University of Dundee

Start : September 2015 | Status : Active

The scientist: Dr. Federica Prati will focus her research on the identification of novel leads for the TB target InhA via fragment-based drug discovery (FBDD) methods. Federica is Postdoctoral Researcher with the Drug Discovery Unit at the University of Dundee, working under the supervision of Prof. Paul Wyatt and Dr. Peter Ray. She is an organic/medicinal chemist by training, and her primary role in this project will be the design, synthesis, and optimisation of the compounds coming from fragment screening against the enzyme.

The sponsors: University of Dundee Drug Discovery Unit

Foundation funding: The Foundation is providing £133,740 in support, together with co-funding from the European Unionīs FP7 program through its COFUND scheme.

GSK’s contribution: GSK will contribute in-kind with its extensive experience in InhA target-based programs for TB (J. Med. Chem. 2014, 57, 1276 – 1288; J. Med. Chem., 2015, 58 (2), pp 613–624). This experience will be leveraged not only in terms of inputting medicinal chemistry knowledge, but also in utilizing the existing InhA biochemical assay and crystallography platform.

Project Description: Isoniazid has been a staple of the TB drug regimen for more than 50 years. Because of this historical importance, its biological target, InhA, is one of the best validated enzymes for TB treatment. However, the increasing prevalence of isoniazid resistant forms of TB (along with other drug resistance issues), is threatening to become a major world health crisis if new drugs with efficacy against these resistant bacterial strains cannot be identified.

Critically, isoniazid resistance is primarily caused by mutations in the katG gene that encodes an enzyme that activates isoniazid to its active form. Therefore, compounds that directly inhibit InhA could be reasonably expected to recapitulate the clinical efficacy of isoniazid while maintaining activity against KatG mutants.

Previous efforts to develop direct InhA inhibitors, have generally struggled to identify compounds in optimal drug-like chemical space. By starting from very small, non-lipophilic hits, FBDD offers the opportunity to rationally design new inhibitors that are more likely to achieve the desired properties.