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ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to ab...

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Autores principales: Dong, Jie, Wang, Ning-Ning, Yao, Zhi-Jiang, Zhang, Lin, Cheng, Yan, Ouyang, Defang, Lu, Ai-Ping, Cao, Dong-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020094/
https://www.ncbi.nlm.nih.gov/pubmed/29943074
http://dx.doi.org/10.1186/s13321-018-0283-x
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author Dong, Jie
Wang, Ning-Ning
Yao, Zhi-Jiang
Zhang, Lin
Cheng, Yan
Ouyang, Defang
Lu, Ai-Ping
Cao, Dong-Sheng
author_facet Dong, Jie
Wang, Ning-Ning
Yao, Zhi-Jiang
Zhang, Lin
Cheng, Yan
Ouyang, Defang
Lu, Ai-Ping
Cao, Dong-Sheng
author_sort Dong, Jie
collection PubMed
description Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/. [Image: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-018-0283-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-60200942018-07-13 ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database Dong, Jie Wang, Ning-Ning Yao, Zhi-Jiang Zhang, Lin Cheng, Yan Ouyang, Defang Lu, Ai-Ping Cao, Dong-Sheng J Cheminform Software Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/. [Image: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-018-0283-x) contains supplementary material, which is available to authorized users. Springer International Publishing 2018-06-26 /pmc/articles/PMC6020094/ /pubmed/29943074 http://dx.doi.org/10.1186/s13321-018-0283-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Dong, Jie
Wang, Ning-Ning
Yao, Zhi-Jiang
Zhang, Lin
Cheng, Yan
Ouyang, Defang
Lu, Ai-Ping
Cao, Dong-Sheng
ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title_full ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title_fullStr ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title_full_unstemmed ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title_short ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
title_sort admetlab: a platform for systematic admet evaluation based on a comprehensively collected admet database
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020094/
https://www.ncbi.nlm.nih.gov/pubmed/29943074
http://dx.doi.org/10.1186/s13321-018-0283-x
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