Exploring non-linear distance metrics in the structure-activity space: QSAR models for human estrogen receptor.

ABSTRACT:

Background

Quantitative structure-activity relationship (QSAR) models are important tools used in discovering new drug candidates and identifying potentially harmful environmental chemicals. These models often face two fundamental challenges: limited amount of available biological activity data and noise or uncertainty in the activity data themselves. To address these challenges, we introduce and explore a QSAR model based on custom distance metrics in the structure-activity space.

Methods

The model is built on top of the k-nearest neighbor model, incorporating non-linearity not only in the chemical structure space, but also in the biological activity space. The model is tuned and evaluated using activity data for human estrogen receptor from the US EPA ToxCast and Tox21 dat

SUBMITTER: Balabin IA 

PROVIDER: S-EPMC6755572 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature