Screening of Potential Inhibitors Targeting the Main Protease Structure of SARS-CoV-2 via Molecular Docking, and Approach with Molecular Dynamics, RMSD, RMSF, H-Bond, SASA and MMGBSA

Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands th...

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Vydáno v:Molecular biotechnology Ročník 66; číslo 8; s. 1919 - 1933
Hlavní autoři: da Fonseca, Aluísio Marques, Caluaco, Bernardino Joaquim, Madureira, Junilson Martinho Canjanja, Cabongo, Sadrack Queque, Gaieta, Eduardo Menezes, Djata, Faustino, Colares, Regilany Paulo, Neto, Moises Maia, Fernandes, Carla Freire Celedonio, Marinho, Gabrielle Silva, dos Santos, Hélcio Silva, Marinho, Emmanuel Silva
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.08.2024
Springer Nature B.V
Témata:
Algorithms
Antiviral Agents - chemistry
Antiviral Agents - pharmacology
Binding Sites
Biochemistry
Biological Techniques
Biotechnology
Cell Biology
Chemistry
Chemistry and Materials Science
Clinical trials
computer simulation
Conformation
Coronavirus 3C Proteases - antagonists & inhibitors
Coronavirus 3C Proteases - chemistry
Coronavirus 3C Proteases - metabolism
Coronaviruses
COVID-19
COVID-19 - virology
COVID-19 Drug Treatment
COVID-19 infection
Drug development
Drug screening
Drugs
energy
Ergotamine
genetic models
Human Genetics
Humans
Hydrogen Bonding
Ligands
Molecular docking
Molecular Docking Simulation
Molecular dynamics
Molecular Dynamics Simulation
Molecular structure
Original Paper
Population genetics
Protease
Protease inhibitors
Protease Inhibitors - chemistry
Protease Inhibitors - metabolism
Protease Inhibitors - pharmacology
Protein Binding
Protein Science
Proteinase
Proteinase inhibitors
proteinases
SARS-CoV-2 - drug effects
SARS-CoV-2 - enzymology
Severe acute respiratory syndrome coronavirus 2
Viral diseases
Virtual screening
Coronavirus
Receptor
Ligand
Molecular docking
covid19
ISSN:1073-6085, 1559-0305, 1559-0305
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Abstract Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M pro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H–Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (−6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (−9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (−9.8 kcal/mol/RMSD of 1.46 Å) and olysio (−9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M pro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
AbstractList Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the Mpro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H–Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (−6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (−9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (−9.8 kcal/mol/RMSD of 1.46 Å) and olysio (−9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the Mpro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M pro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H–Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (−6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (−9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (−9.8 kcal/mol/RMSD of 1.46 Å) and olysio (−9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M pro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the Mᵖʳᵒ protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H–Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (−6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (−9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (−9.8 kcal/mol/RMSD of 1.46 Å) and olysio (−9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the Mᵖʳᵒ protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the Mpro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the Mpro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the Mpro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the Mpro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.
Author Cabongo, Sadrack Queque
Gaieta, Eduardo Menezes
Colares, Regilany Paulo
Marinho, Emmanuel Silva
da Fonseca, Aluísio Marques
Madureira, Junilson Martinho Canjanja
Fernandes, Carla Freire Celedonio
Caluaco, Bernardino Joaquim
dos Santos, Hélcio Silva
Djata, Faustino
Neto, Moises Maia
Marinho, Gabrielle Silva
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  fullname: da Fonseca, Aluísio Marques
  organization: Mestrado Acadêmico em Sociobiodiversidades e Tecnologias Sustentáveis – MASTS, Instituto de Engenharias e Desenvolvimento Sustentável, Universidade da Integração Internacional da Lusofonia Afro-Brasileira
– sequence: 2
  givenname: Bernardino Joaquim
  orcidid: 0000-0002-1375-6320
  surname: Caluaco
  fullname: Caluaco, Bernardino Joaquim
  organization: Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira
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  organization: Instituto de Ciências Exatas e da Natureza, Universidade da Integração Internacional da Lusofonia Afro-Brasileira
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  givenname: Moises Maia
  orcidid: 0000-0001-8586-2782
  surname: Neto
  fullname: Neto, Moises Maia
  organization: Curso de Graduação Em Farmácia, Centro Universitário Fametro
– sequence: 9
  givenname: Carla Freire Celedonio
  surname: Fernandes
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– sequence: 10
  givenname: Gabrielle Silva
  orcidid: 0000-0002-9337-2043
  surname: Marinho
  fullname: Marinho, Gabrielle Silva
  organization: Faculdade de Filosofia, Dom Aureliano Matos - FAFIDAM, Universidade Estadual Do Ceará
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  givenname: Hélcio Silva
  orcidid: 0000-0001-5527-164X
  surname: dos Santos
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  givenname: Emmanuel Silva
  orcidid: 0000-0002-4774-8775
  surname: Marinho
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  organization: Faculdade de Filosofia, Dom Aureliano Matos - FAFIDAM, Universidade Estadual Do Ceará
BackLink https://www.ncbi.nlm.nih.gov/pubmed/37490200$$D View this record in MEDLINE/PubMed
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2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Copyright_xml – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Issue 8
Keywords Virtual screening
Coronavirus
Receptor
Ligand
Molecular docking
covid19
Language English
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Snippet Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that...
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SubjectTerms Algorithms
Antiviral Agents - chemistry
Antiviral Agents - pharmacology
Binding Sites
Biochemistry
Biological Techniques
Biotechnology
Cell Biology
Chemistry
Chemistry and Materials Science
Clinical trials
computer simulation
Conformation
Coronavirus 3C Proteases - antagonists & inhibitors
Coronavirus 3C Proteases - chemistry
Coronavirus 3C Proteases - metabolism
Coronaviruses
COVID-19
COVID-19 - virology
COVID-19 Drug Treatment
COVID-19 infection
Drug development
Drug screening
Drugs
energy
Ergotamine
genetic models
Human Genetics
Humans
Hydrogen Bonding
Ligands
Molecular docking
Molecular Docking Simulation
Molecular dynamics
Molecular Dynamics Simulation
Molecular structure
Original Paper
Population genetics
Protease
Protease inhibitors
Protease Inhibitors - chemistry
Protease Inhibitors - metabolism
Protease Inhibitors - pharmacology
Protein Binding
Protein Science
Proteinase
Proteinase inhibitors
proteinases
SARS-CoV-2 - drug effects
SARS-CoV-2 - enzymology
Severe acute respiratory syndrome coronavirus 2
Viral diseases
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Title Screening of Potential Inhibitors Targeting the Main Protease Structure of SARS-CoV-2 via Molecular Docking, and Approach with Molecular Dynamics, RMSD, RMSF, H-Bond, SASA and MMGBSA
URI https://link.springer.com/article/10.1007/s12033-023-00831-x
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https://www.proquest.com/docview/2841881662
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Volume 66
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