Chapter 28. Recent Developments in Molecular Diversity: Computational Approaches to Combinatorial Chemistry

Publisher Summary This chapter presents an overview of some computational approaches to combinatorial chemistry. The field of molecular diversity has changed rapidly to meet the assortment of chemical and biological approaches to combinatorial chemistry. The first “designed” combinatorial library combined elements of medicinal chemistry bias and diversity selections. The underlying mechanics and approaches used for this library design were encoded into a more formal computational approach to the analysis, design, and synthesis of combinatorial libraries. This new field of molecular diversity has expanded to match the rapid growth in high-throughput screening (HTS) and synthetic methods for the production of combinatorial libraries. In the early days of combinatorial chemistry, molecular diversity was seen as a different field distinct from chemical information and molecular modeling. The chapter summarizes the advances in the field of molecular diversity defined as the computational analysis of large numbers of chemical structures and related biological data. Concepts related to computational filters are elaborated and diversity metrics and molecular filters are described. An overview of virtual library searching and structure-based design is also presented.

[1]  John H. Van Drie.  An inequality for 3D database searching and its use in evaluating the treatment of conformational flexibility , 1996, J. Comput. Aided Mol. Des..

[2]  D C Spellmeyer,et al.  Discovery of nanomolar ligands for 7-transmembrane G-protein-coupled receptors from a diverse N-(substituted)glycine peptoid library. , 1994, Journal of medicinal chemistry.

[3]  I D Kuntz,et al.  Structure-based design and combinatorial chemistry yield low nanomolar inhibitors of cathepsin D. , 1997, Chemistry & biology.

[4]  J. Mason,et al.  New perspectives in lead generation II: Evaluating molecular diversity , 1996 .

[5]  D. E. Patterson,et al.  Designing Chemical Libraries for Lead Discovery , 1996 .

[6]  Johnz Willett.  Similarity and Clustering in Chemical Information Systems , 1987 .

[7]  W. DeGrado,et al.  Complementarity of Combinatorial Chemistry and Structure-Based Ligand Design: Application to the Discovery of Novel Inhibitors of Matrix Metalloproteinases , 1996 .

[8]  H. Kubinyi,et al.  A scoring scheme for discriminating between drugs and nondrugs. , 1998, Journal of medicinal chemistry.

[9]  Bohdan Waszkowycz,et al.  Targeted molecular diversity in drug discovery: Integration of structure-based design and combinatorial chemistry , 1998 .

[10]  Yvonne C. Martin,et al.  Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection , 1996, J. Chem. Inf. Comput. Sci..

[11]  Hualiang Jiang,et al.  A New Approach to Design Virtual Combinatorial Library with Genetic Algorithm Based on 3D Grid Property , 1998, J. Chem. Inf. Comput. Sci..

[12]  S. P. Fodor,et al.  Applications of combinatorial technologies to drug discovery. 1. Background and peptide combinatorial libraries. , 1994, Journal of medicinal chemistry.

[13]  X. Lewell,et al.  Drug-motif-based diverse monomer selection: method and application in combinatorial chemistry. , 1997, Journal of molecular graphics & modelling.

[14]  Amedeo Caflisch,et al.  Computational combinatorial chemistry for de novo ligand design: Review and assessment , 1995 .

[15]  T. Blundell.  Structure-based drug design. , 1996, Nature.

[16]  Yvonne C. Martin,et al.  The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding , 1997, J. Chem. Inf. Comput. Sci..

[17]  A. Ghose,et al.  A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. , 1999, Journal of combinatorial chemistry.

[18]  Eric J. Martin,et al.  Diverse Approaches to Combinatorial Library Design , 1998 .

[19]  Stephen D. Pickett,et al.  Diversity Profiling and Design Using 3D Pharmacophores: Pharmacophore-Derived Queries (PDQ) , 1996, J. Chem. Inf. Comput. Sci..

[20]  John H. Van Drie,et al.  Strategies for the determination of pharmacophoric 3D database queries , 1997, J. Comput. Aided Mol. Des..

[21]  Lori B. Pfahler,et al.  Lead Discovery Using Stochastic Cluster Analysis (SCA): A New Method for Clustering Structurally Similar Compounds , 1998, J. Chem. Inf. Comput. Sci..

[22]  Roger E. Critchlow,et al.  Beyond mere diversity: tailoring combinatorial libraries for drug discovery. , 1999, Journal of combinatorial chemistry.

[23]  K. Luthman,et al.  Evaluation of dynamic polar molecular surface area as predictor of drug absorption: comparison with other computational and experimental predictors. , 1998, Journal of medicinal chemistry.

[24]  James B. Dunbar,et al.  Enhancing the diversity of a corporate database using chemical database clustering and analysis , 1995, J. Comput. Aided Mol. Des..

[25]  H Matter,et al.  Random or rational design? Evaluation of diverse compound subsets from chemical structure databases. , 1998, Journal of medicinal chemistry.

[26]  Pravin Chaturvedi,et al.  Design principles for orally bioavailable drugs , 1996 .

[27]  Ian A. Watson,et al.  Experimental Designs for Selecting Molecules from Large Chemical Databases , 1997, J. Chem. Inf. Comput. Sci..

[28]  G. Bemis,et al.  The properties of known drugs. 1. Molecular frameworks. , 1996, Journal of medicinal chemistry.

[29]  David Chapman,et al.  The measurement of molecular diversity: A three-dimensional approach , 1996, J. Comput. Aided Mol. Des..

[30]  Peter Willett,et al.  Rapid Quantification of Molecular Diversity for Selective Database Acquisition , 1997, J. Chem. Inf. Comput. Sci..

[31]  Han Van De Waterbeemd.  Advanced Computer-Assisted Techniques in Drug Discover , 1994 .

[32]  Peter Willett,et al.  Similarity Searching and Clustering of Chemical-Structure Databases Using Molecular Property Data , 1994, J. Chem. Inf. Comput. Sci..

[33]  Rebecca Rawls.  BRESLOW'S DIALOGUE WITH NATURE , 1999 .

[34]  John Bradshaw,et al.  The Effectiveness of Reactant Pools for Generating Structurally-Diverse Combinatorial Libraries , 1997, J. Chem. Inf. Comput. Sci..

[35]  Ajay,et al.  Can we learn to distinguish between "drug-like" and "nondrug-like" molecules? , 1998, Journal of medicinal chemistry.

[36]  Y. Martin,et al.  Designing combinatorial library mixtures using a genetic algorithm. , 1997, Journal of medicinal chemistry.

[37]  Mark A. Murcko,et al.  Virtual screening : an overview , 1998 .

[38]  M. Desai,et al.  Recent advances in the generation of chemical diversity libraries , 1994 .

[39]  S. Schreiber,et al.  Protein Structure-Based Combinatorial Chemistry: Discovery of Non-Peptide Binding Elements to Src SH3 Domain , 1996 .

[40]  A. N. Jain,et al.  IcePick: a flexible surface-based system for molecular diversity. , 1999, Journal of medicinal chemistry.

[41]  D J Kyle,et al.  Computational screening of combinatorial libraries. , 1996, Bioorganic & medicinal chemistry.

[42]  Robert D Clark,et al.  Bioisosterism as a molecular diversity descriptor: steric fields of single "topomeric" conformers. , 1996, Journal of medicinal chemistry.

[43]  L M Amzel,et al.  Structure-based drug design. , 1998, Current opinion in biotechnology.

[44]  Michael M. Hann,et al.  RECAP-Retrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry , 1998, J. Chem. Inf. Comput. Sci..

[45]  Fionn Murtagh,et al.  Multidimensional clustering algorithms , 1985 .

[46]  S. P. Fodor,et al.  Applications of combinatorial technologies to drug discovery. 2. Combinatorial organic synthesis, library screening strategies, and future directions. , 1994, Journal of medicinal chemistry.

[47]  Dimitris K. Agrafiotis,et al.  Stochastic Algorithms for Maximizing Molecular Diversity , 1997, J. Chem. Inf. Comput. Sci..

[48]  John M. Barnard,et al.  Clustering of chemical structures on the basis of two-dimensional similarity measures , 1992, J. Chem. Inf. Comput. Sci..

[49]  Gobbi,et al.  Genetic optimization of combinatorial libraries , 1998, Biotechnology and bioengineering.

[50]  Y. Martin,et al.  Computational methods in molecular diversity and combinatorial chemistry. , 1998, Current opinion in chemical biology.

[51]  Andrew Smellie,et al.  Identification of Common Functional Configurations Among Molecules , 1996, J. Chem. Inf. Comput. Sci..

[52]  J M Blaney,et al.  Computational approaches for combinatorial library design and molecular diversity analysis. , 1997, Current opinion in chemical biology.

[53]  D C Spellmeyer,et al.  Measuring diversity: experimental design of combinatorial libraries for drug discovery. , 1995, Journal of medicinal chemistry.

[54]  Robert D. Clark,et al.  OptiSim: An Extended Dissimilarity Selection Method for Finding Diverse Representative Subsets , 1997, J. Chem. Inf. Comput. Sci..

[55]  J. Spurlino,et al.  Serendipity meets precision: the integration of structure-based drug design and combinatorial chemistry for efficient drug discovery. , 1997, Structure.

[56]  Paul W. Finn,et al.  Computer-based screening of compound databases for the identification of novel leads , 1996 .