ClusPro-DC (https://cluspro.bu.edu/) implements a straightforward approach to the discrimination between crystallographic and biological dimers by docking the two subunits to exhaustively sample the interaction energy landscape. If a substantial number of low energy docked poses cluster in a narrow vicinity of the native structure of the dimer, then one can assume that there is a well-defined free energy well around the native state, which makes the interaction stable. In contrast, if the interaction sites in the docked poses do not form a large enough cluster around the native structure, then it is unlikely that the subunits form a stable biological dimer. The number of near-native structures is used to estimate the probability of a dimer being biological. Currently, the server examines only the stability of a given interface rather than generating all putative quaternary structures as accomplished by PISA or EPPIC, but it complements the information provided by these methods.
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http://dx.doi.org/10.1016/j.jmb.2016.10.019 | DOI Listing |
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Department of Integrative Biology, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India.
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Tianjin Key Lab of Aqua-Ecology and Aquaculture, College of Fisheries, Tianjin Agricultural University, Tianjin, 300392, China. Electronic address:
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State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China.
Molecular docking is a crucial technique for elucidating protein-ligand interactions. Machine learning-based docking methods offer promising advantages over traditional approaches, with significant potential for further development. However, many current machine learning-based methods face challenges in ensuring the physical plausibility of generated docking poses.
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School of Environment and Geography, Qingdao University, Qingdao 266071, China.
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View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Drug and Health Sciences, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.
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