Literature DB >> 10322208

New Monte Carlo algorithms for protein folding.

U H Hansmann1, Y Okamoto.   

Abstract

Over the past three decades, a number of powerful simulation algorithms have been introduced to the protein folding problem. For many years, the emphasis has been placed on how to both overcome the multiple minima problem and find the conformation with the global minimum potential energy. Since the new view of the protein folding mechanism (based on the free energy landscape of the protein system) arose in the past few years, however, it is now of interest to obtain a global knowledge of the phase space, including the intermediate and denatured states of proteins. Monte Carlo methods have proved especially valuable for these purposes. As well as new, powerful optimization techniques, novel algorithms that can sample much a wider phase space than conventional methods have been established.

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Year:  1999        PMID: 10322208     DOI: 10.1016/S0959-440X(99)80025-6

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  40 in total

1.  A minimal physically realistic protein-like lattice model: designing an energy landscape that ensures all-or-none folding to a unique native state.

Authors:  Piotr Pokarowski; Andrzej Kolinski; Jeffrey Skolnick
Journal:  Biophys J       Date:  2003-03       Impact factor: 4.033

2.  MC-PHS: a Monte Carlo implementation of the primary hydration shell for protein folding and design.

Authors:  Alex Kentsis; Mihaly Mezei; Roman Osman
Journal:  Biophys J       Date:  2003-02       Impact factor: 4.033

3.  Engineering teams up with computer-simulation and visualization tools to probe biomolecular mechanisms.

Authors:  Tamar Schlick
Journal:  Biophys J       Date:  2003-07       Impact factor: 4.033

4.  Database-derived potentials dependent on protein size for in silico folding and design.

Authors:  Yves Dehouck; Dimitri Gilis; Marianne Rooman
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

5.  Self-assembly of the ionic peptide EAK16: the effect of charge distributions on self-assembly.

Authors:  S Jun; Y Hong; H Imamura; B-Y Ha; J Bechhoefer; P Chen
Journal:  Biophys J       Date:  2004-08       Impact factor: 4.033

6.  Oligomerization of amyloid Abeta16-22 peptides using hydrogen bonds and hydrophobicity forces.

Authors:  Giorgio Favrin; Anders Irbäck; Sandipan Mohanty
Journal:  Biophys J       Date:  2004-09-17       Impact factor: 4.033

7.  Protein fragment reconstruction using various modeling techniques.

Authors:  Michal Boniecki; Piotr Rotkiewicz; Jeffrey Skolnick; Andrzej Kolinski
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

8.  Distributions of experimental protein structures on coarse-grained free energy landscapes.

Authors:  Kannan Sankar; Jie Liu; Yuan Wang; Robert L Jernigan
Journal:  J Chem Phys       Date:  2015-12-28       Impact factor: 3.488

9.  Folding thermodynamics of peptides.

Authors:  Anders Irbäck; Sandipan Mohanty
Journal:  Biophys J       Date:  2004-12-21       Impact factor: 4.033

10.  Generation of native-like protein structures from limited NMR data, modern force fields and advanced conformational sampling.

Authors:  Jianhan Chen; Hyung-Sik Won; Wonpil Im; H Jane Dyson; Charles L Brooks
Journal:  J Biomol NMR       Date:  2005-01       Impact factor: 2.835

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