Network-based piecewise linear regression for QSAR modelling.

ABSTRACT: Quantitative Structure-Activity Relationship (QSAR) models are critical in various areas of drug discovery, for example in lead optimisation and virtual screening. Recently, the need for models that are not only predictive but also interpretable has been highlighted. In this paper, a new methodology is proposed to build interpretable QSAR models by combining elements of network analysis and piecewise linear regression. The algorithm presented, modSAR, splits data using a two-step procedure. First, compounds associated with a common target are represented as a network in terms of their structural similarity, revealing modules of similar chemical properties. Second, each module is subdivided into subsets (regions), each of which is modelled by an independent linear equation. Comparative anal

SUBMITTER: Cardoso-Silva J 

PROVIDER: S-EPMC6825651 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature