Computational chemistry in drug lead discovery and design

被引:52
|
作者
Cavasotto, Claudio N. [1 ]
Gabriela Aucar, Maria [1 ]
Adler, Natalia S. [1 ]
机构
[1] Consejo Nacl Invest Cient & Tecn, Lab Computat Chem & Drug Design, Inst Invest Biomed Buenos Aires, Partner Inst,Max Planck Soc, Godoy Cruz 2390,C1425FQD, Buenos Aires, DF, Argentina
关键词
binding free energy; homology modeling; molecular docking; semi-empirical calculations; structure-based drug discovery; PROTEIN-COUPLED RECEPTOR; VAN-DER-WAALS; BINDING FREE-ENERGY; VIRAL DIARRHEA INHIBITORS; STRUCTURE-BASED LIGAND; EQUATION-OF-STATE; HIGH-THROUGHPUT; TARGET FLEXIBILITY; CATALYTIC SUBUNIT; CRYSTAL-STRUCTURE;
D O I
10.1002/qua.25678
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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.
引用
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页数:19
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