Gaia: Automated quality assessment of protein structure models

Pradeep Kota, Feng Ding, Srinivas Ramachandran, Nikolay V. Dokholyan

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Motivation: Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures.Results: In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement.

Original languageEnglish (US)
Article numberbtr374
Pages (from-to)2209-2215
Number of pages7
JournalBioinformatics
Volume27
Issue number16
DOIs
StatePublished - Aug 2011

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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