https://pubs.acs.org/doi/10.1021/acs.jcim.6c01496
Searching in ultralarge Chemical Spaces with known 2D similarity metrics, like fingerprint-based Tanimoto, substructure, or pharmacophore similarity searches, contains pitfalls due to the representation of molecules as synthons with connectivity rules.
Applied to a set of almost 3000 drug-relevant queries we analyzed the ability of similarity search methods to retrieve analog compounds from Chemical Spaces, and how to best approach typical use cases in early phase drug discovery. Distinct characteristics of each similarity metric suggest orthogonal complementarity, enabling a versatile framework to diverse challenges present in hit discovery and lead expansion campaigns.
📕Journal of Chemical Information and Modeling (IF=6.4)