Literature DB >> 8746722

Are database-derived potentials valid for scoring both forward and inverted protein folding?

M J Rooman1, S J Wodak.   

Abstract

Database-derived potentials, compiled from frequencies of sequence and structure features, are often used for scoring the compatibility of protein sequences and conformations. It is often believed that these scores correspond to differences in free energy with, in addition, a term containing the partition function of the system. Since this function does not depend on the conformation, the potentials are considered to be valid for scoring the compatibility of different conformations with a given sequence ('forward folding'), but not of sequences with a given structure ('inverted folding'). This interpretation is questioned here. It is argued that when many body-effects, which dominate frequencies compiled from the protein database, are corrected for, the potentials approximate a physically meaningful free energy difference from which the partition function term cancels out. It is the difference between the free energy of a given sequence in a specific conformation and that of the same sequence in a denatured-like state. Two examples of denatured-like states are discussed. Depending on the considered state, the free energy difference reduces to the commonly used scoring scheme, or contains additional terms that depend on the sequence. In both cases, all the terms can be derived from sequence-structure frequencies in the database. Such free energy difference, commonly defined as the folding free energy, is a measure of protein stability and can be used for scoring both forward and inverted protein folding. The implications for the use of knowledge-based potentials in protein structure prediction are described. Finally, the difficulty of designing tests that could validate the proposed approach, and the inherent limitations of such tests, are discussed.

Mesh:

Substances:

Year:  1995        PMID: 8746722     DOI: 10.1093/protein/8.9.849

Source DB:  PubMed          Journal:  Protein Eng        ISSN: 0269-2139


  12 in total

1.  Scoring functions in protein folding and design.

Authors:  R I Dima; J R Banavar; A Maritan
Journal:  Protein Sci       Date:  2000-04       Impact factor: 6.725

2.  Statistical potentials for fold assessment.

Authors:  Francisco Melo; Roberto Sánchez; Andrej Sali
Journal:  Protein Sci       Date:  2002-02       Impact factor: 6.725

3.  Feasibility in the inverse protein folding protocol.

Authors:  M Ota; K Nishikawa
Journal:  Protein Sci       Date:  1999-05       Impact factor: 6.725

4.  Database-derived potentials dependent on protein size for in silico folding and design.

Authors:  Yves Dehouck; Dimitri Gilis; Marianne Rooman
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

5.  Statistical potential for assessment and prediction of protein structures.

Authors:  Min-Yi Shen; Andrej Sali
Journal:  Protein Sci       Date:  2006-11       Impact factor: 6.725

6.  Statistical potential for modeling and ranking of protein-ligand interactions.

Authors:  Hao Fan; Dina Schneidman-Duhovny; John J Irwin; Guangqiang Dong; Brian K Shoichet; Andrej Sali
Journal:  J Chem Inf Model       Date:  2011-11-21       Impact factor: 4.956

7.  Comparison of protein structures using 3D profile alignment.

Authors:  M Suyama; Y Matsuo; K Nishikawa
Journal:  J Mol Evol       Date:  1997       Impact factor: 2.395

8.  Extracting knowledge from protein structure geometry.

Authors:  Peter Røgen; Patrice Koehl
Journal:  Proteins       Date:  2013-02-27

9.  Potentials of mean force for protein structure prediction vindicated, formalized and generalized.

Authors:  Thomas Hamelryck; Mikael Borg; Martin Paluszewski; Jonas Paulsen; Jes Frellsen; Christian Andreetta; Wouter Boomsma; Sandro Bottaro; Jesper Ferkinghoff-Borg
Journal:  PLoS One       Date:  2010-11-10       Impact factor: 3.240

10.  Four distances between pairs of amino acids provide a precise description of their interaction.

Authors:  Mati Cohen; Vladimir Potapov; Gideon Schreiber
Journal:  PLoS Comput Biol       Date:  2009-08-14       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.