- Shopping Bag ( 0 items )
Other sellers (Hardcover)
-
All (10) from $71.61
-
New (8) from $71.61
-
Used (2) from $71.61
More About This Textbook
Overview
Multiscale Approaches to Protein Modeling is a comprehensive review of the most advanced multiscale methods for protein structure prediction, computational studies of protein dynamics, folding mechanisms and macromolecular interactions. The approaches span a wide range of the levels of coarse-grained representations, various sampling techniques and variety of applications to biomedical and biophysical problems.
Thanks to enormous progress in sequencing of genomic data, we presently know millions of protein sequences. At the same time, the number of experimentally solved protein structures is much smaller, ca. 60,000. This is because of the large cost of structure determination. Thus, theoretical in silico prediction of protein structures and dynamics is essential for understanding the molecular basis of drug action, metabolic and signaling pathways in living cells, designing new technologies in the life science and material sciences. Unfortunately, a "brute force" approach remains impractical. Folding of a typical protein (in vivo or in vitro) takes milliseconds to minutes, while state-of-the-art all-atom molecular mechanics simulations of protein systems can cover only a time period range of nanosecond to microseconds. This is the reason for the enormous progress in development of various mutiscale modeling techniques, applied to protein structure prediction, modeling of protein dynamics and folding pathways, in silico protein engineering, model-aided interpretation of experimental data, modeling of macromolecular assemblies and theoretical studies of protein thermodynamics. Coarse-graining of the proteins' conformational space is a common feature of all these approaches, although the details and the underlying physical models span a very broad spectrum.
Product Details
Table of Contents
1 Lattice Polymers and Protein Models Andrzej Kolinski 1
2 Multiscale Protein and Peptide Docking Mateusz Kurcinski Michal Jamroz Andrzej Kolinski 21
3 Coarse-Grained Models of Proteins: Theory and Applications Cezary Czaplewski Adam Liwo Mariusz Makowski Stanislaw Oldziej Harold A. Scheraga 35
4 Conformational Sampling in Structure Prediction and Refinement with Atomistic and Coarse-Gained Models Michael Feig Srinivasa M. Gopal Kanagasabai Vadivel Andrew Stumpff-Kane 85
5 Effective All-Atom Potentials for Proteins Anders Iibäck Sandipan Mohanty 111
6 Statistical Contact Potentials in Protein Coarse-Grained Modeling: From Pair to Multi-body Potentials Sumudu P. Leelananda Yaping Feng Pawel Gniewek Andrzej Kloczkowski Robert L. Jernigan 127
7 Bridging the Atomic and Coarse-Grained Descriptions of Collective Motions in Proteins Vincenzo Carnevale Cristian Micheletti Francesco Pontiggia Raffaello Potestio 159
8 Structure-Based Models of Biomolecules: Stretching of Proteins, Dynamics of Knots, Hydrodynamic Effects, and Indentation of Virus Capsids Marek Cieplak Joanna I. Sulkowska 179
9 Sampling Protein Energy Landscapes - The Quest for Efficient Algorithms Ulrich H. E. Hansmann 209
10 Protein Structure Prediction: From Recognition of Matches with Known Structures to Recombination of Fragments Michal J. Gajda Marcin Pawlowski Janusz M. Bujnicki 231
11 Genome-Wide Protein Structure Prediction Srayanta Mukherjee Andras Szilagyi Ambrish Roy Yang Zhang 255
12 Multiscale Approach to Protein Folding Dynamics Sebastian Kmiecik Michal Jamroz Andrzej Kolinski 281
13 Error Estimation of Template-Based Protein Structure Models Daisuke Kihara Yifeng David Yang Hao Chen 295
14 Evaluation of Protein Structure Prediction Methods: Issues and Strategics Anna Tramontano Domenico Cozzetto 315
Index 341