Targeting Allosteric Pockets of SARS-CoV-2 Main Protease Mpro

<h3>Repurposing of antivirals is an attractive therapeutic option for the treatment of COVID-19. Mpro (also called 3CLpro) is a key protease of SARS-CoV-2 involved in viral replication, and is a promising drug target for testing the existing antivirals. A major challenge to test the efficacy of antivirals is the conformational plasticity of Mpro and its future mutation prone flexibility. To address this, we hereby propose combination therapy by drugging two specific additional pockets of Mpro probed in our studies. Long scale Molecular Dynamics (MD) simulations provide evidence of these additional sites being allosteric. Suitable choice of drugs in catalytic and allosteric pockets appear to be essential for combination therapy. Current study, based on docking and extensive set of MD simulations, finds the combination of Elbasvir, Glecaprevir, Ritonavir to be a viable candidate for further experimental drug testing/pharmacophore design for Mpro. </h3>

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Targeting Allosteric Pockets of SARS-CoV-2 Main Protease Mpro

10.26434/chemrxiv.12857927.v1 ◽

2020 ◽

Author(s):

Zahoor Ahmad Bhat ◽

Dheeraj Chitara ◽

Jawed Iqbal1 ◽

Sanjeev. B.S. ◽

Arumugam Madhumalar

Keyword(s):

Molecular Dynamics ◽

Combination Therapy ◽

Viral Replication ◽

Drug Target ◽

Drug Testing ◽

Therapeutic Option ◽

Md Simulations ◽

Main Protease ◽

Experimental Drug ◽

Conformational Plasticity

<h3>Repurposing of antivirals is an attractive therapeutic option for the treatment of COVID-19. Mpro (also called 3CLpro) is a key protease of SARS-CoV-2 involved in viral replication, and is a promising drug target for testing the existing antivirals. A major challenge to test the efficacy of antivirals is the conformational plasticity of Mpro and its future mutation prone flexibility. To address this, we hereby propose combination therapy by drugging two specific additional pockets of Mpro probed in our studies. Long scale Molecular Dynamics (MD) simulations provide evidence of these additional sites being allosteric. Suitable choice of drugs in catalytic and allosteric pockets appear to be essential for combination therapy. Current study, based on docking and extensive set of MD simulations, finds the combination of Elbasvir, Glecaprevir, Ritonavir to be a viable candidate for further experimental drug testing/pharmacophore design for Mpro. </h3>

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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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Understanding the Pyrimethamine Drug Resistance Mechanism via Combined Molecular Dynamics and Dynamic Residue Network Analysis

Molecules ◽

10.3390/molecules25040904 ◽

2020 ◽

Vol 25 (4) ◽

pp. 904 ◽

Cited By ~ 1

Author(s):

Arnold Amusengeri ◽

Rolland Bantar Tata ◽

Özlem Tastan Bishop

Keyword(s):

Molecular Dynamics ◽

Drug Resistance ◽

Network Analysis ◽

Binding Free Energy ◽

Resistance Mechanism ◽

Point Mutations ◽

Md Simulations ◽

Conformational Plasticity ◽

New Perspective ◽

The Impact

In this era of precision medicine, insights into the resistance mechanism of drugs are integral for the development of potent therapeutics. Here, we sought to understand the contribution of four point mutations (N51I, C59R, S108N, and I164L) within the active site of the malaria parasite enzyme dihydrofolate reductase (DHFR) towards the resistance of the antimalarial drug pyrimethamine. Homology modeling was used to obtain full-length models of wild type (WT) and mutant DHFR. Molecular docking was employed to dock pyrimethamine onto the generated structures. Subsequent all-atom molecular dynamics (MD) simulations and binding free-energy computations highlighted that pyrimethamine’s stability and affinity inversely relates to the number of mutations within its binding site and, hence, resistance severity. Generally, mutations led to reduced binding affinity to pyrimethamine and increased conformational plasticity of DHFR. Next, dynamic residue network analysis (DRN) was applied to determine the impact of mutations and pyrimethamine binding on communication dispositions of DHFR residues. DRN revealed residues with distinctive communication profiles, distinguishing WT from drug-resistant mutants as well as pyrimethamine-bound from pyrimethamine-free models. Our results provide a new perspective on the understanding of mutation-induced drug resistance.

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Prevention of SARS-CoV-2 Proliferation with a Novel and Potent Main Protease Inhibitor by Docking, ADMET, MM-PBSA, and Molecular Dynamics Simulation

Journal of Computational Biophysics and Chemistry ◽

10.1142/s2737416521500149 ◽

2021 ◽

pp. 2150014

Author(s):

Akbar Noorbakhsh ◽

Rafee Habib Askandar ◽

Mohammad Shakib Alhagh ◽

Chiako Farshadfar ◽

Seyed Hamid Seyedi ◽

...

Keyword(s):

Molecular Dynamics ◽

Drug Target ◽

Md Simulation ◽

Vital Role ◽

Lung Damage ◽

Dynamics Simulation ◽

Reference Drug ◽

Main Protease ◽

Poisson Boltzmann ◽

Adme Properties

COVID-19 is the last disease caused by SARS-CoV-2 associated with a severe immune response and lung damage. The main protease (Mpro) has a vital role in SARS-CoV-2 proliferation. Moreover, humans lack homologous Mpro, which makes the Mpro a suitable drug target for the development of SARS-CoV-2 drugs. The purchasable L5000 library (Selleckchem Inc) includes 99,040 compounds that were used for virtual screening. After molecular docking and ADME studies, we selected a compound (WAY-604395) with a potent binding affinity to the Mpro active site and acceptable ADME properties compared to the reference drug (nelfinavir). Molecular dynamics (MD) simulation outcomes have proved that the Mpro-WAY604395 complex possesses a considerable value of flexibility, stability, compactness and binding energy. Our Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculation demonstrates that WAY-604395 is more potent ([Formula: see text]272.19[Formula: see text]kcal mol[Formula: see text]) in comparison with nelfinavir ([Formula: see text]173.39[Formula: see text]kcal[Formula: see text]mol[Formula: see text]) against SARS-CoV-2 Mpro. In conclusion, we suggest that WAY-604395 has the potential for the treatment of SARS-CoV-2 by inhibition of the Mpro.

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Unveiling the Effect of Low pH on the SARS-CoV-2 Main Protease by Molecular Dynamics Simulations

Polymers ◽

10.3390/polym13213823 ◽

2021 ◽

Vol 13 (21) ◽

pp. 3823

Author(s):

Haruna Luz Barazorda-Ccahuana ◽

Miroslava Nedyalkova ◽

Francesc Mas ◽

Sergio Madurga

Keyword(s):

Molecular Dynamics ◽

Catalytic Mechanism ◽

Md Simulations ◽

High Water ◽

Computational Techniques ◽

Acidic Ph ◽

Active Site Residues ◽

Preclinical Phase ◽

Enzymatic Function ◽

Main Protease

(1) Background: Main Protease (Mpro) is an attractive therapeutic target that acts in the replication and transcription of the SARS-CoV-2 coronavirus. Mpro is rich in residues exposed to protonation/deprotonation changes which could affect its enzymatic function. This work aimed to explore the effect of the protonation/deprotonation states of Mpro at different pHs using computational techniques. (2) Methods: The different distribution charges were obtained in all the evaluated pHs by the Semi-Grand Canonical Monte Carlo (SGCMC) method. A set of Molecular Dynamics (MD) simulations was performed to consider the different protonation/deprotonation during 250 ns, verifying the structural stability of Mpro at different pHs. (3) Results: The present findings demonstrate that active site residues and residues that allow Mpro dimerisation was not affected by pH changes. However, Mpro substrate-binding residues were altered at low pHs, allowing the increased pocket volume. Additionally, the results of the solvent distribution around Sγ, Hγ, Nδ1 and Hδ1 atoms of the catalytic residues Cys145 and His41 showed a low and high-water affinity at acidic pH, respectively. It which could be crucial in the catalytic mechanism of SARS-CoV-2 Mpro at low pHs. Moreover, we analysed the docking interactions of PF-00835231 from Pfizer in the preclinical phase, which shows excellent affinity with the Mpro at different pHs. (4) Conclusion: Overall, these findings indicate that SARS-CoV-2 Mpro is highly stable at acidic pH conditions, and this inhibitor could have a desirable function at this condition.

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Identification of Phosphoinositide-3 Kinases Delta and Gamma Dual Inhibitors Based on the p110δ/γ Crystal Structure

Letters in Drug Design & Discovery ◽

10.2174/1570180816666190730163431 ◽

2020 ◽

Vol 17 (6) ◽

pp. 772-786

Author(s):

Wen-Qing Jia ◽

Xiao-Yan Feng ◽

Ya-Ya Liu ◽

Zhen-Zhen Han ◽

Zhi Jing ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Crystal Structure ◽

Molecular Dynamics ◽

Virtual Screening ◽

Drug Target ◽

Md Simulations ◽

Biological Processes ◽

Lead Compound ◽

Dual Inhibitors ◽

Low Toxicity

Background: Phosphoinositide-3 kinases (PI3Ks) are key signaling molecules that affect a diverse array of biological processes in cells, including proliferation, differentiation, survival, and metabolism. The abnormal activity of PI3K signals is closely related to the occurrence of many diseases, which has become a very promising drug target, especially for the treatment of cancer. PI3Kδ/γ inhibitors can reduce toxicity concerns for chronic indications such as asthma and rheumatoid arthritis compared with pan PI3Ks inhibitors. Methods: With the aim of finding more effective PI3Kδ/γ dual inhibitors, virtual screening, ADMET prediction Molecular Dynamics (MD) simulations and MM-GBSA were executed based on the known p110δ/γ crystal structure. Compound ZINC28564067 with high docking score and low toxicity was obtained. Results: By MD simulations and MM-GBSA, we could observe that ZINC28564067 had more favorable conformation binding to the PI3Kδ/γ than the original ligands. Conclusion: The results provided a rapid approach for the discovery of novel PI3Kδ/γ dual inhibitors which might be a potential anti-tumor lead compound.

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Blue Biotechnology: Computational Screening of Sarcophyton Cembranoid Diterpenes for SARS-CoV-2 Main Protease Inhibition

Marine Drugs ◽

10.3390/md19070391 ◽

2021 ◽

Vol 19 (7) ◽

pp. 391

Author(s):

Mahmoud A. A. Ibrahim ◽

Alaa H. M. Abdelrahman ◽

Mohamed A. M. Atia ◽

Tarik A. Mohamed ◽

Mahmoud F. Moustafa ◽

...

Keyword(s):

Binding Energy ◽

Viral Replication ◽

In Silico ◽

Mapk Pathway ◽

Md Simulations ◽

Biologically Active ◽

Pathway Enrichment Analysis ◽

Protease Inhibition ◽

Computational Screening ◽

Main Protease

The coronavirus pandemic has affected more than 150 million people, while over 3.25 million people have died from the coronavirus disease 2019 (COVID-19). As there are no established therapies for COVID-19 treatment, drugs that inhibit viral replication are a promising target; specifically, the main protease (Mpro) that process CoV-encoded polyproteins serves as an Achilles heel for assembly of replication-transcription machinery as well as down-stream viral replication. In the search for potential antiviral drugs that target Mpro, a series of cembranoid diterpenes from the biologically active soft-coral genus Sarcophyton have been examined as SARS-CoV-2 Mpro inhibitors. Over 360 metabolites from the genus were screened using molecular docking calculations. Promising diterpenes were further characterized by molecular dynamics (MD) simulations based on molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. According to in silico calculations, five cembranoid diterpenes manifested adequate binding affinities as Mpro inhibitors with ΔGbinding < −33.0 kcal/mol. Binding energy and structural analyses of the most potent Sarcophyton inhibitor, bislatumlide A (340), was compared to darunavir, an HIV protease inhibitor that has been recently subjected to clinical-trial as an anti-COVID-19 drug. In silico analysis indicates that 340 has a higher binding affinity against Mpro than darunavir with ΔGbinding values of −43.8 and −34.8 kcal/mol, respectively throughout 100 ns MD simulations. Drug-likeness calculations revealed robust bioavailability and protein-protein interactions were identified for 340; biochemical signaling genes included ACE, MAPK14 and ESR1 as identified based on a STRING database. Pathway enrichment analysis combined with reactome mining revealed that 340 has the capability to re-modulate the p38 MAPK pathway hijacked by SARS-CoV-2 and antagonize injurious effects. These findings justify further in vivo and in vitro testing of 340 as an antiviral agent against SARS-CoV-2.

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SIMULATING DRUG-TARGET INTERACTION USING LARGE SCALE MOLECULAR DYNAMICS AND FUZZY-ART

Asian Journal of Pharmaceutical and Clinical Research ◽

10.22159/ajpcr.2017.v10s1.19973 ◽

2017 ◽

Vol 10 (13) ◽

pp. 399

Author(s):

Ankush Rai ◽

Jagadeesh Kannan

Keyword(s):

Molecular Dynamics ◽

Drug Target ◽

Large Scale ◽

Md Simulations ◽

Experimental Information ◽

Machine Learning Algorithms ◽

Kinetic Properties ◽

Fuzzy Art ◽

Drug Compound ◽

New Biomarkers

The examination of bio-molecular associations between a complex drug compound and its target is of foremost significance for the improvement of new biomarkers or bioresponsive compounds. In this paper, we exhibited a combinatorial technique of simulation of molecular dynamics (MD) and fuzzy ART to focus on the coupling factors of in the molecular binding process and its intermediary transitioning state. Here, MD simulations divided into microsecond length enable us to watch a inter-molecular coupling events, taking after different dynamical pathways and accomplishing ordered binding assembly of molecules. Results form such simulations are used to evaluate parameters corresponding to its thermodynamic and molecular kinetic properties, getting a decent concurrence with accessible experimental information. Utilizing machine learning algorithms in conjunction with MD simulations could enhance the productive for identifying key parts of drug–target binding and localization.

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Inhibition Potencies of Phytochemicals Derived from Sesame Against SARS-CoV-2 Main Protease: A Molecular Docking and Simulation Study

Frontiers in Chemistry ◽

10.3389/fchem.2021.744376 ◽

2021 ◽

Vol 9 ◽

Author(s):

Anuj Kumar ◽

Dwijesh Chandra Mishra ◽

Ulavappa Basavanneppa Angadi ◽

Rashmi Yadav ◽

Anil Rai ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Drug Targets ◽

Human Life ◽

Md Simulations ◽

Natural Compounds ◽

Free Energy Calculations ◽

Lipinski’S Rule ◽

Protease Enzyme ◽

Main Protease

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, has now spread across the nations with high mortality rates and multifaceted impact on human life. The proper treatment methods to overcome this contagious disease are still limited. The main protease enzyme (Mpro, also called 3CLpro) is essential for viral replication and has been considered as one of the potent drug targets for treating COVID-19. In this study, virtual screening was performed to find out the molecular interactions between 36 natural compounds derived from sesame and the Mpro of COVID-19. Four natural metabolites, namely, sesamin, sesaminol, sesamolin, and sesamolinol have been ranked as the top interacting molecules to Mpro based on the affinity of molecular docking. Moreover, stability of these four sesame-specific natural compounds has also been evaluated using molecular dynamics (MD) simulations for 200 nanoseconds. The molecular dynamics simulations and free energy calculations revealed that these compounds have stable and favorable energies, causing strong binding with Mpro. These screened natural metabolites also meet the essential conditions for drug likeness such as absorption, distribution, metabolism, and excretion (ADME) properties as well as Lipinski’s rule of five. Our finding suggests that these screened natural compounds may be evolved as promising therapeutics against COVID-19.

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