Cargando…

Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models

Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes...

Descripción completa

Detalles Bibliográficos
Autores principales: Siramshetty, Vishal B., Shah, Pranav, Kerns, Edward, Nguyen, Kimloan, Yu, Kyeong Ri, Kabir, Md, Williams, Jordan, Neyra, Jorge, Southall, Noel, Nguyễn, Ðắc-Trung, Xu, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693334/
https://www.ncbi.nlm.nih.gov/pubmed/33244000
http://dx.doi.org/10.1038/s41598-020-77327-0
_version_ 1783614720259915776
author Siramshetty, Vishal B.
Shah, Pranav
Kerns, Edward
Nguyen, Kimloan
Yu, Kyeong Ri
Kabir, Md
Williams, Jordan
Neyra, Jorge
Southall, Noel
Nguyễn, Ðắc-Trung
Xu, Xin
author_facet Siramshetty, Vishal B.
Shah, Pranav
Kerns, Edward
Nguyen, Kimloan
Yu, Kyeong Ri
Kabir, Md
Williams, Jordan
Neyra, Jorge
Southall, Noel
Nguyễn, Ðắc-Trung
Xu, Xin
author_sort Siramshetty, Vishal B.
collection PubMed
description Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes (RLM) is employed at the National Center for Advancing Translational Sciences. Between 2012 and 2020, RLM stability data was generated for ~ 24,000 compounds from more than 250 projects that cover a wide range of pharmacological targets and cellular pathways. Although a crucial endpoint, little or no data exists in the public domain. In this study, computational models were developed for predicting RLM stability using different machine learning methods. In addition, a retrospective time-split validation was performed, and local models were built for projects that performed poorly with global models. Further analysis revealed inherent medicinal chemistry knowledge potentially useful to chemists in the pursuit of synthesizing metabolically stable compounds. In addition, we deposited experimental data for ~ 2500 compounds in the PubChem bioassay database (AID: 1508591). The global prediction models are made publicly accessible (https://opendata.ncats.nih.gov/adme). This is to the best of our knowledge, the first publicly available RLM prediction model built using high-quality data generated at a single laboratory.
format Online
Article
Text
id pubmed-7693334
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-76933342020-11-30 Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models Siramshetty, Vishal B. Shah, Pranav Kerns, Edward Nguyen, Kimloan Yu, Kyeong Ri Kabir, Md Williams, Jordan Neyra, Jorge Southall, Noel Nguyễn, Ðắc-Trung Xu, Xin Sci Rep Article Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes (RLM) is employed at the National Center for Advancing Translational Sciences. Between 2012 and 2020, RLM stability data was generated for ~ 24,000 compounds from more than 250 projects that cover a wide range of pharmacological targets and cellular pathways. Although a crucial endpoint, little or no data exists in the public domain. In this study, computational models were developed for predicting RLM stability using different machine learning methods. In addition, a retrospective time-split validation was performed, and local models were built for projects that performed poorly with global models. Further analysis revealed inherent medicinal chemistry knowledge potentially useful to chemists in the pursuit of synthesizing metabolically stable compounds. In addition, we deposited experimental data for ~ 2500 compounds in the PubChem bioassay database (AID: 1508591). The global prediction models are made publicly accessible (https://opendata.ncats.nih.gov/adme). This is to the best of our knowledge, the first publicly available RLM prediction model built using high-quality data generated at a single laboratory. Nature Publishing Group UK 2020-11-26 /pmc/articles/PMC7693334/ /pubmed/33244000 http://dx.doi.org/10.1038/s41598-020-77327-0 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Siramshetty, Vishal B.
Shah, Pranav
Kerns, Edward
Nguyen, Kimloan
Yu, Kyeong Ri
Kabir, Md
Williams, Jordan
Neyra, Jorge
Southall, Noel
Nguyễn, Ðắc-Trung
Xu, Xin
Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title_full Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title_fullStr Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title_full_unstemmed Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title_short Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models
title_sort retrospective assessment of rat liver microsomal stability at ncats: data and qsar models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693334/
https://www.ncbi.nlm.nih.gov/pubmed/33244000
http://dx.doi.org/10.1038/s41598-020-77327-0
work_keys_str_mv AT siramshettyvishalb retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT shahpranav retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT kernsedward retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT nguyenkimloan retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT yukyeongri retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT kabirmd retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT williamsjordan retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT neyrajorge retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT southallnoel retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT nguyenðactrung retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels
AT xuxin retrospectiveassessmentofratlivermicrosomalstabilityatncatsdataandqsarmodels