massachusetts institute of technology (mit)
computer science and artificial intelligence laboratory (csail)
theory of computation group (toc)

computation and biology group (compbio)

email queries iwrap@mit.edu

iWRAP is a novel threading based protein-protein interaction prediction program. For PPI prediction, iWRAP can be divided into two stages. Given two proteins with their sequences, iWRAP threads (using RAPTOR) these two sequences to a non-redundant database constructed from PDB. Using the SCOP classification for the top templates obtained in this stage, iWRAP searches all the protein complexes in the interface template database and then chooses the best potential match. Given the template, iWRAP then uses a novel localized threading algorithm to identify putative interacting residues. Based on this interacting surface, a boosting classifier is used to evaluate the probability of these two proteins interacting. Experimental results indicate that the predictive power of the structure-based method is better than many other information sources. Also, since iWRAP is independent of any functional data, it can be used alongwith other systems data for PPI prediction.

Supplementary Information for our paper "iWRAP: An interface threading approach" is here. Top 100000 predictions for s.cerevisiae using the combined method (iWRAP+DBLRAP(boost)) are here. Note that these sets do NOT contain PPI data used in training and testing the classifier (i.e., the overlapping subset of high-confidence interactions from BioGRID).

Top 100500 predictions for s.cerevisiae using iWRAP are here. iWRAP executable and examples can be downloaded from here. Instructions on installation and running iWRAP can be viewed here. Note that iWRAP uses COIN-OR for optimization and input files generated using PSIPRED.

DBLRAP can be accessed at Struct2Net. In the future, we plan to integrate iWRAP into Struct2Net.

iWRAP is licensed under GPLv3.