Literature DB >> 11391771

How to guarantee optimal stability for most representative structures in the Protein Data Bank.

U Bastolla1, J Farwer, E W Knapp, M Vendruscolo.   

Abstract

We proposed recently an optimization method to derive energy parameters for simplified models of protein folding. The method is based on the maximization of the thermodynamic average of the overlap between protein native structures and a Boltzmann ensemble of alternative structures. Such a condition enforces protein models whose ground states are most similar to the corresponding native states. We present here an extensive testing of the method for a simple residue-residue contact energy function and for alternative structures generated by threading. The optimized energy function guarantees high stability and a well-correlated energy landscape to most representative structures in the PDB database. Failures in the recognition of the native structure can be attributed to the neglect of interactions between different chains in oligomeric proteins or with cofactors. When these are taken into account, only very few X-ray structures are not recognized. Most of them are short inhibitors or fragments and one is a structure that presents serious inconsistencies. Finally, we discuss the reasons that make NMR structures more difficult to recognizeCopyright 2001 Wiley-Liss, Inc.

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Year:  2001        PMID: 11391771     DOI: 10.1002/prot.1075

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


  38 in total

1.  Statistical properties of neutral evolution.

Authors:  Ugo Bastolla; Markus Porto; H Eduardo Roman; Michele Vendruscolo
Journal:  J Mol Evol       Date:  2003       Impact factor: 2.395

Review 2.  The interface of protein structure, protein biophysics, and molecular evolution.

Authors:  David A Liberles; Sarah A Teichmann; Ivet Bahar; Ugo Bastolla; Jesse Bloom; Erich Bornberg-Bauer; Lucy J Colwell; A P Jason de Koning; Nikolay V Dokholyan; Julian Echave; Arne Elofsson; Dietlind L Gerloff; Richard A Goldstein; Johan A Grahnen; Mark T Holder; Clemens Lakner; Nicholas Lartillot; Simon C Lovell; Gavin Naylor; Tina Perica; David D Pollock; Tal Pupko; Lynne Regan; Andrew Roger; Nimrod Rubinstein; Eugene Shakhnovich; Kimmen Sjölander; Shamil Sunyaev; Ashley I Teufel; Jeffrey L Thorne; Joseph W Thornton; Daniel M Weinreich; Simon Whelan
Journal:  Protein Sci       Date:  2012-04-23       Impact factor: 6.725

3.  Inferring ideal amino acid interaction forms from statistical protein contact potentials.

Authors:  Piotr Pokarowski; Andrzej Kloczkowski; Robert L Jernigan; Neha S Kothari; Maria Pokarowska; Andrzej Kolinski
Journal:  Proteins       Date:  2005-04-01

4.  A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins.

Authors:  Rafael F Pagan; Steven E Massey
Journal:  J Mol Evol       Date:  2013-12-21       Impact factor: 2.395

5.  Amino acid interaction preferences in proteins.

Authors:  Anupam Nath Jha; Saraswathi Vishveshwara; Jayanth R Banavar
Journal:  Protein Sci       Date:  2010-03       Impact factor: 6.725

6.  Predicting weakly stable regions, oligomerization state, and protein-protein interfaces in transmembrane domains of outer membrane proteins.

Authors:  Hammad Naveed; Ronald Jackups; Jie Liang
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-21       Impact factor: 11.205

Review 7.  Binding constraints on the evolution of enzymes and signalling proteins: the important role of negative pleiotropy.

Authors:  David A Liberles; Makayla D M Tisdell; Johan A Grahnen
Journal:  Proc Biol Sci       Date:  2011-04-13       Impact factor: 5.349

8.  Fast side chain replacement in proteins using a coarse-grained approach for evaluating the effects of mutation during evolution.

Authors:  Johan A Grahnen; Jan Kubelka; David A Liberles
Journal:  J Mol Evol       Date:  2011-07-29       Impact factor: 2.395

9.  Mutation bias favors protein folding stability in the evolution of small populations.

Authors:  Raul Mendez; Miriam Fritsche; Markus Porto; Ugo Bastolla
Journal:  PLoS Comput Biol       Date:  2010-05-06       Impact factor: 4.475

10.  Quantifying the impact of dependent evolution among sites in phylogenetic inference.

Authors:  Chris A Nasrallah; David H Mathews; John P Huelsenbeck
Journal:  Syst Biol       Date:  2010-11-15       Impact factor: 15.683

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