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Computational study of novel natural inhibitors targeting aminopeptidase N(CD13)
Objectives: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development. Results: Two novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 databa...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244087/ https://www.ncbi.nlm.nih.gov/pubmed/32388498 http://dx.doi.org/10.18632/aging.103155 |
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author | Ge, Junliang Wang, Zhongfeng Cheng, Ye Ren, Junan Wu, Bo Li, Weihang Wang, Xinhui Shu, Xing Liu, Ziling |
author_facet | Ge, Junliang Wang, Zhongfeng Cheng, Ye Ren, Junan Wu, Bo Li, Weihang Wang, Xinhui Shu, Xing Liu, Ziling |
author_sort | Ge, Junliang |
collection | PubMed |
description | Objectives: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development. Results: Two novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 database were found to have a higher binding affinity and more favorable interaction energy binding with CD13 with less rodent carcinogenicity, Ames mutagenicity, and non-inhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis suggested that the 2 complexes, ZINC000000895551-CD13 and ZINC000014820583-CD13, have favorable potential energy, and exist stably in the natural circumstances. Conclusion: This study discovered that ZINC000000895551 and ZINC000014820583 were ideal leading compounds to be inhibitions targeting to CD13. These compounds were selected as safe drug candidates as CD13 target medication design and improvement. Materials and Method: Potential inhibitors of CD13 were identified using a series of computer-aided structural and chemical virtual screening techniques. Structure-based virtual screening was carried out to calculate LibDock scores, followed by analyzing their absorption, distribution, metabolism, and excretion and toxicity predictions. Molecule docking was employed to reveal binding affinity between the selected compounds and CD13. Molecular dynamics simulation was applied to evaluate stability of the ligand-CD13 complex under natural environment. |
format | Online Article Text |
id | pubmed-7244087 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-72440872020-06-03 Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) Ge, Junliang Wang, Zhongfeng Cheng, Ye Ren, Junan Wu, Bo Li, Weihang Wang, Xinhui Shu, Xing Liu, Ziling Aging (Albany NY) Research Paper Objectives: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development. Results: Two novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 database were found to have a higher binding affinity and more favorable interaction energy binding with CD13 with less rodent carcinogenicity, Ames mutagenicity, and non-inhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis suggested that the 2 complexes, ZINC000000895551-CD13 and ZINC000014820583-CD13, have favorable potential energy, and exist stably in the natural circumstances. Conclusion: This study discovered that ZINC000000895551 and ZINC000014820583 were ideal leading compounds to be inhibitions targeting to CD13. These compounds were selected as safe drug candidates as CD13 target medication design and improvement. Materials and Method: Potential inhibitors of CD13 were identified using a series of computer-aided structural and chemical virtual screening techniques. Structure-based virtual screening was carried out to calculate LibDock scores, followed by analyzing their absorption, distribution, metabolism, and excretion and toxicity predictions. Molecule docking was employed to reveal binding affinity between the selected compounds and CD13. Molecular dynamics simulation was applied to evaluate stability of the ligand-CD13 complex under natural environment. Impact Journals 2020-05-09 /pmc/articles/PMC7244087/ /pubmed/32388498 http://dx.doi.org/10.18632/aging.103155 Text en Copyright © 2020 Ge et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Ge, Junliang Wang, Zhongfeng Cheng, Ye Ren, Junan Wu, Bo Li, Weihang Wang, Xinhui Shu, Xing Liu, Ziling Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title | Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title_full | Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title_fullStr | Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title_full_unstemmed | Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title_short | Computational study of novel natural inhibitors targeting aminopeptidase N(CD13) |
title_sort | computational study of novel natural inhibitors targeting aminopeptidase n(cd13) |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244087/ https://www.ncbi.nlm.nih.gov/pubmed/32388498 http://dx.doi.org/10.18632/aging.103155 |
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