Computer-aided drug design (CADD) has emerged as a powerful tool to streamline the time and resource intensive drug discovery process. CADD can be exploited to expedite the search through chemical space to promote the design, development and optimization of drug lead candidates. The work described herein involves the development of state-of-the-art computational drug discovery methods, comprising novel molecular generation techniques combined with explicit hydration thermodynamics based on Grid Inhomogeneous Solvation Theory (GIST) methodology. This revolutionary new protocol was applied to design novel, tightly binding drug candidates towards key protein targets of therapeutic relevance, including Dopamine D3 and Caspase 3 protein targets that are involved in neurological, cancer and autoimmune conditions. Analogues of known lead scaffolds were rationally designed and predicted to bind with significantly higher affinity to the relevant protein targets, due to the displacement of thermodynamically unfavorable water molecules from the binding cavity. Experimental results from the synthesis and assays of the relevant analogues will be integrated into the drug design process to validate and improve the computational predictions in an iterative scheme.

De novo design of drug lead candidates towards targets involved in neurological, cancer, and autoimmune conditions

248th National Meeting (2014)

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