Cargando…

Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing

OBJECTIVES: The comprehensive in silico study aims to figure out the most effective aromatic phytochemical ligands among a number from a library, considering their pharmacokinetic efficacies in blocking “angiotensin-converting enzyme 2 (ACE2) receptor–severe acute respiratory syndrome coronavirus 2...

Descripción completa

Detalles Bibliográficos
Autores principales: Dey, Dipta, Paul, Parag Kumar, Al Azad, Salauddin, Al Mazid, Mohammad Faysal, Khan, Arman Mahmud, Sharif, Md. Arman, Rahman, Md. Hafijur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: A periodical of the Network for the Veterinarians of Bangladesh (BDvetNET) 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043340/
https://www.ncbi.nlm.nih.gov/pubmed/33860009
http://dx.doi.org/10.5455/javar.2021.h481
_version_ 1783678285041893376
author Dey, Dipta
Paul, Parag Kumar
Al Azad, Salauddin
Al Mazid, Mohammad Faysal
Khan, Arman Mahmud
Sharif, Md. Arman
Rahman, Md. Hafijur
author_facet Dey, Dipta
Paul, Parag Kumar
Al Azad, Salauddin
Al Mazid, Mohammad Faysal
Khan, Arman Mahmud
Sharif, Md. Arman
Rahman, Md. Hafijur
author_sort Dey, Dipta
collection PubMed
description OBJECTIVES: The comprehensive in silico study aims to figure out the most effective aromatic phytochemical ligands among a number from a library, considering their pharmacokinetic efficacies in blocking “angiotensin-converting enzyme 2 (ACE2) receptor–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S protein” complex formation as part of a target-specific drug designing. MATERIALS AND METHODS: A library of 57 aromatic pharmacophore phytochemical ligands was prepared from where the top five ligands depending on Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) and quantitative structure-activity relationship (QSAR)-based pharmacokinetic properties were considered. The selected ligands were optimized for commencing molecular docking and dynamic simulation as a complex with the ACE2 receptor to compare their blocking efficacy with the control drug. The ligand–receptor complexes’ accuracy in preventing the Spike (S) protein of SARS-CoV-2 penetration inside the host cells has been analyzed through hydrogen–hydrophobic bond interactions, principal component analysis (PCA), root mean square deviation (RMSD), root mean square fluctuation (RMSF), and B-Factor. Advanced in silico programming language and bioanalytical software were used for high throughput and authentic results. RESULTS: ADMET and QSAR revealed Rhamnetin, Lactupicrin, Rhinacanthin D, Flemiflavanone D, and Exiguaflavanone A as the ligands of our interest to be compared with the control Cassiarin D. According to the molecular docking binding affinity to block ACE2 receptor, the efficiency mountings were Rhinacanthin D > Flemiflavanone D > Lactupicrin > Exiguaflavanone A > Rhamnetin. The binding affinity of the Cassiarin D–ACE2 complex was (−10.2 KJ/mol) found inferior to the Rhinacanthin D–ACE2 complex (−10.8 KJ/mol), referring to Rhinacanthin D as a more stable candidate to use as drugs. The RMSD values of protein–ligand complexes evaluated according to their structural conformation and stable binding pose ranged between 0.1~2.1 Å. The B-factor showed that very few loops were present in the protein structure. The RMSF peak fluctuation regions ranged 5–250, predicting efficient ligand–receptor interactions. CONCLUSION: The experiment sequentially measures all the parameters required in referring to any pharmacophore as a drug, considering which all aromatic components analyzed in the study can strongly be predicted as target-specific medication against the novel coronavirus 2019 infection.
format Online
Article
Text
id pubmed-8043340
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher A periodical of the Network for the Veterinarians of Bangladesh (BDvetNET)
record_format MEDLINE/PubMed
spelling pubmed-80433402021-04-14 Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing Dey, Dipta Paul, Parag Kumar Al Azad, Salauddin Al Mazid, Mohammad Faysal Khan, Arman Mahmud Sharif, Md. Arman Rahman, Md. Hafijur J Adv Vet Anim Res Original Article OBJECTIVES: The comprehensive in silico study aims to figure out the most effective aromatic phytochemical ligands among a number from a library, considering their pharmacokinetic efficacies in blocking “angiotensin-converting enzyme 2 (ACE2) receptor–severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S protein” complex formation as part of a target-specific drug designing. MATERIALS AND METHODS: A library of 57 aromatic pharmacophore phytochemical ligands was prepared from where the top five ligands depending on Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) and quantitative structure-activity relationship (QSAR)-based pharmacokinetic properties were considered. The selected ligands were optimized for commencing molecular docking and dynamic simulation as a complex with the ACE2 receptor to compare their blocking efficacy with the control drug. The ligand–receptor complexes’ accuracy in preventing the Spike (S) protein of SARS-CoV-2 penetration inside the host cells has been analyzed through hydrogen–hydrophobic bond interactions, principal component analysis (PCA), root mean square deviation (RMSD), root mean square fluctuation (RMSF), and B-Factor. Advanced in silico programming language and bioanalytical software were used for high throughput and authentic results. RESULTS: ADMET and QSAR revealed Rhamnetin, Lactupicrin, Rhinacanthin D, Flemiflavanone D, and Exiguaflavanone A as the ligands of our interest to be compared with the control Cassiarin D. According to the molecular docking binding affinity to block ACE2 receptor, the efficiency mountings were Rhinacanthin D > Flemiflavanone D > Lactupicrin > Exiguaflavanone A > Rhamnetin. The binding affinity of the Cassiarin D–ACE2 complex was (−10.2 KJ/mol) found inferior to the Rhinacanthin D–ACE2 complex (−10.8 KJ/mol), referring to Rhinacanthin D as a more stable candidate to use as drugs. The RMSD values of protein–ligand complexes evaluated according to their structural conformation and stable binding pose ranged between 0.1~2.1 Å. The B-factor showed that very few loops were present in the protein structure. The RMSF peak fluctuation regions ranged 5–250, predicting efficient ligand–receptor interactions. CONCLUSION: The experiment sequentially measures all the parameters required in referring to any pharmacophore as a drug, considering which all aromatic components analyzed in the study can strongly be predicted as target-specific medication against the novel coronavirus 2019 infection. A periodical of the Network for the Veterinarians of Bangladesh (BDvetNET) 2021-03-05 /pmc/articles/PMC8043340/ /pubmed/33860009 http://dx.doi.org/10.5455/javar.2021.h481 Text en Copyright: © Journal of Advanced Veterinary and Animal Research https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 4.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Dey, Dipta
Paul, Parag Kumar
Al Azad, Salauddin
Al Mazid, Mohammad Faysal
Khan, Arman Mahmud
Sharif, Md. Arman
Rahman, Md. Hafijur
Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title_full Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title_fullStr Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title_full_unstemmed Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title_short Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing
title_sort molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the sars-cov-2 s protein attachment to ace2 receptor: an in silico approach of targeted drug designing
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043340/
https://www.ncbi.nlm.nih.gov/pubmed/33860009
http://dx.doi.org/10.5455/javar.2021.h481
work_keys_str_mv AT deydipta molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT paulparagkumar molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT alazadsalauddin molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT almazidmohammadfaysal molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT khanarmanmahmud molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT sharifmdarman molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning
AT rahmanmdhafijur molecularoptimizationdockinganddynamicsimulationprofilingofselectivearomaticphytochemicalligandsinblockingthesarscov2sproteinattachmenttoace2receptoraninsilicoapproachoftargeteddrugdesigning