Abstract
Proteins play a crucial role in every organism, which perform a vast amount of functions. The hot regions in protein-protein interactions consist of hot spot residues in protein-protein binding sites which are called interfaces, can help proteins to perform their biological function. Residue based computational prediction of hot regions might be useful to understand the molecular mechanism and is crucial in drug design and protein design. However, it is very challenging to identify the hot regions in protein-proteins. In this paper, we have proposed a support vector machine based on ensemble learning system for predicting hot spot residues, and predicted hot regions in protein-protein interactions. The efficiency of our method is analyzed in identifying hot spots and hot regions in protein-protein interactions and the results obtained are compared with the existing techniques. The results demonstrate that the proposed method is superior to identify the hot spots and hot regions in the protein interfaces.
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