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 FDA approved drugs across 2335 human protein crystal structures. The TMFS method predicts drug−target associations with 91% accuracy for the majority of drugs. Over 58% of the known best ligands for each target were correctly predicted as top ranked, followed by 66%, 76%, 84%, and 91% for agents ranked in the top 10, 20, 30, and 40, respectively, out of all 3671 drugs. Drugs ranked in the top 1−40 that have not been experimentally validated for a particular target now become candidates for repositioning. Furthermore, we used the TMFS method to discover that mebendazole, an antiparasitic with recently discovered and unexpected anticancer properties, has the structural potential to inhibit VEGFR2. We confirmed experimentally that mebendazole inhibits VEGFR2 kinase activity and angiogenesis at doses comparable with its known effects on hookworm. TMFS also predicted, and was confirmed with surface plasmon resonance, that dimethyl celecoxib and the anti-inflammatory agent celecoxib can bind cadherin-11, an adhesion molecule important in rheumatoid arthritis and poor prognosis malignancies for which no targeted therapies exist. We anticipate that expanding our TMFS method to the >27 000 clinically active agents available worldwide across all targets will be most useful in the repositioning of existing drugs for new therapeutic targets.

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“…The article by Simbulan-Rosenthal et al [3] is an important addition to this initiative, elegantly combining a novel rapid computational proteochemometric method [4,5] coupled to cell-based assays to show that the anthelmintic drug mebendazole should be considered in combination with trametinib as a therapeutic option for patients with NRAS Q61mut or other non-V600E BRAF mutant melanomas.…”

“…However, mebendazole binds tubulin at a site that differs from other tubulin binding agents such as vinblastine or paclitaxel and, quite remarkably, interacts with a number of other cancer targets. Several of these targets have been identified using the computational methods developed by this group of investigators and include multiple kinases as well as anti-inflammatory drugs [4,5].…”

“…The computational proteochemometric method developed by Dakshanamurthy et al [4,5] WT mutation, these investigators demonstrated that mebendazole synergized strongly with trametinib in both BAK and BUL cell lines, but was either antagonistic or additive in STU cells at low or high concentrations, respectively. Further, the combination of these two drugs induced caspase-3 activity earlier and to a greater extent than either drug alone, indicating a rapid induction of apoptosis.…”

“…The identification of therapeutic need, coupled to sophisticated computational approaches, increasing News genetic and genomic information, exemplifies the value of a polypharmacological approach based on repurposing [4,5,7] and adds strength to the emphasis on precision oncology and personalized medicine [1,8]. As this report demonstrates, there is considerable value in examining existing drugs that have been approved or have at least passed through Phase I safety and tolerability studies as the path to clinical application is shortened considerably.…”

Repurposing Drugs in the Genomics Era: Bioinformatics Approaches

“…Bioinformatics approaches can be used effectively to develop a database of repurposed drugs. 12,13 Mining of the genome-and -knowledge oriented databases is an attractive starting point for drug targets discovery. The availability of genome databases such as the NCBI Phenome-Genome Integrator, PheGenI, 14 the Genome-wide Association Studies Catalogue, GWAS, 15 human protein atlas, 16 human protein map, 17 proteomics dB 18 the Uniprot knowledgebase 19 and canSar protein annotation tool 20 can facilitate a systematic characterization of drug targets.…”