Developing an in silico pipeline for faster drug candidate discovery: Virtual high throughput screening with the Signature molecular descriptor using support vector machine models

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• 作者：Jonathan Jun Feng Chen^a ; Donald Patrick Visco Jr.^b
• 关键词：Virtual high throughput screening ; QSAR ; Drug discovery ; CAMD ; Signature
• 刊名：Chemical Engineering Science
• 出版年：2017
• 出版时间：23 February 2017
• 年：2017
• 卷：159
• 期：Complete
• 页码：31-42
• 全文大小：1432 K
• 卷排序：159

文摘

Created SVM models using PCA as a filter and GA as a wrapper with the Signature molecular descriptor. Used Cathepsin-L as proof-of-concept for virtual high-throughput screening. Screened PubChem Compound Database and experimentally evaluated predicted inhibitors. First-pass through algorithm yielded a 19% hit rate. Second-pass through algorithm yielded a 75% hit rate.