Literature DB >> 7783220

Atomic environment energies in proteins defined from statistics of accessible and contact surface areas.

M Delarue1, P Koehl.   

Abstract

Atomic contact potentials are derived by statistical analysis of atomic surface contact areas versus atom type in a database of non-homologous protein structures. The atomic environment is characterized by the surface area accessible to solvent and the surface of contacts with polar and non-polar atoms. Four types of atoms are considered, namely neutral polar atoms from protein backbones and from protein side-chains, non-polar atoms and charged atoms. Potential energies delta Ej(E) are defined from the preference for an atom of type j to be in a given environment E compared to the expected value if everything was random; Boltzmann's law is then used to transform these preferences into energies. These new potentials very clearly discriminate misfolded from correct structural models. The performance of these potentials are critically assessed by monitoring the recognition of the native fold among a large number of alternative structural folding types (the hide-and-seek procedure), as well as by testing if the native sequence can be recovered from a large number of randomly shuffled sequences for a given 3D fold (a procedure similar to the inverse folding problem). We suggest that these potentials reflect the atomic short range non-local interactions in proteins. To characterise atomic solvation alone, similar potentials were derived as a function of the percentage of solvent-accessible area alone. These energies were found to agree reasonably well with the solvation formalism of Eisenberg and McLachlan.

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Year:  1995        PMID: 7783220     DOI: 10.1006/jmbi.1995.0328

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


  5 in total

1.  Use of surface area computations to describe atom-atom interactions.

Authors:  X de La Cruz; M Calvo
Journal:  J Comput Aided Mol Des       Date:  2001-06       Impact factor: 3.686

2.  What should the Z-score of native protein structures be?

Authors:  L Zhang; J Skolnick
Journal:  Protein Sci       Date:  1998-05       Impact factor: 6.725

Review 3.  Measuring the shapes of macromolecules - and why it matters.

Authors:  Jie Li; Paul Mach; Patrice Koehl
Journal:  Comput Struct Biotechnol J       Date:  2013-12-09       Impact factor: 7.271

4.  Accessibility and partner number of protein residues, their relationship and a webserver, ContPlot for their display.

Authors:  Arumay Pal; Ranjit Prasad Bahadur; Partha Sarathi Ray; Pinak Chakrabarti
Journal:  BMC Bioinformatics       Date:  2009-04-08       Impact factor: 3.169

5.  All-Atom Four-Body Knowledge-Based Statistical Potentials to Distinguish Native Protein Structures from Nonnative Folds.

Authors:  Majid Masso
Journal:  Biomed Res Int       Date:  2017-10-08       Impact factor: 3.411

  5 in total

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