Literature DB >> 15037081

Can contact potentials reliably predict stability of proteins?

Jainab Khatun1, Sagar D Khare, Nikolay V Dokholyan.   

Abstract

The simplest approximation of interaction potential between amino acid residues in proteins is the contact potential, which defines the effective free energy of a protein conformation by a set of amino acid contacts formed in this conformation. Finding a contact potential capable of predicting free energies of protein states across a variety of protein families will aid protein folding and engineering in silico on a computationally tractable time-scale. We test the ability of contact potentials to accurately and transferably (across various protein families) predict stability changes of proteins upon mutations. We develop a new methodology to determine the contact potentials in proteins from experimental measurements of changes in protein's thermodynamic stabilities (DeltaDeltaG) upon mutations. We apply our methodology to derive sets of contact interaction parameters for a hierarchy of interaction models including solvation and multi-body contact parameters. We test how well our models reproduce experimental measurements by statistical tests. We evaluate the maximum accuracy of predictions obtained by using contact potentials and the correlation between parameters derived from different data-sets of experimental (DeltaDeltaG) values. We argue that it is impossible to reach experimental accuracy and derive fully transferable contact parameters using the contact models of potentials. However, contact parameters may yield reliable predictions of DeltaDeltaG for datasets of mutations confined to the same amino acid positions in the sequence of a single protein.

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Year:  2004        PMID: 15037081     DOI: 10.1016/j.jmb.2004.01.002

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  19 in total

1.  Folding Trp-cage to NMR resolution native structure using a coarse-grained protein model.

Authors:  Feng Ding; Sergey V Buldyrev; Nikolay V Dokholyan
Journal:  Biophys J       Date:  2004-11-08       Impact factor: 4.033

2.  Prediction of protein thermostability with a direction- and distance-dependent knowledge-based potential.

Authors:  Christian Hoppe; Dietmar Schomburg
Journal:  Protein Sci       Date:  2005-09-09       Impact factor: 6.725

3.  Protein folding: then and now.

Authors:  Yiwen Chen; Feng Ding; Huifen Nie; Adrian W Serohijos; Shantanu Sharma; Kyle C Wilcox; Shuangye Yin; Nikolay V Dokholyan
Journal:  Arch Biochem Biophys       Date:  2007-06-08       Impact factor: 4.013

4.  The ruggedness of protein-protein energy landscape and the cutoff for 1/r(n) potentials.

Authors:  Anatoly M Ruvinsky; Ilya A Vakser
Journal:  Bioinformatics       Date:  2009-02-23       Impact factor: 6.937

5.  MedusaDock 2.0: Efficient and Accurate Protein-Ligand Docking With Constraints.

Authors:  Jian Wang; Nikolay V Dokholyan
Journal:  J Chem Inf Model       Date:  2019-04-17       Impact factor: 4.956

Review 6.  Computational approaches for predicting mutant protein stability.

Authors:  Shweta Kulshreshtha; Vigi Chaudhary; Girish K Goswami; Nidhi Mathur
Journal:  J Comput Aided Mol Des       Date:  2016-05-09       Impact factor: 3.686

7.  A Transferable Coarse Grain Non-bonded Interaction Model For Amino Acids.

Authors:  Russell Devane; Wataru Shinoda; Preston B Moore; Michael L Klein
Journal:  J Chem Theory Comput       Date:  2009-08-11       Impact factor: 6.006

8.  Importance of a single disulfide bond for the PsbO protein of photosystem II: protein structure stability and soluble overexpression in Escherichia coli.

Authors:  Julia Nikitina; Tatiana Shutova; Bogdan Melnik; Sergey Chernyshov; Victor Marchenkov; Gennady Semisotnov; Vyacheslav Klimov; Göran Samuelsson
Journal:  Photosynth Res       Date:  2008-08-16       Impact factor: 3.573

9.  I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.

Authors:  Emidio Capriotti; Piero Fariselli; Rita Casadio
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

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

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