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Here we present mCSM-lig, a structure-guided computational approach for quantifying the effects of single-point missense mutations on affinities of small molecules for proteins. mCSM-lig uses graph-based signatures to represent the wild-type environment of mutations and small-molecule chemical features and changes in protein stability as evidence to train a predictive model using a representative set of protein-ligand complexes from the Platinum database. We show our method provides a very good correlation with experimental data (up to \u03c1\u2009=\u20090.67) and is effective in predicting a range of chemotherapeutic, antiviral and antibiotic resistance mutations, providing useful insights for genotypic screening and to guide drug development. mCSM-lig also provides insights into understanding Mendelian disease mutations and as a tool for guiding protein design. mCSM-lig is freely available as a web server at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/structure.bioc.cam.ac.uk\/mcsm_lig\">http:\/\/structure.bioc.cam.ac.uk\/mcsm_lig<\/jats:ext-link>.<\/jats:p>","DOI":"10.1038\/srep29575","type":"journal-article","created":{"date-parts":[[2016,7,7]],"date-time":"2016-07-07T09:16:36Z","timestamp":1467882996000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":136,"title":["mCSM-lig: quantifying the effects of mutations on protein-small molecule affinity in genetic disease and emergence of drug resistance"],"prefix":"10.1038","volume":"6","author":[{"given":"Douglas E. 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