title: PXR ligand classification model with SFED-weighted WHIM and CoMMA descriptors.
abstract: Understanding which type of endogenous and exogenous compounds serve as agonists for the nuclear pregnane X receptor (PXR) would be valuable for drug discovery and development, because PXR regulates a large number of genes related to xenobiotic metabolism. Although several models have been proposed to classify human PXR activators and non-activators, models with better predictability are necessary for practical purposes in drug discovery. Grid-weighted holistic invariant molecular (G-WHIM) and comparative molecular moment analysis (G-CoMMA) type 3D descriptors that contain information about the solvation free energy of target molecules were developed. With these descriptors, prediction models built using decision tree (DT)-, support vector machine (SVM)-, and Kohonen neural network (KNN)-based models exhibited better predictability than previously proposed models. Solvation free energy density-weighted G-WHIM and G-CoMMA descriptors reveal new insights into PXR ligand classification, and incorporation with machine learning methods (DT, SVM, KNN) exhibits promising results, especially SVM and KNN. SVM- and KNN-based models exhibit accuracy around 0.90, and DT-based models exhibit accuracy around 0.8 for both the training and test sets.
authors.affiliation: Department of Biotechnology, Yonsei University, Seoul, Korea.
authors.forename: S L
authors.initials: SL
authors.lastname: Ma
authors.forename: J Y
authors.initials: JY
authors.lastname: Joung
authors.forename: S
authors.initials: S
authors.lastname: Lee
authors.forename: K H
authors.initials: KH
authors.lastname: Cho
authors.forename: K T
authors.initials: KT
authors.lastname: No
mesh_terms: D001185:Artificial Intelligence; D003663:Decision Trees; D055808:Drug Discovery / Q000379:methods*; D008024:Ligands; D008958:Models, Molecular; D016571:Neural Networks, Computer; D000077297:Pregnane X Receptor; D021281:Quantitative Structure-Activity Relationship; D011987:Receptors, Steroid / Q000819:agonists / Q000737:chemistry*; D060388:Support Vector Machine
chemical_list: D008024:Ligands; D000077297:Pregnane X Receptor; D011987:Receptors, Steroid