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Novel In Silico Approach to Drug Discovery via Computational Intelligence
被引:17
|作者:
Hecht, David
[1
]
Fogel, Gary B.
[2
]
机构:
[1] Southwestern Coll, Chula Vista, CA 91910 USA
[2] Nat Select Inc, San Diego, CA 92121 USA
关键词:
DE-NOVO DESIGN;
FALCIPARUM DIHYDROFOLATE-REDUCTASE;
QUANTITATIVE STRUCTURE-ACTIVITY;
COMBINATORIAL CHEMISTRY;
LIGAND DESIGN;
CANDIDATE STRUCTURES;
GENETIC ALGORITHM;
HIGH-THROUGHPUT;
LEAD DISCOVERY;
BINDING-SITES;
D O I:
10.1021/ci9000647
中图分类号:
R914 [药物化学];
学科分类号:
100701 ;
摘要:
A computational intelligence drug discovery platform is introduced as an innovative technology designed to accelerate high-throughput drug screening for generalized protein-targeted drug discovery. This technology results in collections of novel small molecule compounds that bind to protein targets as well as details on predicted binding modes and molecular interactions. The approach was tested on dihydrofolate reductase (DHFR) for novel antimalarial drug discovery; however, the methods developed can be applied broadly in early stage drug discovery and development. For this purpose, an initial fragment library was defined, and an automated fragment assembly algorithm was generated. These were combined with a computational intelligence screening tool for prescreening of compounds relative to DHFR inhibition. The entire method was assayed relative to spaces of known DHFR inhibitors and with chemical feasibility in mind, leading to experimental validation in future studies.
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页码:1105 / 1121
页数:17
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