Tree-Based QSAR Model for Drug Repurposing in the Discovery of New Antibacterial Compounds Against Escherichia coli.

ABSTRACT: Drug repurposing appears as an increasing popular tool in the search of new treatment options against bacteria. In this paper, a tree-based classification method using Linear Discriminant Analysis (LDA) and discrete indexes was used to create a QSAR (Quantitative Structure-Activity Relationship) model to predict antibacterial activity against Escherichia coli. The model consists on a hierarchical decision tree in which a discrete index is used to divide compounds into groups according to their values for said index in order to construct probability spaces. The second step consists in the calculation of a discriminant function which determines the prediction of the model. The model was used to screen the DrugBank database, identifying 134 drugs as possible antibacterial candidates. Out of t

SUBMITTER: Suay-Garcia B 

PROVIDER: S-EPMC7760995 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature