Abstract
BackgroundVarious methods have been developed to computationally predict hotspot residues at novel protein-protein interfaces. However, there are various challenges in obtaining accurate prediction. We have developed a novel method which uses different aspects of protein structure and sequence space at residue level to highlight interface residues crucial for the protein-protein complex formation.ResultsECMIS (Energetic Conservation Mass Index and Spatial Clustering) algorithm was able to outperform existing hotspot identification methods. It was able to achieve around 80% accuracy with incredible increase in sensitivity and outperforms other existing methods. This method is even sensitive towards the hotspot residues contributing only small-scale hydrophobic interactions.ConclusionCombination of diverse features of the protein viz. energy contribution, extent of conservation, location and surrounding environment, along with optimized weightage for each feature, was the key for the success of the algorithm. The academic version of the algorithm is available at http://caps.ncbs.res.in/download/ECMIS/ECMIS.zip.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-303) contains supplementary material, which is available to authorized users.
Highlights
Various methods have been developed to computationally predict hotspot residues at novel proteinprotein interfaces
Dataset a) Training set A dataset of 316 alanine-mutated interface residues (Additional file 1) derived from 19 protein complexes was taken from Alanine Scanning Energetic Database (ASEdb) [6]
The interface residues with binding free energy less than 0.4 kcal/mol were considered as non-hotspot residues, as described by Tuncbag et al [30] and Xia et al [47]
Summary
Various methods have been developed to computationally predict hotspot residues at novel proteinprotein interfaces. Free energy is an important criterion for proteinprotein binding and for better understanding of protein-protein interactions. The contribution of various interface residues towards free energy of binding is not uniform [1,2] and the ones which are energetically more important are known as hotspots. Hotspot residues are defined as those which bring changes in the binding free energy by more than 2 kcal/mol, when mutated to alanine [3]. These residues are generally seen to exist in clusters known as ‘hot regions’ [4]. Alanine Scanning Energetic Database (ASEdb) [6]
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