Literature DB >> 3477791

Monte Carlo-minimization approach to the multiple-minima problem in protein folding.

Z Li1, H A Scheraga.   

Abstract

A Monte Carlo-minimization method has been developed to overcome the multiple-minima problem. The Metropolis Monte Carlo sampling, assisted by energy minimization, surmounts intervening barriers in moving through successive discrete local minima in the multidimensional energy surface. The method has located the lowest-energy minimum thus far reported for the brain pentapeptide [Met5]enkephalin in the absence of water. Presumably it is the global minimum-energy structure. This supports the concept that protein folding may be a Markov process. In the presence of water, the molecules appear to exist as an ensemble of different conformations.

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Year:  1987        PMID: 3477791      PMCID: PMC299132          DOI: 10.1073/pnas.84.19.6611

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  17 in total

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Authors:  M Levitt; A Warshel
Journal:  Nature       Date:  1975-02-27       Impact factor: 49.962

2.  Conformational energy calculations on polypeptides and proteins: use of a statistical mechanical procedure for evaluating structure and properties.

Authors:  H A Scheraga; G H Paine
Journal:  Ann N Y Acad Sci       Date:  1986       Impact factor: 5.691

3.  Multiple conformational states of proteins: a molecular dynamics analysis of myoglobin.

Authors:  R Elber; M Karplus
Journal:  Science       Date:  1987-01-16       Impact factor: 47.728

4.  Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. II. Average backbone structure of enkephalin.

Authors:  G H Paine; H A Scheraga
Journal:  Biopolymers       Date:  1986-08       Impact factor: 2.505

5.  Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. III. Probable and average conformations of enkephalin.

Authors:  G H Paine; H A Scheraga
Journal:  Biopolymers       Date:  1987-07       Impact factor: 2.505

6.  Protein states and proteinquakes.

Authors:  A Ansari; J Berendzen; S F Bowne; H Frauenfelder; I E Iben; T B Sauke; E Shyamsunder; R D Young
Journal:  Proc Natl Acad Sci U S A       Date:  1985-08       Impact factor: 11.205

Review 7.  Motions in proteins.

Authors:  F R Gurd; T M Rothgeb
Journal:  Adv Protein Chem       Date:  1979

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Authors:  B Robson; D J Osguthorpe
Journal:  J Mol Biol       Date:  1979-07-25       Impact factor: 5.469

9.  Use of buildup and energy-minimization procedures to compute low-energy structures of the backbone of enkephalin.

Authors:  M Vásquez; H A Scheraga
Journal:  Biopolymers       Date:  1985-08       Impact factor: 2.505

10.  Prediction of the native conformation of a polypeptide by a statistical-mechanical procedure. I. Backbone structure of enkephalin.

Authors:  G H Paine; H A Scheraga
Journal:  Biopolymers       Date:  1985-08       Impact factor: 2.505

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  219 in total

1.  Catalytic tempering: A method for sampling rough energy landscapes by Monte Carlo.

Authors:  G Stolovitzky; B J Berne
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-10       Impact factor: 11.205

2.  Soft protein-protein docking in internal coordinates.

Authors:  Juan Fernández-Recio; Maxim Totrov; Ruben Abagyan
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

3.  Exact solutions for chemical bond orientations from residual dipolar couplings.

Authors:  William J Wedemeyer; Carol A Rohl; Harold A Scherag
Journal:  J Biomol NMR       Date:  2002-02       Impact factor: 2.835

4.  Long time dynamics of Met-enkephalin: comparison of explicit and implicit solvent models.

Authors:  Min-yi Shen My; Karl F Freed
Journal:  Biophys J       Date:  2002-04       Impact factor: 4.033

5.  Theoretical prediction of a crystal structure.

Authors:  R J Wawak; K D Gibson; A Liwo; H A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  1996-03-05       Impact factor: 11.205

6.  Conformation-family Monte Carlo: a new method for crystal structure prediction.

Authors:  J Pillardy; Y A Arnautova; C Czaplewski; K D Gibson; H A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  2001-10-16       Impact factor: 11.205

7.  RNA-binding strategies common to cold-shock domain- and RNA recognition motif-containing proteins.

Authors:  X Manival; L Ghisolfi-Nieto; G Joseph; P Bouvet; M Erard
Journal:  Nucleic Acids Res       Date:  2001-06-01       Impact factor: 16.971

8.  Enhanced sampling of the molecular potential energy surface using mutually orthogonal latin squares: application to peptide structures.

Authors:  K Vengadesan; N Gautham
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

9.  NCAD, a database integrating the intrinsic conformational preferences of non-coded amino acids.

Authors:  Guillem Revilla-López; Juan Torras; David Curcó; Jordi Casanovas; M Isabel Calaza; David Zanuy; Ana I Jiménez; Carlos Cativiela; Ruth Nussinov; Piotr Grodzinski; Carlos Alemán
Journal:  J Phys Chem B       Date:  2010-06-03       Impact factor: 2.991

10.  Atomically detailed folding simulation of the B domain of staphylococcal protein A from random structures.

Authors:  Jorge A Vila; Daniel R Ripoll; Harold A Scheraga
Journal:  Proc Natl Acad Sci U S A       Date:  2003-11-24       Impact factor: 11.205

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