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Title: Elucidating protein-protein interactions through computational approaches and designing small molecule inhibitors against them for various diseases
Authors: Sarkar S.
Gulati K.
Kairamkonda M.
Mishra A.
Poluri, Krishna Mohan
Published in: Current Topics in Medicinal Chemistry
Abstract: Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span. © 2018 Bentham Science Publishers.
Citation: Current Topics in Medicinal Chemistry(2018), 18(20): 1719-1736
Issue Date: 2018
Publisher: Bentham Science Publishers B.V.
Keywords: High throughput screening
Machine learning
Molecular signaling
Protein-protein interactions
Small molecule inhibitors
Structure-function relationships
ISSN: 15680266
Author Scopus IDs: 57205433302
Author Affiliations: Sarkar, S., Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Gulati, K., Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Kairamkonda, M.,
Corresponding Author: Poluri, K.M.; Department of Biotechnology, Centre for Nanotechnology, Indian Institute of Technology RoorkeeIndia; email:
Appears in Collections:Journal Publications [BT]

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