Computational chemistry in drug lead discovery and design

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Abstract

The main contributions of our group during the last 15 years developing and using biomolecular simulation tools in drug lead discovery and design, in close collaboration with experimental researchers, are presented. Special emphasis has been given to methodological improvements in the following areas: (1) target homology modeling incorporating knowledge about known ligands to accurately characterize the binding site; (2) designing alternative strategies to account for protein flexibility in high-throughput docking; (3) development of stochastic- and normal-mode-based methods to de novo design structurally diverse protein conformers; (4) development and validation of quantum mechanical semi-empirical linear-scaling calculations to correctly estimate ligand binding free energy. Several successful cases of computer-aided drug discovery are also presented, especially our recent work on viral targets.

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Cavasotto, C. N., Aucar, M. G., & Adler, N. S. (2019, January 15). Computational chemistry in drug lead discovery and design. International Journal of Quantum Chemistry. John Wiley and Sons Inc. https://doi.org/10.1002/qua.25678

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