Title | ||
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HomPPI: a class of sequence homology based protein-protein interface prediction methods |
Abstract | ||
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Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins,
the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces
has been a subject of debate.
Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes,
including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based
inference of interface residues in a query protein sequence.
Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface
residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface
residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI),
which can be used to predict the interface residues of a query protein with a specific target protein.
Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein
interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity
of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface
residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art
interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier,
PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific
target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can
be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/.
Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein
interface residues that participate in either obligate or transient interactions. For query proteins involved in transient
interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction
partners. |
Year | DOI | Venue |
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2011 | 10.1186/1471-2105-12-244 | BMC Bioinformatics |
Keywords | Field | DocType |
Protein Data Bank, Query Sequence, Query Protein, Interface Residue, Protein Interface | Protein sequencing,Biology,Target protein,Intrinsically disordered proteins,Homology (biology),Bioinformatics,Classifier (linguistics),Protein Data Bank,DNA microarray,Peptide sequence | Journal |
Volume | Issue | ISSN |
12 | 1 | 1471-2105 |
Citations | PageRank | References |
10 | 0.52 | 34 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Li C Xue | 1 | 15 | 3.07 |
Drena Dobbs | 2 | 423 | 35.43 |
Vasant Honavar | 3 | 3353 | 468.10 |