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The use of computer-aided drug design methodology to target DNA-protein, RNA-protein and protein-protein interactions implicated in cancer

University of British Columbia

Modern drug discovery is broadly facilitated by the use of various computational tools and techniques. These enable to significantly reduce the cost and amount of time required to identify drug candidates. The development of cancer therapeutics has particularly benefited from the rise of the field of computer-aided drug design (CADD). Herein we present several practical examples of the development of small molecule-inhibitors of three types of cancer drug targets (protein-protein, protein-DNA and protein-RNA interaction interfaces) with the use of CADD tools. First, a protein-DNA interaction targeting is demonstrated with the case of DNA Topoisomerase II (TopoII). In Chapter II, a comprehensive overview of computational studies on the development of TopoII inhibitors is provided. We then discuss computational validation of the proposed mode of action and optimization of a promising catalytic inhibitor of TopoII called T60. Second, we identified inhibitors of an RNA-protein interaction Lin28-let-7. The virtual screening used in this work resulted in a particularly high 18% hit-rate supporting the utility of CADD methodology. Third, we employed homology modelling and virtual screening to discover inhibitors of a protein-protein complex, Siah1-UBC13. The hit molecule exhibited a similar activity profile to a drug candidate that was previously found in an in vitro screening of several thousand chemicals. This exemplifies the cost efficiency of in silico screens compared to in vitro. Altogether, the presented results demonstrate the broad utility of CADD methodology in precision cancer drug discovery.

Text

2023-02-28

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/75749

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/