title: Exploring in silico prediction of the unbound brain-to-plasma drug concentration ratio: model validation, renewal, and interpretation.
abstract: Recently, we built an in silico model to predict the unbound brain-to-plasma concentration ratio (Kp,uu,brain), a measure of the distribution of a compound between the blood plasma and the brain. Here, we validate the previous model with new additional data points expanding the chemical space and use that data also to renew the model. The model building process was similar to our previous approach; however, a new set of descriptors, molecular signatures, was included to facilitate the model interpretation from a structure perspective. The best consensus model shows better predictive power than the previous model (R(2) = 0.6 vs. R(2) = 0.53, when the same 99 compounds were used as test set). The two-class classification accuracy increased from 76% using the previous model to 81%. Furthermore, the atom-summarized gradient based on molecular signature descriptors was proposed as an interesting new approach to interpret the Kp,uu,brain machine learning model and scrutinize structure Kp,uu,brain relationships for investigated compounds.
authors.affiliation: Department of Biology, Lund University, Lund, SE-22100, Sweden; Chemistry Innovation Centre, Discovery Sciences, AstraZeneca R&D Mölndal, Mölndal, SE-43183, Sweden.
authors.forename: Srinidhi
authors.initials: S
authors.lastname: Varadharajan
authors.forename: Susanne
authors.initials: S
authors.lastname: Winiwarter
authors.forename: Lars
authors.initials: L
authors.lastname: Carlsson
authors.forename: Ola
authors.initials: O
authors.lastname: Engkvist
authors.forename: Ajay
authors.initials: A
authors.lastname: Anantha
authors.forename: Thierry
authors.initials: T
authors.lastname: Kogej
authors.forename: Markus
authors.initials: M
authors.lastname: Fridén
authors.forename: Jonna
authors.initials: J
authors.lastname: Stålring
authors.forename: Hongming
authors.initials: H
authors.lastname: Chen
mesh_terms: D000818:Animals; D001812:Blood-Brain Barrier / Q000378:metabolism*; D002199:Capillary Permeability; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000008:administration & dosage / Q000097:blood*; D010599:Pharmacokinetics; D011485:Protein Binding; D015203:Reproducibility of Results; D060388:Support Vector Machine
chemical_list: D004364:Pharmaceutical Preparations
keywords: ADME; blood-brain barrier; computational ADME; drug transport; in silico modeling; machine learning; unbound brain-to-plasma concentration ratio