Identifying the Hot Spot Residues of the SARS-CoV-2 Main Protease Using MM-PBSA and Multiple Force Fields

In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein–ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of Mpro, which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2.

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In Silico Molecular Docking and Molecular Dynamic Simulation of Potential Inhibitors of 3C-like Main Proteinase (3CLpro) from Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Using Selected African Medicinal Plants

10.26434/chemrxiv.12480434.v1 ◽

2020 ◽

Author(s):

Sahar Qazi ◽

Mustafa Alhaji Isa ◽

Adam Mustapha ◽

Khalid Raza ◽

Ibrahim Alkali Allamin ◽

...

Keyword(s):

Molecular Docking ◽

Severe Acute Respiratory Syndrome ◽

In Silico ◽

Md Simulation ◽

Binding Energies ◽

Anacardium Occidentale ◽

Upper Respiratory Tract ◽

Ligand Complex ◽

In Silico Docking ◽

Main Protease

<p>The Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is an infectious virus that causes mild to severe life-threatening upper respiratory tract infection. The virus emerged in Wuhan, China in 2019, and later spread across the globe. Its genome has been completely sequenced and based on the genomic information, the virus possessed 3C-Like Main Protease (3CLpro), an essential multifunctional enzyme that plays a vital role in the replication and transcription of the virus by cleaving polyprotein at eleven various sites to produce different non-structural proteins. This makes the protein an important target for drug design and discovery. Herein, we analyzed the interaction between the 3CLpro and potential inhibitory compounds identified from the extracts of <i>Zingiber offinale</i> and <i>Anacardium occidentale</i> using in silico docking and Molecular Dynamics (MD) Simulation. The crystal structure of SARS-CoV-2 main protease in complex with 02J (5-Methylisoxazole-3-carboxylic acid) and PEJ (composite ligand) (PDB Code: 6LU7,2.16Å) retrieved from Protein Data Bank (PDB) and subject to structure optimization and energy minimization. A total of twenty-nine compounds were obtained from the extracts of <i>Zingiber offinale </i>and the leaves of <i>Anacardium occidentale. </i>These compounds were screened for physicochemical (Lipinski rule of five, Veber rule, and Egan filter), <i>Pan</i>-Assay Interference Structure (PAINS), and pharmacokinetic properties to determine the Pharmaceutical Active Ingredients (PAIs). Of the 29 compounds, only nineteen (19) possessed drug-likeness properties with efficient oral bioavailability and less toxicity. These compounds subjected to molecular docking analysis to determine their binding energies with the 3CLpro. The result of the analysis indicated that the free binding energies of the compounds ranged between ˗5.08 and -10.24kcal/mol, better than the binding energies of 02j (-4.10kcal/mol) and PJE (-5.07kcal.mol). Six compounds (CID_99615 = -10.24kcal/mol, CID_3981360 = 9.75kcal/mol, CID_9910474 = -9.14kcal/mol, CID_11697907 = -9.10kcal/mol, CID_10503282 = -9.09kcal/mol and CID_620012 = -8.53kcal/mol) with good binding energies further selected and subjected to MD Simulation to determine the stability of the protein-ligand complex. The results of the analysis indicated that all the ligands form stable complexes with the protein, although, CID_9910474 and CID_10503282 had a better stability when compared to other selected phytochemicals (CID_99615, CID_3981360, CID_620012, and CID_11697907). </p>

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In Silico Molecular Docking and Molecular Dynamic Simulation of Potential Inhibitors of 3C-like Main Proteinase (3CLpro) from Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Using Selected African Medicinal Plants

10.26434/chemrxiv.12480434 ◽

2020 ◽

Author(s):

Sahar Qazi ◽

Mustafa Alhaji Isa ◽

Adam Mustapha ◽

Khalid Raza ◽

Ibrahim Alkali Allamin ◽

...

Keyword(s):

Molecular Docking ◽

Severe Acute Respiratory Syndrome ◽

In Silico ◽

Md Simulation ◽

Binding Energies ◽

Anacardium Occidentale ◽

Upper Respiratory Tract ◽

Ligand Complex ◽

In Silico Docking ◽

Main Protease

<p>The Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is an infectious virus that causes mild to severe life-threatening upper respiratory tract infection. The virus emerged in Wuhan, China in 2019, and later spread across the globe. Its genome has been completely sequenced and based on the genomic information, the virus possessed 3C-Like Main Protease (3CLpro), an essential multifunctional enzyme that plays a vital role in the replication and transcription of the virus by cleaving polyprotein at eleven various sites to produce different non-structural proteins. This makes the protein an important target for drug design and discovery. Herein, we analyzed the interaction between the 3CLpro and potential inhibitory compounds identified from the extracts of <i>Zingiber offinale</i> and <i>Anacardium occidentale</i> using in silico docking and Molecular Dynamics (MD) Simulation. The crystal structure of SARS-CoV-2 main protease in complex with 02J (5-Methylisoxazole-3-carboxylic acid) and PEJ (composite ligand) (PDB Code: 6LU7,2.16Å) retrieved from Protein Data Bank (PDB) and subject to structure optimization and energy minimization. A total of twenty-nine compounds were obtained from the extracts of <i>Zingiber offinale </i>and the leaves of <i>Anacardium occidentale. </i>These compounds were screened for physicochemical (Lipinski rule of five, Veber rule, and Egan filter), <i>Pan</i>-Assay Interference Structure (PAINS), and pharmacokinetic properties to determine the Pharmaceutical Active Ingredients (PAIs). Of the 29 compounds, only nineteen (19) possessed drug-likeness properties with efficient oral bioavailability and less toxicity. These compounds subjected to molecular docking analysis to determine their binding energies with the 3CLpro. The result of the analysis indicated that the free binding energies of the compounds ranged between ˗5.08 and -10.24kcal/mol, better than the binding energies of 02j (-4.10kcal/mol) and PJE (-5.07kcal.mol). Six compounds (CID_99615 = -10.24kcal/mol, CID_3981360 = 9.75kcal/mol, CID_9910474 = -9.14kcal/mol, CID_11697907 = -9.10kcal/mol, CID_10503282 = -9.09kcal/mol and CID_620012 = -8.53kcal/mol) with good binding energies further selected and subjected to MD Simulation to determine the stability of the protein-ligand complex. The results of the analysis indicated that all the ligands form stable complexes with the protein, although, CID_9910474 and CID_10503282 had a better stability when compared to other selected phytochemicals (CID_99615, CID_3981360, CID_620012, and CID_11697907). </p>

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High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling

Chemical Science ◽

10.1039/d1sc00145k ◽

2021 ◽

Author(s):

Théo Jaffrelot Inizan ◽

Frédéric Célerse ◽

Olivier Adjoua ◽

Dina El Ahdab ◽

Luc-Henri Jolly ◽

...

Keyword(s):

Molecular Dynamics ◽

High Resolution ◽

Adaptive Sampling ◽

Force Fields ◽

Sampling Strategy ◽

Md Simulations ◽

Conformational Space ◽

Many Body ◽

Polarizable Force Fields ◽

Main Protease

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs).

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Molecular Docking and Dynamics Simulation Study of Hyrtios erectus Isolated Scalarane Sesterterpenes as Potential SARS-CoV-2 Dual Target Inhibitors

Biology ◽

10.3390/biology10050389 ◽

2021 ◽

Vol 10 (5) ◽

pp. 389

Author(s):

Sameh S. Elhady ◽

Reda F. A. Abdelhameed ◽

Rania T. Malatani ◽

Abdulrahman M. Alahdal ◽

Hanin A. Bogari ◽

...

Keyword(s):

Molecular Docking ◽

Md Simulation ◽

Protein Complexes ◽

Antiviral Agents ◽

Binding Energies ◽

Dynamics Simulation ◽

Main Protease ◽

Simulation Parameters ◽

Molecular Docking And Dynamics ◽

Dual Target

Presently, the world is under the toll of pandemic coronavirus disease-2019 (COVID-19) outbreak caused by SARS-CoV-2. Lack of effective and safe therapeutics has stressed the scientific community for developing novel therapeutics capable of alleviating and stopping this pandemic. Within the presented study, molecular docking, ADME properties and all-atom molecular dynamic (MD) simulation, along with two standard antiviral agents (lopinavir and benzopurpurin-4B), were applied to investigate 15 scalaranes sesterterpenes natural compounds, purified from the Red Sea marine sponge Hyrtios erectus, as potential COVID-19 dual-target inhibitors. Following multi-step docking within COVID-19 main protease and Nsp15 endoribonuclease cavities, nine promising drug-like compounds exhibited higher docking scores as well as better interactions with the target’s crucial residues than those of reference ligands. Compounds 2, 6, 11, and 15, were predicted to simultaneously subdue the activity of the two COVID-19 targets. Dynamics behavior of the best-docked molecules, compounds 15 and 6, within COVID-19 target pockets showed substantial stability of ligand-protein complexes as presented via several MD simulation parameters. Furthermore, calculated free-binding energies from MD simulation illustrated significant ligand’s binding affinity towards respective target pockets. All provided findings supported the utility of scalarane-based sesterterpenes, particularly compounds 15 and 6, as promising lead candidates guiding the development of effective therapeutics against SARS-CoV-2.

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Molecular Docking of Olea europaea and Curcuma Longa Compounds as Potential Drug Agents for Targeting Main-Protease of SARS-nCoV2

10.26434/chemrxiv.13246739 ◽

2020 ◽

Author(s):

Rashid Saif ◽

Muhammad Hassan Raza ◽

Talha Rehman ◽

Muhammad Osama Zafar ◽

Saeeda Zia ◽

...

Keyword(s):

Molecular Docking ◽

Structural Information ◽

Curcuma Longa ◽

Experimental Studies ◽

Md Simulations ◽

Binding Energies ◽

Target Protein ◽

Target Proteins ◽

Main Protease

<p>One of the main reasons of rapidly growing cases of COVID-19 pandemic is the unavailability of approved therapeutic agents. Therefore, it is urgently required to find out the best drug/vaccine by all means. Aim of the current study is to test the anti-viral drug potential of many of the available olive and turmeric compounds that can be used as potential inhibitors against one of the target proteins of SARS-nCoV2 named Main protease (Mpro/3clpro). Molecular docking of thirty olive and turmeric compounds with target protein was performed using Molecular Operating Environment (MOE) software to determine the best ligand-protein interaction energies. The structural information of the viral target protein M pro/3CL pro and ligands were taken from PDB and PubChem database respectively. Out of the thirty drug agents, 6 ligands do not follow the Lipinski rule of drug likeliness by violating two or more rules while remaining 24 obey the rules and included for the downstream analysis. Ten ligands from olive and four from turmeric gave the best lowest binding energies, which are Neuzhenide, Rutin, Demethyloleoeuropein, Oleuropein, Luteolin-7-rutinoside, Ligstroside, Verbascoside, Luteolin-7-glucoside, Cosmosin, Curcumin, Tetrehydrocurcumin, Luteolin-4'-o-glucoside, Demethoxycurcumin and Bidemethoxycurcumin with docking scores of -10.91, -9.49, -9.48, -9.21, -9.18, -8.72, -8.51, -7.68, -7.67, -7.65, -7.42, -7.25, -7.02 and - 6.77 kcal/mol respectively. Our predictions suggest that these ligands have the potential inhibitory effects of M pro of SARS-nCoV2, so, these herbal plants would be helpful in harnessing COVID-19 infection as home remedy with no serious known side effects. Further, in-silico MD simulations and in-vivo experimental studies are needed to validate the inhibitory properties of these compounds against the current and other target proteins in SARS-nCoV2.<br></p>

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Developing a molecular dynamics force field for both folded and disordered protein states

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1800690115 ◽

2018 ◽

Vol 115 (21) ◽

pp. E4758-E4766 ◽

Cited By ~ 256

Author(s):

Paul Robustelli ◽

Stefano Piana ◽

David E. Shaw

Keyword(s):

Molecular Dynamics ◽

Force Field ◽

Md Simulation ◽

State Of The Art ◽

Force Fields ◽

Md Simulations ◽

Disordered Proteins ◽

Disordered Protein ◽

Data Points ◽

Folded Proteins

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points. We find that none of the tested force fields simultaneously provided accurate descriptions of folded proteins, of the dimensions of disordered proteins, and of the secondary structure propensities of disordered proteins. Guided by simulation results on a subset of our benchmark, however, we modified parameters of one force field, achieving excellent agreement with experiment for disordered proteins, while maintaining state-of-the-art accuracy for folded proteins. The resulting force field, a99SB-disp, should thus greatly expand the range of biological systems amenable to MD simulation. A similar approach could be taken to improve other force fields.

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Can Antimalarial Phytochemicals be a Possible Cure for COVID-19? Molecular Docking Studies of Some Phytochemicals to SARS-CoV-2 3C-like Protease

Infectious Disorders - Drug Targets ◽

10.2174/1871526521666210729164054 ◽

2021 ◽

Vol 21 ◽

Author(s):

Anamul Hasan ◽

Khoshnur Jannat ◽

Tohmina Afroze Bondhon ◽

Rownak Jahan ◽

Md Shahadat Hossan ◽

...

Keyword(s):

Molecular Docking ◽

Docking Studies ◽

Binding Energies ◽

Binding Affinities ◽

Drug Candidates ◽

Lead Compounds ◽

High Binding ◽

Main Protease ◽

Acridone Alkaloid ◽

First Time

Objective: To evaluate the efficacy of reported anti-malarial phytochemicals as lead compounds for possible drug development against COVID-19. Methods: An in silico approach was used in this study to determine through molecular docking the binding affinities and site of binding of these phytochemicals to the 3C-like protease of COVID-19 which is considered as the main protease of the virus. Results: A number of anti-malarial phytochemicals like apigenin-7-O-glucoside, decurvisine, luteolin-7-O-glucoside, sargabolide J, and shizukaols A, B, F, and G showed predicted high binding energies with G values of -8.0 kcal/mol or higher. Shizukaols F and B demonstrated the best binding energies of -9.5 and -9.8, respectively. The acridone alkaloid 5-hydroxynoracronycine also gave a predicted high binding energy of -7.9 kcal/mol. Conclusion: This is for the first time that decursivine and several shizukaols were reported as potential anti-viral agents. These compounds merit further studies to determine whether they can be effective drug candidates against COVID-19.

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Profiling Molecular Simulations of SARS-CoV-2 Main Protease (Mpro) Binding to Repurposed Drugs Using Neural Network Force Fields

10.26434/chemrxiv.12376094.v1 ◽

2020 ◽

Author(s):

Aayush Gupta

Keyword(s):

Neural Network ◽

Protein Interactions ◽

Force Fields ◽

Md Simulations ◽

Interaction Sites ◽

Main Protease ◽

Rational Drug ◽

Interaction Map ◽

Novel Coronavirus ◽

Approved Drugs

<div> <p> </p><div> <div> <div> <p> </p><div> <div> <div> <p> </p><div> <div> <div> <p>With the current pandemic situation caused by a novel coronavirus disease (COVID-19), there is an urgent call to develop a working therapeutic against it. Efficient computations aid to minimize the efforts by identifying a subset of drugs that can potentially bind to COVID-19 main protease or target protein (M<sup>PRO</sup>). The results of computations are always accompanied by their accuracy which depends on the details described by the model used. Machine learning models trained on millions of points and with unmatched accuracies are the best bet to employ in the process. In this work, I first identified and described the interaction sites of M<sup>PRO</sup> protein using a geometric deep learning model. Secondly, I conducted virtual screening (at one of the sites identified) on FDA approved drugs and picked 91 drugs having the highest binding affinity (below -8.0 kcal/mol). Then, I carried out 10 ns of molecular dynamics (MD) simulations using classical force fields and classified 37 drugs to be binding (includes drugs like Lopinavir, Saquinavir, Indinavir etc.) based on RMSD between MD-binding trajectories. To drastically improve the dynamics profile of selected 37 drugs, I brought in the highly accurate neural network force field (ANI) trained on coupled-cluster methods (CCSD(T)) data points and performed 1 ns of binding dynamics of each drug with protein. With the accurate approach, 19 drugs were qualified based on their RMSD cutoffs, and again with their free energy (ANI/MM/PBSA) computations another 7 drugs were rejected. The final selection of 12 drugs was validated based on MD trajectory clustering approach where 11 of 12 drugs (Targretin, Eltrombopag, Rifaximin, Deflazacort, Ergotamine, Doxazosin, Lastacaft, Rifampicin, Victrelis, Trajenta, Toposar, Indinavir) were confirmed to be binding. Further investigations were made to study their interactions with the protein and an accurate 2D- interaction map was generated. These findings and mapping of drug-protein interactions are highly accurate and could be potentially used to guide rational drug discovery against the COVID-19. </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>

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Azole-acridine hybrids as potential enzymatic inhibitors of coronavirus-2 main protease and RNA polymerase by molecular modeling strategy

10.21203/rs.3.rs-32809/v1 ◽

2020 ◽

Author(s):

Charles K. Rono ◽

Banothile C.E. Makhubela

Keyword(s):

Molecular Docking ◽

Rna Polymerase ◽

Docking Study ◽

Living Cells ◽

Binding Energies ◽

Binding Affinities ◽

Molecular Docking Study ◽

Main Protease ◽

Current Outbreak ◽

Modeling Strategy

Abstract SARS-CoV-2 has been identified as the cause of the current outbreak of coronavirus disease (COVID-19). As part of the efforts to develop potential drugs with promise for clinical use, a molecular docking study on azole (triazole and pyrazole) based molecules on the main protease Mpro and RNA polymerase as possible inhibitors that could be elected for further experimental bioassays. Autodock has been employed to identify azole derivatives 1-6 preferred conformations in the active site of the enzyme and to estimate their binding affinities to the protease and RNA polymerase targets. From the molecular docking strategy, these new azole compounds though nonpeptides in nature display possible inhibition of Mpro activity with comparable affinities (-4.7 kcal/mol to -6.5 kcal/mol) to the recently reported peptide-like inhibitors such as α-ketoamide inhibitor 13b (-5.0 k/cal/mol). They also exhibit improved binding affinities to RNA polymerase (-6.3 to -7.1 kcal/mol) comparable to remdesivir (-6.6 kcal/mol). Based on the observed binding energies, these compounds may possess anti-coronavirus bioactivity through inhibition of the virus main protease as well as RNA polymerase activities in living cells.

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