info:eu-repo/semantics/article
Computational chemistry in drug lead discovery and design
Fecha
2019-01Registro en:
Cavasotto, Claudio Norberto; Aucar, María Gabriela; Adler, Natalia Sol; Computational chemistry in drug lead discovery and design; John Wiley & Sons Inc.; International Journal of Quantum Chemistry; 119; 2; 1-2019; 1-19
0020-7608
1097-461X
CONICET Digital
CONICET
Autor
Cavasotto, Claudio Norberto
Aucar, María Gabriela
Adler, Natalia Sol
Resumen
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.