期刊
JOURNAL OF MEDICINAL CHEMISTRY
卷 59, 期 9, 页码 4077-4086出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jmedchem.5b01849
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资金
- ETH Zurich
- inSili.com LLC.
Computational medicinal chemistry offers viable strategies for finding, characterizing, and optimizing innovative pharmacologically active compounds. Technological advances in both computer hardware and software as well as biological chemistry have enabled a renaissance of computer-assisted de novo design of molecules with desired pharmacological properties. Here, we present our current perspective on the concept of automated molecule generation by highlighting chemocentric methods that may capture druglike chemical space, consider ligand promiscuity for hit and lead finding, and provide fresh ideas for the rational design of customized screening of compound libraries.
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