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protein–protein interfaces published month download article/chapter residue composition protein–protein interfaces heteromeric interfaces homomeric interfaces manage preferences author information authors protein data bank full article pdf protein journal aims privacy choices/manage cookies european economic area check access instant access utah state university iowa state university interactions apparently favored related subjects author correspondence conditions privacy policy opposite charge pairs pro-trp pairs protein sci 11 protein sci 7 protein sci 3 article yan accepting optional cookies computational intelligence journal finder publish protein cores protein structures pdb secondary structure structure quality interface surfaces main content log article log changhui yan article cite feihong wu hydrophobic pairs solvent accessibility personal data ben-tal interfaces differ comparing interfaces interfaces include biophys chem 114 privacy policy

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         headline:Characterization of Protein–Protein Interfaces
         description:We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.
         datePublished:2007-09-13T00:00:00Z
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      headline:Characterization of Protein–Protein Interfaces
      description:We analyze the characteristics of protein–protein interfaces using the largest datasets available from the Protein Data Bank (PDB). We start with a comparison of interfaces with protein cores and non-interface surfaces. The results show that interfaces differ from protein cores and non-interface surfaces in residue composition, sequence entropy, and secondary structure. Since interfaces, protein cores, and non-interface surfaces have different solvent accessibilities, it is important to investigate whether the observed differences are due to the differences in solvent accessibility or differences in functionality. We separate out the effect of solvent accessibility by comparing interfaces with a set of residues having the same solvent accessibility as the interfaces. This strategy reveals residue distribution propensities that are not observable by comparing interfaces with protein cores and non-interface surfaces. Our conclusions are that there are larger numbers of hydrophobic residues, particularly aromatic residues, in interfaces, and the interactions apparently favored in interfaces include the opposite charge pairs and hydrophobic pairs. Surprisingly, Pro-Trp pairs are over represented in interfaces, presumably because of favorable geometries. The analysis is repeated using three datasets having different constraints on sequence similarity and structure quality. Consistent results are obtained across these datasets. We have also investigated separately the characteristics of heteromeric interfaces and homomeric interfaces.
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      name:Department of Computer Science, Utah State University, Logan, USA
      name:Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, USA
      name:Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, USA
      name:Artificial Intelligence Research Laboratory, Department of Computer Science, Iowa State University, Ames, USA
      name:Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, USA
      name:Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, USA
      name:Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, USA
      name:Laurence H Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, USA
      name:Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, USA
      name:Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, USA
      name:Laurence H Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, USA
      name:Department of Genetics, Development and Cell Biology, Iowa State University, Ames, USA
      name:Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, USA
      name:Center for Computational Intelligence, Learning, and Discovery, Iowa State University, Ames, USA
      name:Artificial Intelligence Research Laboratory, Department of Computer Science, Iowa State University, Ames, USA
      name:Laurence H Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, USA
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