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Cited by in F6Publishing
For: Zha J, Li M, Kong R, Lu S, Zhang J. Explaining and Predicting Allostery with Allosteric Database and Modern Analytical Techniques. Journal of Molecular Biology 2022. [DOI: 10.1016/j.jmb.2022.167481] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
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1 Govindaraj RG, Thangapandian S, Schauperl M, Denny RA, Diller DJ. Recent applications of computational methods to allosteric drug discovery. Front Mol Biosci 2023;9. [DOI: 10.3389/fmolb.2022.1070328] [Reference Citation Analysis]
2 Xiao S, Verkhivker GM, Tao P. Machine learning and protein allostery. Trends Biochem Sci 2022:S0968-0004(22)00311-5. [PMID: 36564251 DOI: 10.1016/j.tibs.2022.12.001] [Reference Citation Analysis]
3 Kamaraj R, Drastik M, Maixnerova J, Pavek P. Allosteric Antagonism of the Pregnane X Receptor (PXR): Current-State-of-the-Art and Prediction of Novel Allosteric Sites. Cells 2022;11:2974. [DOI: 10.3390/cells11192974] [Reference Citation Analysis]
4 Berezovsky IN, Nussinov R. Multiscale Allostery: Basic Mechanisms and Versatility in Diagnostics and Drug Design. J Mol Biol 2022;:167751. [PMID: 35863488 DOI: 10.1016/j.jmb.2022.167751] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Xiao S, Tian H, Tao P. PASSer2.0: Accurate Prediction of Protein Allosteric Sites Through Automated Machine Learning. Front Mol Biosci 2022;9:879251. [DOI: 10.3389/fmolb.2022.879251] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]