Using evolutionary coupling methodology and other unique computational biology tools to advance pharmaceutical development
The prediction of drug effects is a long-standing challenge in the biomedical data community and pharmaceutical industry. As new candidate target genes emerge from successful CRISPR and GWAS screens, assessing ‘anti-targets’ and exploiting polypharmacology becomes important. However, the challenge is to build truly predictive models for the effect of drugs on as many human targets as possible. Dr. Debbie Marks and researchers in her laboratory established computational methods that broaden the scope of molecular target types for which this predictive information is available. These methods, including evolutionary coupling methodology recently described in Cell (Toth-Petroczy, Palmedo et al., Cell 2016; Weinreb et al. Cell May 2016) as well as other unique approaches can be used to (i) develop drugs targeting disordered proteins associated with pathological processes, (ii) identify druggable mRNA targets, and (iii) optimize/improve the specificity of CRISPR sgRNA. We are looking for partners and investors interested in exploring the opportunities for collaboration in the three areas outlined above.
Intellectual Property Status: Patent(s) Pending