic proteinase. , 1993, Journal of medicinal chemistry.

[51]  A C May,et al.  Protein structure comparisons using a combination of a genetic algorithm, dynamic programming and least-squares minimization. , 1994, Protein engineering.

[52]  Gerrit Kateman,et al.  CFIT - A GENETIC ALGORITHM FOR SURVIVAL OF THE FITTING , 1993 .

[53]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[54]  D. E. Clark,et al.  PRO_LIGAND: an approach to de novo molecular design. 2. Design of novel molecules from molecular field analysis (MFA) models and pharmacophores. , 1994, Journal of medicinal chemistry.

[55]  Mark A. Murcko,et al.  GenStar: A method for de novo drug design , 1993, J. Comput. Aided Mol. Des..

[56]  Conrad C. Huang,et al.  Automated site-directed drug design using molecular lattices , 1992 .

[57]  Ernö Pretsch,et al.  Application of genetic algorithms in molecular modeling , 1994, J. Comput. Chem..