scholarly journals Structural Analysis of COVID-19 Main Protease and its Interaction with the Inhibitor N3

2020 ◽  
Author(s):  
Tika Ram Lamichhane ◽  
Madhav Prasad Ghimire
Keyword(s):  
Root Mean Square ◽  
Solvent Accessibility ◽  
Radial Distance ◽  
Structural Features ◽  
Radius Of Gyration ◽  
Physical Parameters ◽  
Mean Square ◽  
Atom Pairs ◽  
Main Protease ◽  
Dynamics Simulations

<i>Here, we analyze the structural features of a ligand binding domain (LBD) in COVID-19 main protease (MP) followed by the interactions between the inhibitor N3 and MP-LBD residues through the molecular dynamics simulations. The time based changes in physical parameters that includes root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RG), dihedral distributions, residue velocity, radial distribution function (RDF) and H-bonding signify the degrees of folding states in MP-N3 complex formed by the superimposed b-barrels and flexible a-helices. Sharp and flat RDF peaks observed for the atom pairs dictate the flexibility of MP-LBD residues during their interactions with N3. In spite of larger solvent accessibility of N3, it interacts strongly with the LBD residues resulting in H-bonding. Among the LBD residues, GLU166 is found to have the lowest residue velocity that offers the sharp RDF peaks for three H-bonding atom pairs nearly at 2 Å radial distance, whereas GLY143 has the highest value of residue velocity giving rise to a flat RDF peak for the MP-N3 atom pair. Furthermore, electrostatic and van der Waals interaction energies between N3 and MP-LBD residues are noted to have the negative values. All these parameters explain the binding nature of N3 like inhibitors to the substrate binding sites of COVID-19 main protease. These analysis are expected to be a possible route applicable in drug designing mechanism to restrict the viral replication and transcription of COVID-19.</i><i> </i>

scholarly journals Structural Analysis of COVID-19 Main Protease and its Interaction with the Inhibitor N3

2020 ◽  
Author(s):  
Tika Ram Lamichhane ◽  
Madhav Prasad Ghimire
Keyword(s):  
Root Mean Square ◽  
Solvent Accessibility ◽  
Radial Distance ◽  
Structural Features ◽  
Radius Of Gyration ◽  
Physical Parameters ◽  
Mean Square ◽  
Atom Pairs ◽  
Main Protease ◽  
Dynamics Simulations

<i>Here, we analyze the structural features of a ligand binding domain (LBD) in COVID-19 main protease (MP) followed by the interactions between the inhibitor N3 and MP-LBD residues through the molecular dynamics simulations. The time based changes in physical parameters that includes root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RG), dihedral distributions, residue velocity, radial distribution function (RDF) and H-bonding signify the degrees of folding states in MP-N3 complex formed by the superimposed b-barrels and flexible a-helices. Sharp and flat RDF peaks observed for the atom pairs dictate the flexibility of MP-LBD residues during their interactions with N3. In spite of larger solvent accessibility of N3, it interacts strongly with the LBD residues resulting in H-bonding. Among the LBD residues, GLU166 is found to have the lowest residue velocity that offers the sharp RDF peaks for three H-bonding atom pairs nearly at 2 Å radial distance, whereas GLY143 has the highest value of residue velocity giving rise to a flat RDF peak for the MP-N3 atom pair. Furthermore, electrostatic and van der Waals interaction energies between N3 and MP-LBD residues are noted to have the negative values. All these parameters explain the binding nature of N3 like inhibitors to the substrate binding sites of COVID-19 main protease. These analysis are expected to be a possible route applicable in drug designing mechanism to restrict the viral replication and transcription of COVID-19.</i><i> </i>

scholarly journals Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach

2021 ◽  
Vol 1 ◽  
Author(s):  
Shafi Mahmud ◽  
Md. Robiul Hasan ◽  
Suvro Biswas ◽  
Gobindo Kumar Paul ◽  
Shamima Afrose ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Economy ◽  
Transmission Rate ◽  
Accessible Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Protease Inhibition ◽  
Main Protease

Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of −8.3, −8.6, and −8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.

scholarly journals Plant-Based Phytochemical Screening by Targeting Main Protease of SARS-CoV-2 to Design Effective Potent Inhibitors

Biology ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 589
Author(s):  
Shafi Mahmud ◽  
Suvro Biswas ◽  
Gobindo Kumar Paul ◽  
Mohasana Akter Mita ◽  
Maria Meha Promi ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Active Sites ◽  
Treatment Options ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Drug Candidates ◽  
Main Protease ◽  
Antibacterial And Antifungal

Currently, a worldwide pandemic has been declared in response to the spread of coronavirus disease 2019 (COVID-19), a fatal and fast-spreading viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The low availability of efficient vaccines and treatment options has resulted in a high mortality rate, bringing the world economy to its knees. Thus, mechanistic investigations of drugs capable of counteracting this disease are in high demand. The main protease (Mpro) expressed by SARS-CoV-2 has been targeted for the development of potential drug candidates due to the crucial role played by Mpro in viral replication and transcription. We generated a phytochemical library containing 1672 phytochemicals derived from 56 plants, which have been reported as having antiviral, antibacterial, and antifungal activity. A molecular docking program was used to screen the top three candidate compounds: epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate, which had respective binding affinities of −8.4, −8.5, and −8.8 kcal/mol. Several active sites in the targeted protein, including Cys145, His41, Met49, Glu66, and Met165, were found to interact with the top three candidate compounds. The multiple simulation profile, root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and solvent-accessible surface area values supported the inflexible nature of the docked protein–compound complexes. The toxicity and carcinogenicity profiles were assessed, which showed that epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate had favorable pharmacological properties with no adverse effects. These findings suggest that these compounds could be developed as part of an effective drug development pathway to treat COVID-19.

scholarly journals Efficacy of Phytochemicals Derived from Avicennia officinalis for the Management of COVID-19: A Combined In Silico and Biochemical Study

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2210
Author(s):  
Shafi Mahmud ◽  
Gobindo Kumar Paul ◽  
Mirola Afroze ◽  
Shirmin Islam ◽  
Swagota Briti Ray Gupt ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Antioxidant Activities ◽  
Binding Free Energy ◽  
Healthcare Management ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Main Protease ◽  
Avicennia Officinalis

The recent coronavirus disease 2019 (COVID-19) pandemic is a global threat for healthcare management and the economic system, and effective treatments against the pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus responsible for this disease have not yet progressed beyond the developmental phases. As drug refinement and vaccine progression require enormously broad investments of time, alternative strategies are urgently needed. In this study, we examined phytochemicals extracted from Avicennia officinalis and evaluated their potential effects against the main protease of SARS-CoV-2. The antioxidant activities of A. officinalis leaf and fruit extracts at 150 µg/mL were 95.97% and 92.48%, respectively. Furthermore, both extracts displayed low cytotoxicity levels against Artemia salina. The gas chromatography–mass spectroscopy analysis confirmed the identifies of 75 phytochemicals from both extracts, and four potent compounds, triacontane, hexacosane, methyl linoleate, and methyl palminoleate, had binding free energy values of −6.75, −6.7, −6.3, and −6.3 Kcal/mol, respectively, in complexes with the SARS-CoV-2 main protease. The active residues Cys145, Met165, Glu166, Gln189, and Arg188 in the main protease formed non-bonded interactions with the screened compounds. The root-mean-square difference (RMSD), root-mean-square fluctuations (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen bond data from a molecular dynamics simulation study confirmed the docked complexes′ binding rigidity in the atomistic simulated environment. However, this study′s findings require in vitro and in vivo validation to ensure the possible inhibitory effects and pharmacological efficacy of the identified compounds.

scholarly journals Effects of the Temperature and the pH on the Main Protease of SARS-CoV-2: A Molecular Dynamics Simulation Study

2021 ◽  
Vol 12 (6) ◽  
pp. 7239-7248
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Root Mean Square ◽  
Dynamics Simulation ◽  
Effect Of Temperature ◽  
Water Molecules ◽  
Mean Square ◽  
Main Protease ◽  
Decreasing Ph ◽  
Increasing Temperature

The novel coronavirus, recognized as COVID-19, is the cause of an infection outbreak in December 2019. The effect of temperature and pH changes on the main protease of SARS-CoV-2 were investigated using all-atom molecular dynamics simulation. The obtained results from the root mean square deviation (RMSD) and root mean square fluctuations (RMSF) analyses showed that at a constant temperature of 25℃ and pH=5, the conformational change of the main protease is more significant than that of pH=6 and 7. Also, by increasing temperature from 25℃ to 55℃ at constant pH=7, a remarkable change in protein structure was observed. The radial probability of water molecules around the main protease was decreased by increasing temperature and decreasing pH. The weakening of the binding energy between the main protease and water molecules due to the increasing temperature and decreasing pH has reduced the number of hydrogen bonds between the main protease and water molecules. Finding conditions that alter the conformation of the main protease could be fundamental because this change could affect the virus’s functionality and its ability to impose illness.

scholarly journals Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4829
Author(s):  
Sajjad Haider ◽  
Assem Barakat ◽  
Zaheer Ul-Haq
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Root Mean Square ◽  
Cancer Metastasis ◽  
Pharmacophore Model ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dynamic Simulations

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

scholarly journals Fruit Bromelain-Derived Peptide Potentially Restrains the Attachment of SARS-CoV-2 Variants to hACE2: A Pharmacoinformatics Approach

Molecules ◽  
2022 ◽  
Vol 27 (1) ◽  
pp. 260
Author(s):  
Trina Ekawati Tallei ◽  
Fatimawali ◽  
Ahmad Akroman Adam ◽  
Mona M. Elseehy ◽  
Ahmed M. El-Shehawi ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Antiviral Agents ◽  
Md Simulations ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Angiotensin Converting Enzyme 2 ◽  
In Silico Study ◽  
Mean Square Fluctuation ◽  
Binding Residues ◽  
Binding Energy Calculations

Before entering the cell, the SARS-CoV-2 spike glycoprotein receptor-binding domain (RBD) binds to the human angiotensin-converting enzyme 2 (hACE2) receptor. Hence, this RBD is a critical target for the development of antiviral agents. Recent studies have discovered that SARS-CoV-2 variants with mutations in the RBD have spread globally. The purpose of this in silico study was to determine the potential of a fruit bromelain-derived peptide. DYGAVNEVK. to inhibit the entry of various SARS-CoV-2 variants into human cells by targeting the hACE binding site within the RBD. Molecular docking analysis revealed that DYGAVNEVK interacts with several critical RBD binding residues responsible for the adhesion of the RBD to hACE2. Moreover, 100 ns MD simulations revealed stable interactions between DYGAVNEVK and RBD variants derived from the trajectory of root-mean-square deviation (RMSD), radius of gyration (Rg), and root-mean-square fluctuation (RMSF) analysis, as well as free binding energy calculations. Overall, our computational results indicate that DYGAVNEVK warrants further investigation as a candidate for preventing SARS-CoV-2 due to its interaction with the RBD of SARS-CoV-2 variants.

scholarly journals Structure Features of Peptide-Type SARS-CoV Main Protease Inhibitors: Quantitative Structure Activity Relationship Study

2020 ◽  
Author(s):  
Vijay Masand ◽  
Ajaykumar Gandhi ◽  
Vesna Rastija ◽  
Meghshyam K. Patil
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Quantitative Structure ◽  
Statistical Parameters ◽  
Qsar Analysis ◽  
Structure Activity ◽  
Atom Pairs ◽  
Main Protease ◽  
Qsar Models ◽  
Quantitative Structure Activity Relationships

<div>In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that govern the MPro inhibitory activity of peptide-type compounds. The QSAR analysis is based on a dataset of sixty-two peptide-type compounds which resulted in the generation of statistically robust and highly predictive multiple models. All the developed models were validated extensively and satisfy the threshold values for many statistical parameters (for e.g. R2 = 0.80–0.82, Q2loo = 0.74–0.77). The developed models identified interrelations of atom pairs as important molecular descriptors. Therefore, the present QSAR models have a good balance of Qualitative and Quantitative approaches, thereby, useful for future modifications of peptide-type compounds for anti- SARS-CoV activity.</div><div><br></div>

scholarly journals Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins

2016 ◽  
Author(s):  
Yuan-Ping Pang
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Root Mean Square ◽  
A Priori ◽  
Model Systems ◽  
Dynamics Simulation ◽  
High Mass ◽  
Mean Square ◽  
Dynamics Simulations

ABSTRACTPredicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2–9 ± 1 Å2for Cα and 7.3 ± 0.9–9.6 ± 0.2 Å2for Cγ, when the sampling was done, for each of these proteins, over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations using AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive toa prioriprediction of crystallographic B-factors of a folded globular protein.

scholarly journals Changes of Conformation in Albumin with Temperature by Molecular Dynamics Simulations

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 405
Author(s):  
Piotr Weber ◽  
Piotr Bełdowski ◽  
Krzysztof Domino ◽  
Damian Ledziński ◽  
Adam Gadomski
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Root Mean Square ◽  
Mean Square Displacement ◽  
Conformational Space ◽  
Global Dynamics ◽  
Mean Square ◽  
Conformational Entropy ◽  
The Mean ◽  
Dynamics Simulations

This work presents the analysis of the conformation of albumin in the temperature range of 300 K – 312 K , i.e., in the physiological range. Using molecular dynamics simulations, we calculate values of the backbone and dihedral angles for this molecule. We analyze the global dynamic properties of albumin treated as a chain. In this range of temperature, we study parameters of the molecule and the conformational entropy derived from two angles that reflect global dynamics in the conformational space. A thorough rationalization, based on the scaling theory, for the subdiffusion Flory–De Gennes type exponent of 0 . 4 unfolds in conjunction with picking up the most appreciable fluctuations of the corresponding statistical-test parameter. These fluctuations coincide adequately with entropy fluctuations, namely the oscillations out of thermodynamic equilibrium. Using Fisher’s test, we investigate the conformational entropy over time and suggest its oscillatory properties in the corresponding time domain. Using the Kruscal–Wallis test, we also analyze differences between the mean root mean square displacement of a molecule at various temperatures. Here we show that its values in the range of 306 K – 309 K are different than in another temperature. Using the Kullback–Leibler theory, we investigate differences between the distribution of the mean root mean square displacement for each temperature and time window.

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