Computational Methods for Protein Folding, Volume 120

Since the first attempts to model proteins on a computer began almost thirty years ago, our understanding of protein structure and dynamics has dramatically increased. Spectroscopic measurement techniques continue to improve in resolution and sensitivity, allowing a wealth of information to be obtained with regard to the kinetics of protein folding and unfolding, and complementing the detailed structural picture of the folded state. Concurrently, algorithms, software, and computational hardware have progressed to the point where both structural and kinetic problems may be studied with a fair degree of realism. Despite these advances, many major challenges remain in understanding protein folding at both the conceptual and practical levels. Computational Methods for Protein Folding seeks to illuminate recent advances in computational modeling of protein folding in a way that will be useful to physicists, chemists, and chemical physicists. Covering a broad spectrum of computational methods and practices culled from a variety of research fields, the editors present a full range of models that, together, provide a thorough and current description of all aspects of protein folding. A valuable resource for both students and professionals in the field, the book will be of value both as a cutting-edge overview of existing information and as a catalyst for inspiring new studies. Computational Methods for Protein Folding is the 120th volume in the acclaimed series Advances in Chemical Physics, a compilation of scholarly works dedicated to the dissemination of contemporary advances in chemical physics, edited by Nobel Prize-winner Ilya Prigogine. Aaron R. Dinner, Sung-Sau-So, and Martin Karplus Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima -- Jaroslaw Meller, Ron Elber Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima -- Jaroslaw Meller, Ron Elber -- Jeffrey Skolnick and Andrzej Kolinski Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima -- Jaroslaw Meller, Ron Elber -- Jeffrey Skolnick and Andrzej Kolinski -- Pierre-Jean L'Heureux ... [et al.] Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima -- Jaroslaw Meller, Ron Elber -- Jeffrey Skolnick and Andrzej Kolinski -- Pierre-Jean L'Heureux ... [et al.] -- Volker A. Eyrich, Daron M. Standley, and Richard A. Freisner Aaron R. Dinner, Sung-Sau-So, and Martin Karplus -- D. Thirumalai, D.K. Klimov, and R.I. Dima -- Jaroslaw Meller, Ron Elber -- Jeffrey Skolnick and Andrzej Kolinski -- Pierre-Jean L'Heureux ... [et al.] -- Volker A. Eyrich, Daron M. Standley, and Richard A. Freisner -- John L. Klepeis ... [et al.] Aaron R. Dinner, Sung-Sau-So, and Martin Karplus-- D. Thirumalai, D.K. Klimov, and R.I. Dima-- Jaroslaw Meller, Ron Elber-- Jeffrey Skolnick and Andrzej Kolinski-- Pierre-Jean L'Heureux ... [et al.]-- Volker A. Eyrich, Daron M. Standley, and Richard A. Freisner-- John L. Klepeis ... [et al.]-- Anders Wallqvist ... [et al.] Statistical analysis of protein folding kinetics. (Aaron, R. Dinner, Sung-Sau-So, and Martin Karplus). Insights into specific problems in protein folding using simple concepts. (D. Thirumalai. D. K. Klimov, and R. I. Dima). Protein recognition by sequence-to-structure fitness: bridging efficiency and capacity of threading models. (Jaroslaw Meller and Ron Elber). A unified approach to the prediction of protein structure and function.( Jefferey Skolnick and Andrzej Kolinski). Knowledge-based prediction of protein tertiary structure. (Pierre-Jean L'Heurex, Benoit Cromp, Éric Martineau, and Jhon Gunn). AB initio protein structure prediction using a side-dependent tertiary folding potential. (Volker A. Eyrich, Daron M. Standley, and Richard A. Friesner). Deterministic global optimization and AB initio approaches for the structure prediction of polypeptides, dynamics of protein folding, and protein-protein interactions. (John L. Kepeis, Heather D. Schafroth, Karl M. Westerberg, and Christodouls A. Floudas). Detecting native protein folds among large decoy sites with the OPLS all-atom potentiasl and the surface generalized born solvent model. ( Anders Wallqvist, Emilio Gallicchio, Anthony K. Felts, and Ronald M. Levy) Statistical Analysis Of Protein Folding Kinetics / Aaron R. Dinner, Sung-sau-so, And Martin Karplus -- Insights Into Specific Problems In Protein Folding Using Simple Concepts / D. Thirumalai, D.k. Klimov, And R.i. Dima -- Protein Recognition By Sequence-to-structure Fitness : Bridging Efficiency And Capacity Of Threading Models / Jaroslaw Meller, Ron Elber -- A Unified Approach To The Prediction Of Protein Structure And Function / Jeffrey Skolnick And Andrzej Kolinski -- Knowledge-based Prediction Of Protein Tertiary Structure / Pierre-jean L'heureux [and Others] -- Ab Initio Protein Structure Prediction Using A Size-dependent Tertiary Folding Potential / Volker A. Eyrich, Daron M. Standley, And Richard A. Freisner -- Deterministic Global Optimization And Ab Initio Approaches For The Structure Prediction Of Polypeptides, Dynamics Of Protein Folding, And Protein-protein Interactions / John L. Klepeis [and Others] -- Detecting Native Protein Folds Among Large Decoy Sites With The Opls All-atom Potential And The Surface Generalized Born Solvent Model / Anders Wallqvist [and Others]. Edited By Richard A. Friesner ; Series Editors I. Prigogine And Stuart A. Rice. Includes Bibliographical References And Indexes. Experimental and theoretical studies have led to the emergence of a unified general mechanism for protein folding that serves as a framework for the design and interpretation of research in this area [1]. "" ... Should prove to be an excellent addition to the collection of reference texts held by scientists ... "" (Journal of the American Chemical Society, Vol. 124, No. 41, 2002)