Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning-Reference-Cited by-同舟云学术

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Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning

Published:2018-12-12 Issue:3 Volume:59 Page:1147-1162
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Brocke Stephanie A.¹,Degen Alexandra¹,MacKerell Alexander D.²³^ORCID,Dutagaci Bercem¹^ORCID,Feig Michael¹^ORCID

Affiliation:

1. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States

2. Department of Pharmaceutical Sciences, University of Maryland, School of Pharmacy, Baltimore, Maryland 21201, United States

3. University of Maryland Computer-Aided Drug Design Center, Baltimore, Maryland 21201, United States

Funder

Division of Molecular and Cellular Biosciences

Michigan State University

National Institutes of Health

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00648

Reference88 articles.

1. Drug interactions with lipid membranes

2. Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells

3. MDCK (Madin-Darby Canine Kidney) Cells: A Tool for Membrane Permeability Screening

4. Physicochemical High Throughput Screening: Parallel Artificial Membrane Permeation Assay in the Description of Passive Absorption Processes

5. Prediction of Drug Absorption Using Multivariate Statistics

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