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Drug research and discovery are of critical importance in human health care. Computational approaches for drug lead discovery and optimization have proven successful in many recent research programs. These methods have grown in their effectiveness not only because of improved understanding of the basic science - the biological events and molecular interactions that define a target for therapeutic intervention - but also because of advances in algorithms, representations, and mathematical procedures for studying such processes. This volume surveys some of those advances. A broad landscape of high-profile topics in computer-assisted molecular design (CAMD) directed to drug design are included. Subject areas represented in the volume include receptor-based applications such as binding energy approximations, molecular docking, and de novo design; non-receptor-based applications such as molecular similarity; molecular dynamics simulations; solvation and partitioning of a solute between aqueous and nonpolar media; graph theory; non-linear multidimensional optimization, processing of information obtained from simulation studies, global optimization and search strategies, and performance enhancement through parallel computing.
Inhaltsverzeichnis
Panel Discussions.- Important current problems in drug design that may be computationally tractable.- New problems that should be addressed in the next ten years.- Molecular Properties.- Matching of chemical and biological structures using subgraph and maximal common subgraph isomorphism algorithms.- Molecular similarity.- Modeling the effect of solvation on structure, reactivity, and partitioning of organic solutes: Utility in drug design.- Cell-based methods for sampling in high-dimensional spaces.- A preliminary multiobjective analysis of the chemotherapeutic benefits of hairpin-linked polyamides.- Receptor-Based Modeling.- Using structural information for the creative design of molecules.- GrowMol, a de novo computer program, and its application to thermolysin and pepsin: Results of the design and synthesis of a novel inhibitor.- Deducing objective site models by mixed integer programming.- Numerical Methods.- Molecular dynamics information extraction.- Ionic charging free energies using Ewald summation.- Genetic function approximation: Evolutionary construction of novel, interpretable, nonlinear models of experimental data.- Applications of distributed computing to conformational searches.
