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Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening

Structural and biochemical studies elucidate that PA(N) may contribute to the host protein shutdown observed during influenza A infection. Thus, inhibition of the endonuclease activity of viral RdRP is an attractive approach for novel antiviral therapy. In order to envisage structurally diverse nove...

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Autores principales: Zhang, Chao, Xiang, Junjie, Xie, Qian, Zhao, Jing, Zhang, Hong, Huang, Erfang, Shaw, Pangchui, Liu, Xiaoping, Hu, Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659138/
https://www.ncbi.nlm.nih.gov/pubmed/34885710
http://dx.doi.org/10.3390/molecules26237129
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author Zhang, Chao
Xiang, Junjie
Xie, Qian
Zhao, Jing
Zhang, Hong
Huang, Erfang
Shaw, Pangchui
Liu, Xiaoping
Hu, Chun
author_facet Zhang, Chao
Xiang, Junjie
Xie, Qian
Zhao, Jing
Zhang, Hong
Huang, Erfang
Shaw, Pangchui
Liu, Xiaoping
Hu, Chun
author_sort Zhang, Chao
collection PubMed
description Structural and biochemical studies elucidate that PA(N) may contribute to the host protein shutdown observed during influenza A infection. Thus, inhibition of the endonuclease activity of viral RdRP is an attractive approach for novel antiviral therapy. In order to envisage structurally diverse novel compounds with better efficacy as PA(N) endonuclease inhibitors, a ligand-based-pharmacophore model was developed using 3D-QSAR pharmacophore generation (HypoGen algorithm) methodology in Discovery Studio. As the training set, 25 compounds were taken to generate a significant pharmacophore model. The selected pharmacophore Hypo1 was further validated by 12 compounds in the test set and was used as a query model for further screening of 1916 compounds containing 71 HIV-1 integrase inhibitors, 37 antibacterial inhibitors, 131 antiviral inhibitors and other 1677 approved drugs by the FDA. Then, six compounds (Hit01–Hit06) with estimated activity values less than 10 μM were subjected to ADMET study and toxicity assessment. Only one potential inhibitory ‘hit’ molecule (Hit01, raltegravir’s derivative) was further scrutinized by molecular docking analysis on the active site of PA(N) endonuclease (PDB ID: 6E6W). Hit01 was utilized for designing novel potential PA(N) endonuclease inhibitors through lead optimization, and then compounds were screened by pharmacophore Hypo1 and docking studies. Six raltegravir’s derivatives with significant estimated activity values and docking scores were obtained. Further, these results certainly do not confirm or indicate the seven compounds (Hit01, Hit07, Hit08, Hit09, Hit10, Hit11 and Hit12) have antiviral activity, and extensive wet-laboratory experimentation is needed to transmute these compounds into clinical drugs.
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spelling pubmed-86591382021-12-10 Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening Zhang, Chao Xiang, Junjie Xie, Qian Zhao, Jing Zhang, Hong Huang, Erfang Shaw, Pangchui Liu, Xiaoping Hu, Chun Molecules Article Structural and biochemical studies elucidate that PA(N) may contribute to the host protein shutdown observed during influenza A infection. Thus, inhibition of the endonuclease activity of viral RdRP is an attractive approach for novel antiviral therapy. In order to envisage structurally diverse novel compounds with better efficacy as PA(N) endonuclease inhibitors, a ligand-based-pharmacophore model was developed using 3D-QSAR pharmacophore generation (HypoGen algorithm) methodology in Discovery Studio. As the training set, 25 compounds were taken to generate a significant pharmacophore model. The selected pharmacophore Hypo1 was further validated by 12 compounds in the test set and was used as a query model for further screening of 1916 compounds containing 71 HIV-1 integrase inhibitors, 37 antibacterial inhibitors, 131 antiviral inhibitors and other 1677 approved drugs by the FDA. Then, six compounds (Hit01–Hit06) with estimated activity values less than 10 μM were subjected to ADMET study and toxicity assessment. Only one potential inhibitory ‘hit’ molecule (Hit01, raltegravir’s derivative) was further scrutinized by molecular docking analysis on the active site of PA(N) endonuclease (PDB ID: 6E6W). Hit01 was utilized for designing novel potential PA(N) endonuclease inhibitors through lead optimization, and then compounds were screened by pharmacophore Hypo1 and docking studies. Six raltegravir’s derivatives with significant estimated activity values and docking scores were obtained. Further, these results certainly do not confirm or indicate the seven compounds (Hit01, Hit07, Hit08, Hit09, Hit10, Hit11 and Hit12) have antiviral activity, and extensive wet-laboratory experimentation is needed to transmute these compounds into clinical drugs. MDPI 2021-11-25 /pmc/articles/PMC8659138/ /pubmed/34885710 http://dx.doi.org/10.3390/molecules26237129 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Chao
Xiang, Junjie
Xie, Qian
Zhao, Jing
Zhang, Hong
Huang, Erfang
Shaw, Pangchui
Liu, Xiaoping
Hu, Chun
Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title_full Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title_fullStr Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title_full_unstemmed Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title_short Identification of Influenza PA(N) Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening
title_sort identification of influenza pa(n) endonuclease inhibitors via 3d-qsar modeling and docking-based virtual screening
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659138/
https://www.ncbi.nlm.nih.gov/pubmed/34885710
http://dx.doi.org/10.3390/molecules26237129
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