TY - JOUR T1 - A Computational Approach to Finding Novel Targets for Existing Drugs A1 - Li, Yvonne Y. A1 - An, Jianghong A1 - Jones, Steven J. M. Y1 - 2011/09/01 N2 - Author Summary Most drugs are designed to bind to and inhibit the function of a disease target protein. However, drugs are often able to bind to ‘off-target’ proteins due to similarities in the protein binding sites. If an off-target is known to be involved in another disease, then the drug has potential to treat the second disease. This repositioning strategy is an alternate and efficient approach to drug discovery, as the clinical and toxicity histories of existing drugs can greatly reduce drug development cost and time. We present here a large-scale computational approach that simulates three-dimensional binding between existing drugs and target proteins to predict novel drug-target interactions. Our method focuses on removing false predictions, using annotated ‘known’ interactions, scoring and ranking thresholds. 31 of our top novel drug-target predictions were validated through literature search, and demonstrated the utility of our method. We were also able to identify the cancer drug nilotinib as a potent inhibitor of MAPK14, a target in inflammatory diseases, which suggests a potential use for the drug in treating rheumatoid arthritis. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 9 UR - https://doi.org/10.1371/journal.pcbi.1002139 SP - e1002139 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002139 ER -