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