This text traces developments in rational drug discovery and combinatorial library design with contributions from 50 leading scientists in academia and industry who offer coverage of basic principles, design strategies, methodologies, software tools and algorithms, and applications. It outlines the fundamentals of pharmacophore modelling and 3D Quantitative Structure-Activity Relationships (QSAR), classical QSAR, and target protein structure-based design methods.
Introduction - library design concepts and implementation strategies. Part 1 Design principles: fundamentals of pharmacophore modelling for combinatorial chemistry; quantitative structure-activity relationships (QSAR) - versatile tool in drug design; quantitative structure-activity relationships (QSAR) - a review of 3D QSAR; binding energy landscapes of ligand-protein complexes and molecular docking - principles, methods and validation experiments; fast continuum electrostatics methods for structure-based ligand design; quo vadis, scoring functions? toward an integrated pharmacokinetic and binding affinity prediction framework. Part 2 Current methods and software tools: knowledge-based approaches for the design of small molecule libraries for drug discovery; drug-likeness profiles of chemical libraries; tools for designing diverse, drug-like, cost-effective combinatorial libraries; relative and asbolute diversity analysis of combinatorial libraries; rational combinatorial library design and database mining using inverse QSAR approach; dissimilarity-based compound selection for library design; pharmacore-based approaches to combinatorial library design; high throughput conformational sampling and fuzzy similarity metrics - a novel approach to similarity searching and focused combinatorial library design and its role in the drug discovery laboratory. Part 3 Applications: applications of cell-based diversity methods to combinatorial library design; structure based combinatorial library design and screening - applications of the multiple copy simultaneous search method; genetic algorithm-directed lead generation; enhancement of the drug discovery process by integration of structure-based drug design and combinatorial synthesis; design of structrural combinatorial libraries that mimic biological motifs.