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Protein–Protein Docking: Past, Present, and Future

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Abstract

The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions of proteins in a living body. Due to their practical difficulties, reliable experimental techniques pave the way for introducing computational methods in the interaction prediction. Automated methods reduced the difficulties but could not yet replace experimental studies as the field is still evolving. Interaction prediction problem being critical needs highly accurate results, but none of the existing methods could offer reliable performance that can parallel with experimental results yet. This article aims to assess the existing computational docking algorithms, their challenges, and future scope. Blind docking techniques are quite helpful when no information other than the individual structures are available. As more and more complex structures are being added to different databases, information-driven approaches can be a good alternative. Artificial intelligence, ruling over the major fields, is expected to take over this domain very shortly.

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Acknowledgements

The authors acknowledge the Department of Computer Science and Engineering, NIT Calicut, for facilitating the access to the research articles referenced. Special thanks to Mr. Abdulfathaah Shamsuddin, Mr. Gokul Prasad S, Mr. Joel Mathew Cherian, Mr. Roshan MSB, and Mr. Saimanoj Akondi of NIT Calicut for their valuable suggestions.

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Sunny, S., Jayaraj, P.B. Protein–Protein Docking: Past, Present, and Future. Protein J 41, 1–26 (2022). https://doi.org/10.1007/s10930-021-10031-8

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