%0 Journal Article %1 Zhou2015Comprehensive %A Zhou, Hongyi %A Gao, Mu %A Skolnick, Jeffrey %D 2015 %J Scientific reports %K drug-protein-interactions %T Comprehensive prediction of drug-protein interactions and side effects for the human proteome. %U http://view.ncbi.nlm.nih.gov/pubmed/26057345 %V 5 %X Identifying unexpected drug-protein interactions is crucial for drug repurposing. We develop a comprehensive proteome scale approach that predicts human protein targets and side effects of drugs. For drug-protein interaction prediction, FINDSITE(comb), whose average precision is \~30\% and recall \~27\%, is employed. For side effect prediction, a new method is developed with a precision of \~57\% and a recall of \~24\%. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. The result implies that drug side effects are inevitable and existing drugs may be useful for repurposing, with only \~1,000 human proteins likely causing serious side effects. A killing index derived from serious side effects has a strong correlation with FDA approved drugs being withdrawn. Therefore, it provides a pre-filter for new drug development. The methodology is free to the academic community on the DR. PRODIS (DRugome, PROteome, and DISeasome) webserver at http://cssb.biology.gatech.edu/dr.prodis/. DR. PRODIS provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs, as well as an interface for the virtual target screening of new compounds.

@article{Zhou2015Comprehensive, abstract = {Identifying unexpected drug-protein interactions is crucial for drug repurposing. We develop a comprehensive proteome scale approach that predicts human protein targets and side effects of drugs. For drug-protein interaction prediction, {FINDSITE}(comb), whose average precision is \~{}30\% and recall \~{}27\%, is employed. For side effect prediction, a new method is developed with a precision of \~{}57\% and a recall of \~{}24\%. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. The result implies that drug side effects are inevitable and existing drugs may be useful for repurposing, with only \~{}1,000 human proteins likely causing serious side effects. A killing index derived from serious side effects has a strong correlation with {FDA} approved drugs being withdrawn. Therefore, it provides a pre-filter for new drug development. The methodology is free to the academic community on the {DR}. {PRODIS} ({DRugome}, {PROteome}, and {DISeasome}) webserver at http://cssb.biology.gatech.edu/dr.prodis/. {DR}. {PRODIS} provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs, as well as an interface for the virtual target screening of new compounds.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Zhou, Hongyi and Gao, Mu and Skolnick, Jeffrey}, biburl = {https://www.bibsonomy.org/bibtex/20688f1a3ee94c6117e82fcfdeacbedfb/karthikraman}, citeulike-article-id = {13662129}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/26057345}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=26057345}, day = 09, interhash = {dec4b98d46026897f0aafe3e520e0098}, intrahash = {0688f1a3ee94c6117e82fcfdeacbedfb}, issn = {2045-2322}, journal = {Scientific reports}, keywords = {drug-protein-interactions}, month = jun, pmid = {26057345}, posted-at = {2015-07-01 12:57:41}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Comprehensive prediction of drug-protein interactions and side effects for the human proteome.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/26057345}, volume = 5, year = 2015 }