Medicinal Chemistry Data for
QSAR modeling & drug discovery
Quantitative structure-activity relationship (QSAR) is a computational modeling method for revealing relationships between structural properties of chemical compounds and biological activities. When used with machine learning approaches, it decreases the number of compounds to be synthesized by facilitating the selection of the most promising candidates.
A critical bottleneck in QSAR modeling for drug discovery is the availability of high-quality, clean, annotated datasets on which to train algorithms and search for novel compounds. GOSTAR provides a massive, normalized, thoroughly quality-controlled data set that is available in part or in its entirety as a flat file. With the ability to connect via API, GOSTAR can seamlessly integrate into your systems, providing a continuously updated stream of bioactivity information. GOSTAR is uniquely suited to the needs of today’s AI / ML-based drug discovery programs.