Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules-Reference-Cited by-同舟云学术

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules

Published:2023-09-08 Issue:18 Volume:63 Page:5903-5915
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Pandey Poonam¹,MacKerell Alexander D.¹^ORCID

Affiliation:

1. Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., HSF II-633, Baltimore, Maryland 21201, United States

Funder

National Institute of General Medical Sciences

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.3c00514

Reference94 articles.

1. Introduction to Biopharmaceutics Measures

2. Molecular simulation of nonfacilitated membrane permeation

3. Coexistence of passive and carrier-mediated processes in drug transport

4. Evidence-based approach to assess passive diffusion and carrier-mediated drug transport

5. Passive Lipoidal Diffusion and Carrier-Mediated Cell Uptake Are Both Important Mechanisms of Membrane Permeation in Drug Disposition

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