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Project

Fragment-based computational design of inhibitors of dipeptidyl peptidase 8 and 9.

Evaluation of the binding affinity of small molecules against therapeutically relevant proteins is currently performed using in vitro assays tailored to the specific problem at hand. However, despite their proven usefulness, compound solubility issues and limited chemical diversity imposed by the input compound library, emphasise some drawbacks. Fragment-based methods have also been introduced in which fragments are linked up with other fragments to grow into drug-like molecules. However, because such fragments are small, binding is weak and not always straightforward to detect. Hence, as an alternative to the experimental fragment-based screening, this project is investigating whether it is possible to use computational fragment-based drug design to identify fragments that might serve as starting points for further optimisation. The proposed method utilises metadynamics of the protein in combination with a number of small fragments in an explicit water box. The validity of the method will be tested on three 'real-world' protein targets, including dipeptidylpeptidase 4 (DPP4), DPP8 and DPP9. The crystal structures of these three dimeric enzymes have been determined, and at UAMC we have synthesized a large number of inhibitors and have biochemically characterized their corresponding cross-reactivities (selectivities), hence allowing us to evaluate whether computational fragment-based design can be modified to address selectivity issues within the drug design cycle.
Date:1 Nov 2020 →  Today
Keywords:MOLECULAR DYNAMICS, MEDICINAL CHEMISTRY, DRUG DESIGN, COMPUTATIONAL CHEMISTRY
Disciplines:Cheminformatics, Compound screening, Biomolecular modelling and design, Medicinal chemistry