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.