Docking scores and QSAR using evolved neural networks for the Pan-inhibition of wild-type and mutant PfDHFR by cycloguanil derivatives
作者： David Hecht , Mars Cheung , Gary B. Fogel
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摘要: Linear and nonlinear quantitative structure-activity relationship (QSAR) models docking score functions were developed for dihydrofolate reductase (DHFR) inhibition by cycloguanil derivatives using small molecule descriptors derived from MOE in silico energies. The best QSAR identified when artificial neural networks optimized evolutionary computation. resulting can be used to identify key DHFR are useful high-throughput screening of novel drug compounds.
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