Literature DB >> 8159662

Evaluation of the conformational free energies of loops in proteins.

K C Smith1, B Honig.   

Abstract

In this paper we discuss the problem of including solvation free energies in evaluating the relative stabilities of loops in proteins. A conformational search based on a gas-phase potential function is used to generate a large number of trial conformations. As has been found previously, the energy minimization step in this process tends to pack charged and polar side chains against the protein surface, resulting in conformations which are unstable in the aqueous phase. Various solvation models can easily identify such structures. In order to provide a more severe test of solvation models, gas-phase conformations were generated in which side chains were kept extended so as to maximize their interaction with the solvent. The free energies of these conformations were compared to that calculated for the crystal structure in three loops of the protein E. coli RNase H, with lengths of 7, 8, and 9 residues. Free energies were evaluated with a finite difference Poisson-Boltzmann (FDPB) calculation for electrostatics and a surface area-based term for nonpolar contributions. These were added to a gas-phase potential function. A free energy function based on atomic solvation parameters was also tested. Both functions were quite successful in selecting, based on a free energy criterion, conformations quite close to the crystal structure for two of the three loops. For one loop, which is involved in crystal contacts, conformations that are quite different from the crystal structure were also selected. A method to avoid precision problems associated with using the FDPB method to evaluate conformational free energies in proteins is described.

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Year:  1994        PMID: 8159662     DOI: 10.1002/prot.340180205

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


  30 in total

1.  Molecular dynamics study of the energetic, mechanistic, and structural implications of a closed phosphate tube in ncd.

Authors:  T J Minehardt; R Cooke; E Pate; P A Kollman
Journal:  Biophys J       Date:  2001-03       Impact factor: 4.033

2.  Selecting near-native conformations in homology modeling: the role of molecular mechanics and solvation terms.

Authors:  A Janardhan; S Vajda
Journal:  Protein Sci       Date:  1998-08       Impact factor: 6.725

3.  Modeling of loops in protein structures.

Authors:  A Fiser; R K Do; A Sali
Journal:  Protein Sci       Date:  2000-09       Impact factor: 6.725

4.  Evaluating conformational free energies: the colony energy and its application to the problem of loop prediction.

Authors:  Zhexin Xiang; Cinque S Soto; Barry Honig
Journal:  Proc Natl Acad Sci U S A       Date:  2002-05-28       Impact factor: 11.205

5.  Structural determinants of trypsin affinity and specificity for cationic inhibitors.

Authors:  F Polticelli; P Ascenzi; M Bolognesi; B Honig
Journal:  Protein Sci       Date:  1999-12       Impact factor: 6.725

6.  Structural features of [NiFeSe] and [NiFe] hydrogenases determining their different properties: a computational approach.

Authors:  Carla S A Baltazar; Vitor H Teixeira; Cláudio M Soares
Journal:  J Biol Inorg Chem       Date:  2012-04       Impact factor: 3.358

Review 7.  Advances in homology protein structure modeling.

Authors:  Zhexin Xiang
Journal:  Curr Protein Pept Sci       Date:  2006-06       Impact factor: 3.272

8.  Optimization of the GB/SA solvation model for predicting the structure of surface loops in proteins.

Authors:  Agnieszka Szarecka; Hagai Meirovitch
Journal:  J Phys Chem B       Date:  2006-02-16       Impact factor: 2.991

9.  Minimalist explicit solvation models for surface loops in proteins.

Authors:  Ronald P White; Hagai Meirovitch
Journal:  J Chem Theory Comput       Date:  2006       Impact factor: 6.006

10.  Prediction of protein loop structures using a local move Monte Carlo approach and a grid-based force field.

Authors:  Meng Cui; Mihaly Mezei; Roman Osman
Journal:  Protein Eng Des Sel       Date:  2008-10-27       Impact factor: 1.650

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