Literature DB >> 9779790

Exploring the conformational space of protein side chains using dead-end elimination and the A* algorithm.

A R Leach1, A P Lemon.   

Abstract

We describe an algorithm which enables us to search the conformational space of the side chains of a protein to identify the global minimum energy combination of side chain conformations as well as all other conformations within a specified energy cutoff of the global energy minimum. The program is used to explore the side chain conformational energy surface of a number of proteins, to investigate how this surface varies with the energy model used to describe the interactions within the system and the rotamer library. Enumeration of the rotamer combinations enables us to directly evaluate the partition function, and thus calculate the side chain contribution to the conformational entropy of the folded protein. An investigation of these conformations and the relationships between them shows that most of the conformations near to the global energy minimum arise from changes in side chain conformations that are essentially independent; very few result from a concerted change in conformation of two or more residues. Some of the limitations of the approach are discussed.

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Year:  1998        PMID: 9779790     DOI: 10.1002/(sici)1097-0134(19981101)33:2<227::aid-prot7>3.0.co;2-f

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  68 in total

1.  A stochastic algorithm for global optimization and for best populations: a test case of side chains in proteins.

Authors:  Meir Glick; Anwar Rayan; Amiram Goldblum
Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-15       Impact factor: 11.205

2.  Side-chain repacking calculations for predicting structures and stabilities of heterodimeric coiled coils.

Authors:  A E Keating; V N Malashkevich; B Tidor; P S Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2001-12-18       Impact factor: 11.205

3.  GEM: a Gaussian Evolutionary Method for predicting protein side-chain conformations.

Authors:  Jinn-Moon Yang; Chi-Hung Tsai; Ming-Jing Hwang; Huai-Kuang Tsai; Jenn-Kang Hwang; Cheng-Yan Kao
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

4.  Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer library.

Authors:  Ronald W Peterson; P Leslie Dutton; A Joshua Wand
Journal:  Protein Sci       Date:  2004-03       Impact factor: 6.725

5.  A Bayesian approach for determining protein side-chain rotamer conformations using unassigned NOE data.

Authors:  Jianyang Zeng; Kyle E Roberts; Pei Zhou; Bruce Randall Donald
Journal:  J Comput Biol       Date:  2011-10-04       Impact factor: 1.479

6.  Chemical space sampling by different scoring functions and crystal structures.

Authors:  Natasja Brooijmans; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-04-18       Impact factor: 3.686

7.  BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

Authors:  Jonathan D Jou; Swati Jain; Ivelin S Georgiev; Bruce R Donald
Journal:  J Comput Biol       Date:  2016-01-08       Impact factor: 1.479

8.  Side-chain flexibility in protein-ligand binding: the minimal rotation hypothesis.

Authors:  Maria I Zavodszky; Leslie A Kuhn
Journal:  Protein Sci       Date:  2005-04       Impact factor: 6.725

9.  Action-at-a-distance interactions enhance protein binding affinity.

Authors:  Brian A Joughin; David F Green; Bruce Tidor
Journal:  Protein Sci       Date:  2005-03-31       Impact factor: 6.725

10.  CIRSE: a solvation energy estimator compatible with flexible protein docking and design applications.

Authors:  David S Cerutti; Tushar Jain; J Andrew McCammon
Journal:  Protein Sci       Date:  2006-07       Impact factor: 6.725

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