Challenges and prospects for computational aids to molecular diversity

Although workers have devised many usable strategies, a validated method for the computational analysis and optimization of molecular diversity in compound collections or combinatorial libraries remains a challenge. Even the most ambitious programs consider less than 1:1039 of all possible compounds. The various methods need to be validated against experimental data and compared with each other, which might require sharing the structures and biological activities of 105–106 molecules. We need molecular descriptors that more accurately reflect the biological properties of compounds: this will probably entail designing a strategy to realistically include the properties of the multiple conformers, tautomers, and ionization states of molecules. For true computer generation of diverse synthesizable compounds, we need a whole new generation of programs that organize the knowledge of synthetic organic chemistry. Additionally, if the goal is to design molecules to fit a macromolecular target of known 3D structure, we also need improved methods for estimating ligand affinity.

[1]  Johann Gasteiger,et al.  Similarity concepts for the planning of organic reactions and syntheses , 1992, J. Chem. Inf. Comput. Sci..

[2]  Oleg A. Raevsky,et al.  Complete Thermodynamic Description of H‐Bonding in the Framework of Multiplicative Approach , 1992 .

[3]  Edward P. Jaeger,et al.  Application of Genetic Algorithms to Combinatorial Synthesis: A Computational Approach to Lead Identification and Lead Optimization†,∇ , 1996 .

[4]  Y. Martin,et al.  Quantitative drug design , 1978 .

[5]  Hans-Joachim Böhm,et al.  Towards the automatic design of synthetically accessible protein ligands: Peptides, amides and peptidomimetics , 1996, J. Comput. Aided Mol. Des..

[6]  G. Klopman.  Artificial intelligence approach to structure-activity studies. Computer automated structure evaluation of biological activity of organic molecules , 1985 .

[7]  J. Ellman,et al.  Chapter 31. Solid-Phase Synthesis: Applications to Combinatorial Libraries , 1996 .

[8]  Vijay K. Gombar,et al.  Assessment of n-Octanol/Water Partition Coefficient: When Is the Assessment Reliable? , 1996, J. Chem. Inf. Comput. Sci..

[9]  Irwin D. Kuntz,et al.  A fast and efficient method for 2D and 3D molecular shape description , 1992, J. Comput. Aided Mol. Des..

[10]  Robert D Clark,et al.  Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors. , 1996, Journal of medicinal chemistry.

[11]  Y. Martin,et al.  3D database searching in drug design. , 1992, Journal of medicinal chemistry.

[12]  W. T. Wipke,et al.  Computer-Assisted Organic Synthesis , 1977 .

[13]  Robert P. Sheridan,et al.  Using a Genetic Algorithm To Suggest Combinatorial Libraries , 1995, J. Chem. Inf. Comput. Sci..

[14]  Johann Gasteiger,et al.  A Collection of Computer Methods for Synthesis Design and Reaction Prediction , 2010 .

[15]  Peter Willett,et al.  The Extent of the Relationship between the Graph-Theoretical and the Geometrical Shape Coefficients of Chemical Compounds , 1995, J. Chem. Inf. Comput. Sci..

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

[17]  Robert D. Brown.  Descriptors for diversity analysis , 1996 .

[18]  David Weininger,et al.  CHUCKLES: A method for representing and searching peptide and peptoid sequences on both monomer and atomic levels , 1994, J. Chem. Inf. Comput. Sci..

[19]  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..

[20]  Ramaswamy Nilakantan,et al.  New method for rapid characterization of molecular shapes: applications in drug design , 1993, J. Chem. Inf. Comput. Sci..

[21]  W. G. Richards,et al.  Rapid evaluation of shape similarity using Gaussian functions , 1993, J. Chem. Inf. Comput. Sci..

[22]  Robin Taylor,et al.  Simulation Analysis of Experimental Design Strategies for Screening Random Compounds as Potential New Drugs and Agrochemicals , 1995, J. Chem. Inf. Comput. Sci..

[23]  John M. Barnard,et al.  Techniques for Generating Descriptive Fingerprints in Combinatorial Libraries , 1997, J. Chem. Inf. Comput. Sci..

[24]  Dinesh V. Patel,et al.  Strategy and Tactics in Combinatorial Organic Synthesis. Applications to Drug Discovery , 1996 .

[25]  Peter Willett,et al.  Similarity searching in files of three-dimensional chemical structures: Comparison of fragment-based measures of shape similarity , 1994, J. Chem. Inf. Comput. Sci..

[26]  E. Corey,et al.  Computer‐assisted synthetic analysis. Quantitative assessment of transform utilities , 1992 .

[27]  Gilles Klopman,et al.  Quantitative structure-agonist activity relationship of capsaicin analogues , 1995, J. Comput. Aided Mol. Des..

[28]  Rainer Moll,et al.  Reaction Databases and Synthesis Planning-Combined Application and Synergetic Effects , 1997, J. Chem. Inf. Comput. Sci..

[29]  Robert P. Sheridan,et al.  Chemical Similarity Using Geometric Atom Pair Descriptors , 1996, J. Chem. Inf. Comput. Sci..

[30]  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..

[31]  M. Schroeder,et al.  "Diversomers": an approach to nonpeptide, nonoligomeric chemical diversity. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[32]  David Weininger,et al.  CHORTLES: A Method for Representing Oligomeric and Template-Based Mixtures , 1995, J. Chem. Inf. Comput. Sci..

[33]  Johann Gasteiger,et al.  Computer‐Assisted Planning of Organic Syntheses: The Second Generation of Programs , 1996 .

[34]  David A. Pensak,et al.  LHASA—Logic and Heuristics Applied to Synthetic Analysis , 1977 .

[35]  I. Kuntz.  Structure-Based Strategies for Drug Design and Discovery , 1992, Science.

[36]  P Willett,et al.  Searching for pharmacophoric patterns in databases of three‐dimensional chemical structures , 1995, Journal of molecular recognition : JMR.

[37]  P. Hajduk,et al.  Discovering High-Affinity Ligands for Proteins: SAR by NMR , 1996, Science.

[38]  Johann Gasteiger,et al.  The comparison of geometric and electronic properties of molecular surfaces by neural networks: Application to the analysis of corticosteroid-binding globulin activity of steroids , 1996, J. Comput. Aided Mol. Des..

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

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

[41]  Philip N. Judson,et al.  Starting material oriented retrosynthetic analysis in the LHASA program. 1. General description , 1992, J. Chem. Inf. Comput. Sci..

[42]  W. Graham Richards,et al.  Similarity of molecular shape , 1991, J. Comput. Aided Mol. Des..

[43]  George W. A. Milne,et al.  Discovery of novel, non-peptide HIV-1 protease inhibitors by pharmacophore searching. , 1996, Journal of medicinal chemistry.

[44]  A. N. Jain,et al.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites. , 1996, Chemistry & biology.

[45]  Martin A. Ott,et al.  Computer tools for reaction retrieval and synthesis planning in organic chemistry. A brief review of their history, methods, and programs , 1992 .

[46]  J. Cherfils,et al.  Molecular docking programs successfully predict the binding of a β-lactamase inhibitory protein to TEM-1 β-lactamase , 1996, Nature Structural Biology.

[47]  Klaus Gubernator,et al.  Optimization of the Biological Activity of Combinatorial Compound Libraries by a Genetic Algorithm , 1995 .

[48]  D. Cosgrove,et al.  BOOMSLANG: a program for combinatorial structure generation. , 1996, Journal of molecular graphics.

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

[50]  Wendy A. Warr,et al.  Commercial software systems for diversity analysis , 1996 .

[51]  W. Todd Wipke,et al.  Artificial intelligence in organic synthesis. SST: starting material selection strategies. An application of superstructure search , 1984, J. Chem. Inf. Comput. Sci..

[52]  Robert P. Sheridan,et al.  Chemical Similarity Using Physiochemical Property Descriptors , 1996, J. Chem. Inf. Comput. Sci..

[53]  Michael H. Abraham,et al.  Hydrogen bonding. Part 9. Solute proton donor and proton acceptor scales for use in drug design , 1989 .