Literature DB >> 12069626

Evolution and physics in comparative protein structure modeling.

András Fiser1, Michael Feig, Charles L Brooks, Andrej Sali.   

Abstract

From a physical perspective, the native structure of a protein is a consequence of physical forces acting on the protein and solvent atoms during the folding process. From a biological perspective, the native structure of proteins is a result of evolution over millions of years. Correspondingly, there are two types of protein structure prediction methods, de novo prediction and comparative modeling. We review comparative protein structure modeling and discuss the incorporation of physical considerations into the modeling process. A good starting point for achieving this aim is provided by comparative modeling by satisfaction of spatial restraints. Incorporation of physical considerations is illustrated by an inclusion of solvation effects into the modeling of loops.

Mesh:

Substances:

Year:  2002        PMID: 12069626     DOI: 10.1021/ar010061h

Source DB:  PubMed          Journal:  Acc Chem Res        ISSN: 0001-4842            Impact factor:   22.384


  31 in total

1.  An analysis of core deformations in protein superfamilies.

Authors:  Alejandra Leo-Macias; Pedro Lopez-Romero; Dmitry Lupyan; Daniel Zerbino; Angel R Ortiz
Journal:  Biophys J       Date:  2004-11-12       Impact factor: 4.033

2.  Base-flipping mechanism in postmismatch recognition by MutS.

Authors:  Sean M Law; Michael Feig
Journal:  Biophys J       Date:  2011-11-01       Impact factor: 4.033

3.  RNA polymerase II with open and closed trigger loops: active site dynamics and nucleic acid translocation.

Authors:  Michael Feig; Zachary F Burton
Journal:  Biophys J       Date:  2010-10-20       Impact factor: 4.033

4.  Prediction of side-chain conformations on protein surfaces.

Authors:  Zhexin Xiang; Peter J Steinbach; Matthew P Jacobson; Richard A Friesner; Barry Honig
Journal:  Proteins       Date:  2007-03-01

5.  Dihedral-angle information entropy as a gauge of secondary structure propensity.

Authors:  Shi Zhong; Jeremy M Moix; Stephen Quirk; Rigoberto Hernandez
Journal:  Biophys J       Date:  2006-09-15       Impact factor: 4.033

6.  Modeling mutations in protein structures.

Authors:  Eric Feyfant; Andrej Sali; András Fiser
Journal:  Protein Sci       Date:  2007-09       Impact factor: 6.725

Review 7.  CHARMM: the biomolecular simulation program.

Authors:  B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus
Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

8.  Blind test of physics-based prediction of protein structures.

Authors:  M Scott Shell; S Banu Ozkan; Vincent Voelz; Guohong Albert Wu; Ken A Dill
Journal:  Biophys J       Date:  2009-02       Impact factor: 4.033

9.  Comparative protein structure modeling using Modeller.

Authors:  Ben Webb; Andrej Sali; Narayanan Eswar; Marc A Marti-Renom; M S Madhusudhan; David Eramian; Min-Yi Shen; Ursula Pieper
Journal:  Curr Protoc Bioinformatics       Date:  2006-10

10.  Complete atomistic model of a bacterial cytoplasm for integrating physics, biochemistry, and systems biology.

Authors:  Michael Feig; Ryuhei Harada; Takaharu Mori; Isseki Yu; Koichi Takahashi; Yuji Sugita
Journal:  J Mol Graph Model       Date:  2015-02-28       Impact factor: 2.518

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.