Comparing a Query Compound with Drug Target Classes Using 3D-Chemical Similarity.

ABSTRACT: 3D similarity is useful in predicting the profiles of unprecedented molecular frameworks that are 2D dissimilar to known compounds. When comparing pairs of compounds, 3D similarity of the pairs depends on conformational sampling, the alignment method, the chosen descriptors, and the similarity coefficients. In addition to these four factors, 3D chemocentric target prediction of an unknown compound requires compound-target associations, which replace compound-to-compound comparisons with compound-to-target comparisons. In this study, quantitative comparison of query compounds to target classes (one-to-group) was achieved via two types of 3D similarity distributions for the respective target class with parameter optimization for the fitting models: (1) maximum likelihood (ML) estimation of q

SUBMITTER: Lee SH 

PROVIDER: S-EPMC7352980 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature