Molecular Descriptors for Drugs: A Discriminant Analysis
Liza Tybaco Billones, Alex Gonzaga, Junie B. Billones · Philippine Journal of Health Research and Development · 2019
Background: The biological activity of a compound is assumed to be encoded in its chemical composition and geometric structure, from which physico-chemical, electrotopological, and graph theory-derived properties can be determined. Objective: This study aimed to identify the molecular descriptors derived from Dragon® 6 software that can discriminate compounds as drug or nondrug. Methodology: Over 4000 molecular properties were obtained for approximately 2000 known drugs and 2000 nondrugs on which Linear Discriminant Analysis was performed. Results: Compounds can be discriminated between drug and nondrug with 81% accuracy using only two molecular descriptors, the information index HVcpx and the topological index MDDD. Conclusion: A "Rule of Three" (HVcpx ≤ 3 and MDDD ≥ 30) seems to confer druglikeness in compounds. This rule can be used as additional filter in high throughput screening of compounds in any drug discovery research.