Accelerating drug discovery through tight integration of expert molecular design and predictive scoring

被引：49

作者：

Abel, Robert ^{[1
]}

Mondal, Sayan ^{[1
]}

Masse, Craig ^{[2
]}

Greenwood, Jeremy ^{[1
]}

Harriman, Geraldine ^{[2
]}

Ashwell, Mark A. ^{[2
]}

Bhat, Sathesh ^{[1
]}

Wester, Ronald ^{[2
]}

Frye, Leah ^{[1
]}

Kapeller, Rosana ^{[2
]}

Friesner, Richard A. ^{[3
]}

机构：

[1] Schrodinger Inc, New York, NY 10036 USA

[2] Nimbus Therapeut, Cambridge, MA 02141 USA

[3] Columbia Univ, Dept Chem, New York, NY 10027 USA

来源：

CURRENT OPINION IN STRUCTURAL BIOLOGY | 2017年 / 43卷

关键词：

FREE-ENERGY CALCULATIONS; FATTY-ACID OXIDATION; PROTEIN-LIGAND-BINDING; COENZYME-A CARBOXYLASE; ACETYL-COA CARBOXYLASE-2; CARBOXYLTRANSFERASE DOMAIN; HYDROPHOBIC ENCLOSURE; CRYSTAL-STRUCTURE; REPLICA EXCHANGE; INHIBITORS;

D O I：

10.1016/j.sbi.2016.10.007

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Modeling protein-ligand interactions has been a central goal of computational chemistry for many years. We here review recent progress toward this goal, and highlight the role free energy calculation methods and computational solvent analysis techniques are now having in drug discovery. We further describe recent use of these methodologies to advance two separate drug discovery programs targeting acetyl-CoA carboxylase and tyrosine kinase 2. These examples suggest that tight integration of sophisticated chemistry teams with state-of-the-art computational methods can dramatically improve the efficiency of small molecule drug discovery.

引用

页码：38 / 44

页数：7

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