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AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants
Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and “drug-likeness” of a relatively small but structurally diverse dataset (containing >1,000 compounds)...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3813505/ https://www.ncbi.nlm.nih.gov/pubmed/24205103 http://dx.doi.org/10.1371/journal.pone.0078085 |
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author | Ntie-Kang, Fidele Zofou, Denis Babiaka, Smith B. Meudom, Rolande Scharfe, Michael Lifongo, Lydia L. Mbah, James A. Mbaze, Luc Meva’a Sippl, Wolfgang Efange, Simon M. N. |
author_facet | Ntie-Kang, Fidele Zofou, Denis Babiaka, Smith B. Meudom, Rolande Scharfe, Michael Lifongo, Lydia L. Mbah, James A. Mbaze, Luc Meva’a Sippl, Wolfgang Efange, Simon M. N. |
author_sort | Ntie-Kang, Fidele |
collection | PubMed |
description | Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and “drug-likeness” of a relatively small but structurally diverse dataset (containing >1,000 compounds) from African medicinal plants, which have been tested and proven a wide range of biological activities. The geographical regions of collection of the medicinal plants cover the entire continent of Africa, based on data from literature sources and information from traditional healers. For each isolated compound, the three dimensional (3D) structure has been used to calculate physico-chemical properties used in the prediction of oral bioavailability on the basis of Lipinski’s “Rule of Five”. A comparative analysis has been carried out with the “drug-like”, “lead-like”, and “fragment-like” subsets, as well as with the Dictionary of Natural Products. A diversity analysis has been carried out in comparison with the ChemBridge diverse database. Furthermore, descriptors related to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been used to predict the pharmacokinetic profile of the compounds within the dataset. Our results prove that drug discovery, beginning with natural products from the African flora, could be highly promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs. |
format | Online Article Text |
id | pubmed-3813505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38135052013-11-07 AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants Ntie-Kang, Fidele Zofou, Denis Babiaka, Smith B. Meudom, Rolande Scharfe, Michael Lifongo, Lydia L. Mbah, James A. Mbaze, Luc Meva’a Sippl, Wolfgang Efange, Simon M. N. PLoS One Research Article Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We assess the bioactivity and “drug-likeness” of a relatively small but structurally diverse dataset (containing >1,000 compounds) from African medicinal plants, which have been tested and proven a wide range of biological activities. The geographical regions of collection of the medicinal plants cover the entire continent of Africa, based on data from literature sources and information from traditional healers. For each isolated compound, the three dimensional (3D) structure has been used to calculate physico-chemical properties used in the prediction of oral bioavailability on the basis of Lipinski’s “Rule of Five”. A comparative analysis has been carried out with the “drug-like”, “lead-like”, and “fragment-like” subsets, as well as with the Dictionary of Natural Products. A diversity analysis has been carried out in comparison with the ChemBridge diverse database. Furthermore, descriptors related to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been used to predict the pharmacokinetic profile of the compounds within the dataset. Our results prove that drug discovery, beginning with natural products from the African flora, could be highly promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs. Public Library of Science 2013-10-30 /pmc/articles/PMC3813505/ /pubmed/24205103 http://dx.doi.org/10.1371/journal.pone.0078085 Text en © 2013 Ntie-Kang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ntie-Kang, Fidele Zofou, Denis Babiaka, Smith B. Meudom, Rolande Scharfe, Michael Lifongo, Lydia L. Mbah, James A. Mbaze, Luc Meva’a Sippl, Wolfgang Efange, Simon M. N. AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title | AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title_full | AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title_fullStr | AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title_full_unstemmed | AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title_short | AfroDb: A Select Highly Potent and Diverse Natural Product Library from African Medicinal Plants |
title_sort | afrodb: a select highly potent and diverse natural product library from african medicinal plants |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3813505/ https://www.ncbi.nlm.nih.gov/pubmed/24205103 http://dx.doi.org/10.1371/journal.pone.0078085 |
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