A visual approach for analysis and inference of molecular activity spaces.

ABSTRACT:

Background

Molecular space visualization can help to explore the diversity of large heterogeneous chemical data, which ultimately may increase the understanding of structure-activity relationships (SAR) in drug discovery projects. Visual SAR analysis can therefore be useful for library design, chemical classification for their biological evaluation and virtual screening for the selection of compounds for synthesis or in vitro testing. As such, computational approaches for molecular space visualization have become an important issue in cheminformatics research. The proposed approach uses molecular similarity as the sole input for computing a probabilistic surface of molecular activity (PSMA). This similarity matrix is transformed in 2D using different dimension reduction algorithms

SUBMITTER: Kausar S 

PROVIDER: S-EPMC6805449 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature