The Protein Folding Problem and Tertiary Structure Prediction

Two of the most controversial unsolved problems in molecular biology, the protein folding problem and tertiary structure prediction are detailed in this exciting look into the forefront of biotechnology. The techniques illustrated in this volume will serve as essential tools to guide the design of new protein based drugs, as well as the field of protein engineering. It is written by the world's top experts in protein folding and conformation, and includes the latest developments in lattice models, numerical methods, tertiary structure prediction, potential functions, and much more. The editors have provided a wide scope of topics and techniques, including: a review of protein folding; the dead end elimination problem; applications of neural networks in molecular sequence prediction; molecular docking of flexible ligands; knowledge-based predictions of protein structure; and future directions in this rapidly developing field. Discover the most promising new techniques for unraveling the mysteries of protein folding and structure. This collection of articles should be required reading for all molecular biologists, pharmaceutical chemists, and protein chemists in biotechnology.

Table of Contents:
Preface, Kenneth M. Merz, Jr. and Scott M. Le Grand; modeling side chains in peptides and proteins with the locally enhanced sampling / simulated annealling method, Adrian Roitberg and Ron Elber; conformation searching using simulated annealing, Stephen R. Wilson and Weih Cui; multiple-start Monte Carlo docking of flexible ligands, Trevor N. Hart and Randy J. Read; application of the genetic algorithm to tertiary structure prediction, Scott M. Le Grand and Kenneth M. Merz, Jr; conformational search and protein folding, Robert Bruccoleri; building protein folds using distance geometry - towards a general modeling and prediction method, William R. Taylor and Andras Aszodi; molecular dynamics studies of protein folding, Amadeo Caflisch and Martin Karplus; contact potential for global identification of correct protein folding, Gordon M. Crippen and Vladimir N. Maiorov; neural networks for molecular sequence classification, Cathy H. Wu; the "dead end elimination" theorem as a new approach to the side chain packing problem, Johan Desmet, Marc De Maeyer, and Ignace Lasters; short structural motifs - definition, identification, and applications, Ron Unger; in search of protein folds, Manfred J. Sippl, Sabine Weitckus, and Hannes Flockner; an adaptive branch-and-bound minimisation method based on dynamic programming, Sandor Vajda and Charles Delisi; computational complexity, protein structure prediction, and the levinthal paradox, J. Thomas Ngo, Joe Marks, Martin Karplus; toward quantitative protein structure prediction, Teresa Head-Gordon; the role of interior side-chain packing in protein folding and stability, James H. Hurley.