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CRD: A de novo design algorithm for the prediction of cognate protein receptors for small molecule ligands

Sankar, S and Vasudevan, S and Chandra, N (2024) CRD: A de novo design algorithm for the prediction of cognate protein receptors for small molecule ligands. In: Structure, 32 (3). 362-375.e4.

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Official URL: https://doi.org/10.1016/j.str.2023.12.009


While predicting a ligand that binds to a protein is feasible with current methods, the opposite, i.e., the prediction of a receptor for a ligand remains challenging. We present an approach for predicting receptors of a given ligand that uses de novo design and structural bioinformatics. We have developed the algorithm CRD, comprising multiple modules combining fragment-based sub-site finding, a machine learning function to estimate the size of the site, a genetic algorithm that encodes knowledge on protein structures and a physics-based fitness scoring scheme. CRD includes a pseudo-receptor design component followed by a mapping component to identify proteins that might contain these sites. CRD recovers the sites and receptors of several natural ligands. It designs similar sites for similar ligands, yet to some extent can distinguish between closely related ligands. CRD correctly predicts receptor classes for several drugs and might become a valuable tool for drug discovery. © 2023 Elsevier Ltd

Item Type: Journal Article
Publication: Structure
Publisher: Cell Press
Additional Information: The copyright for this article belongs to the Authors.
Keywords: ligand; protein; protein binding, algorithm; binding site; chemistry; drug design, Algorithms; Binding Sites; Drug Design; Ligands; Protein Binding; Proteins
Department/Centre: Division of Biological Sciences > Biochemistry
Division of Interdisciplinary Sciences > Centre for Biosystems Science and Engineering
Division of Physical & Mathematical Sciences > Mathematics
Date Deposited: 23 Apr 2024 07:07
Last Modified: 23 Apr 2024 07:07
URI: https://eprints.iisc.ac.in/id/eprint/84641

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