Computational Methods For Predicting Protein–Protein Interactions

Abstract

Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational techniques for the prediction of PPIs. Computational techniques have been applied to the collection, indexing, validation, analysis, and extrapolation of PPI data. This chapter will focus on computational prediction of PPI, reviewing a number of techniques including PIPE, developed in our own laboratory. For comparison, the conventional large-scale approaches to predict PPIs are also briefly discussed. The chapter concludes with a discussion of the limitations of both experimental and computational methods of determining PPIs.

A Novel Structural and Functional Insight Into Chloroplast-Encoded Central Subunit of Dark-Operated Protochlorophyllide Oxidoreductase (Dpor) of Plants

“…Glu62, Arg91, Gln52, Asn53, His19, Lys467, Val466, Asn17, Ser380, Glu72, Asn402, Thr462, Ile59, Tyr49 (Punta and Orfan, 2008;Pitre et al, 2008;Dereeper et al, 2008;Nawaz et al, 2014). For the very first time in present study, we have carried out structural as well as functional annotation of plant's ChlB subunit using different computational biology and bioinformatics approaches.…”

“…But all experimental techniques are costly, take too much time and need high expertise. However, computational techniques propose solutions for these problems (Pitre et al, 2008). We therefore consider bioinformatics tools for protein-protein interaction prediction.…”

Protein Interactome and Its Application to Protein Function Prediction

“…While recent reviews Pitre et al, 2008;Shoemaker & Panchenko, 2007;Skrabanek et al, 2008;Xia et al, 2010) have discussed computational prediction methods for PPIs in details, we here briefly introduce som e o f a p p r o a c h e s t h a t a r e w i d e l y u s e d . Although the amounts of experimental resources of PPIs are growing rapidly, proteomewide PPIs information is still lacking and mostly limited on several model organisms.…”

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning

“…The cost, time and other limitations associated with the current experimental methods to detect protein-protein interaction have motivated the development of computational methods for predicting PPIs [1][2][3]. Acquiring knowledge of the interfacial regions between interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design and disease treatment [4][5][6].…”