Predicting new indications for approved drugs using a proteochemometric method.

ABSTRACT: The most effective way to move from target identification to the clinic is to identify already approved drugs with the potential for activating or inhibiting unintended targets (repurposing or repositioning). This is usually achieved by high throughput chemical screening, transcriptome matching, or simple in silico ligand docking. We now describe a novel rapid computational proteochemometric method called "train, match, fit, streamline" (TMFS) to map new drug-target interaction space and predict new uses. The TMFS method combines shape, topology, and chemical signatures, including docking score and functional contact points of the ligand, to predict potential drug-target interactions with remarkable accuracy. Using the TMFS method, we performed extensive molecular fit computations on 3671

SUBMITTER: Dakshanamurthy S 

PROVIDER: S-EPMC3419493 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature