In-Silico Drug Repurposing for Targeting SARS-CoV-2 Mpro

10.26434/chemrxiv.12210845.v1 ◽

2020 ◽

Author(s):

Shilpa Sharma ◽

Shashank Deep

Keyword(s):

In Silico ◽

Drug Targets ◽

Md Simulation ◽

Chemical Constituents ◽

Drug Repurposing ◽

Viral Disease ◽

Ayurvedic Drugs ◽

Main Protease ◽

Novel Coronavirus ◽

Potential Inhibitors

COVID-19, caused by novel coronavirus or SARS-CoV-2, is a viral disease which has infected millions worldwide. Considering the urgent need of the drug for fighting against this infectious disease, we performed in-silico drug repurposing. The main protease (Mpro) is one of the best characterized drug targets among coronaviruses, therefore, this was screened for already known drugs, including chemical constituents of Ayurvedic drugs, using docking and MD simulation. The results suggest EGCG, withaferin A and artesunate may act as potential inhibitors of the main protease (Mpro).

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An Integrative in Silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease

Molecular Informatics ◽

10.1002/minf.202000187 ◽

2021 ◽

Author(s):

Nemanja Djokovic ◽

Dusan Ruzic ◽

Teodora Djikic ◽

Sandra Cvijic ◽

Jelisaveta Ignjatovic ◽

...

Keyword(s):

In Silico ◽

Drug Repurposing ◽

Main Protease ◽

Potential Inhibitors

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Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

10.26434/chemrxiv.12111297 ◽

2020 ◽

Author(s):

Son Tung Ngo ◽

Ngoc Quynh Anh Pham ◽

Ly Le ◽

Duc-Hung Pham ◽

Van Vu

Keyword(s):

Free Energy ◽

Molecular Docking ◽

Drug Targets ◽

Binding Free Energy ◽

Natural Compounds ◽

Main Protease ◽

Energy Perturbation ◽

Novel Coronavirus ◽

Potential Inhibitors ◽

Hiv 1

The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1st, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, cannabisin A and isoacteoside, and an HIV-1 PR inhibitor, darunavir, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of 13b, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of darunavir to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2.

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Drug Repurposing and New Therapeutic Strategies for SARS-CoV-2 Disease Using a Novel Molecular Modeling-AI Hybrid Workflow

10.26434/chemrxiv.12449081.v1 ◽

2020 ◽

Author(s):

Scott Bembenek

Keyword(s):

Molecular Modeling ◽

Therapeutic Targets ◽

Drug Repurposing ◽

Preclinical Research ◽

Main Protease ◽

Novel Coronavirus ◽

Approved Drugs ◽

Usual Process ◽

Potential Inhibitors ◽

Computational Platform

The recent outbreak of the novel coronavirus (SARS-CoV-2) poses a significant challenge to the scientific and medical communities to find immediate treatments. The usual process of identifying viable molecules and transforming them into a safe and effective drug takes 10-15 years, with around 5 years of that time spent in preclinical research and development alone. The fastest strategy is to identify existing drugs or late-stage clinical molecules (originally intended for other therapeutic targets) that already have some level of efficacy. To this end, we tasked our novel molecular modeling-AI hybrid computational platform with finding potential inhibitors of the SARS-CoV-2 main protease (Mpro, 3CLpro). Over 13,000 FDA-approved drugs and clinical candidates (represented by just under 30,000 protomers) were examined. This effort resulted in the identification of several promising molecules. Moreover, it provided insight into key chemical motifs surely to be beneficial in the design of future inhibitors. Finally, it facilitated a unique perspective into other potentially therapeutic targets and pathways for SARS-CoV-2.

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Drug Repurposing and New Therapeutic Strategies for SARS-CoV-2 Disease Using a Novel Molecular Modeling-AI Hybrid Workflow

10.26434/chemrxiv.12449081 ◽

2020 ◽

Author(s):

Scott Bembenek

Keyword(s):

Molecular Modeling ◽

Therapeutic Targets ◽

Drug Repurposing ◽

Preclinical Research ◽

Main Protease ◽

Novel Coronavirus ◽

Approved Drugs ◽

Usual Process ◽

Potential Inhibitors ◽

Computational Platform

The recent outbreak of the novel coronavirus (SARS-CoV-2) poses a significant challenge to the scientific and medical communities to find immediate treatments. The usual process of identifying viable molecules and transforming them into a safe and effective drug takes 10-15 years, with around 5 years of that time spent in preclinical research and development alone. The fastest strategy is to identify existing drugs or late-stage clinical molecules (originally intended for other therapeutic targets) that already have some level of efficacy. To this end, we tasked our novel molecular modeling-AI hybrid computational platform with finding potential inhibitors of the SARS-CoV-2 main protease (Mpro, 3CLpro). Over 13,000 FDA-approved drugs and clinical candidates (represented by just under 30,000 protomers) were examined. This effort resulted in the identification of several promising molecules. Moreover, it provided insight into key chemical motifs surely to be beneficial in the design of future inhibitors. Finally, it facilitated a unique perspective into other potentially therapeutic targets and pathways for SARS-CoV-2.

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Molecular docking, pharmacophore modelling, MD simulation and in silico ADMET study reveals bitter cola constituents as potential inhibitors of SARS-CoV-2 main protease and RNA dependent-RNA polymerase

Journal of Biomolecular Structure and Dynamics ◽

10.1080/07391102.2021.2024883 ◽

2022 ◽

pp. 1-16

Author(s):

Abimbola Peter Oluyori ◽

Bolatito Eunice Olanipekun ◽

Oluyomi Stephen Adeyemi ◽

Godshelp Osas Egharevba ◽

Abayomi Emmanuel Adegboyega ◽

...

Keyword(s):

Molecular Docking ◽

Rna Polymerase ◽

In Silico ◽

Md Simulation ◽

Rna Dependent Rna Polymerase ◽

Pharmacophore Modelling ◽

Main Protease ◽

In Silico Admet ◽

Potential Inhibitors

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Aminoglycosides as potential inhibitors of SARS-CoV-2 main protease: an in silico drug repurposing study on FDA-approved antiviral and anti-infection agents

Journal of Infection and Public Health ◽

10.1016/j.jiph.2021.01.016 ◽

2021 ◽

Vol 14 (5) ◽

pp. 611-619

Author(s):

Mohammad Z. Ahmed ◽

Qamar Zia ◽

Anzarul Haque ◽

Ali S. Alqahtani ◽

Omar M. Almarfadi ◽

...

Keyword(s):

In Silico ◽

Drug Repurposing ◽

Main Protease ◽

Potential Inhibitors

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Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

10.26434/chemrxiv.12111297.v2 ◽

2020 ◽

Author(s):

Son Tung Ngo ◽

Ngoc Quynh Anh Pham ◽

Ly Le ◽

Duc-Hung Pham ◽

Van Vu

Keyword(s):

Free Energy ◽

Molecular Docking ◽

Drug Targets ◽

Binding Free Energy ◽

Natural Compounds ◽

Main Protease ◽

Energy Perturbation ◽

Novel Coronavirus ◽

Potential Inhibitors ◽

Hiv 1

The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1st, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, cannabisin A and isoacteoside, and an HIV-1 PR inhibitor, darunavir, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of 13b, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of darunavir to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2.

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Natural compounds as potential inhibitors of novel coronavirus (COVID-19) main protease: An in silico study

10.21203/rs.3.rs-22839/v1 ◽

2020 ◽

Cited By ~ 3

Author(s):

Amaresh Mishra ◽

Yamini Pathak ◽

Vishwas Tripathi

Keyword(s):

In Silico ◽

Structural Diversity ◽

Natural Compounds ◽

Binding Energies ◽

Maslinic Acid ◽

Main Protease ◽

In Silico Studies ◽

Gallocatechin Gallate ◽

Novel Coronavirus ◽

Potential Inhibitors

Abstract COVID-19 pandemic, a novel coronavirus disease is caused by severe acute respiratory syndrome corona virus, SARS-CoV-2. It was first reported in Wuhan, China and has now expanded to more than 190 countries across the world. Till date, there is no specific medication available to prevent or target SARS CoV-2 infection. Very recently, the crystal structure of COVID- 19 main protease (Mpro) was revealed by Liu et al. (2020). SARS-CoV-2 main protease (Mpro) is a key enzyme that plays a crucial role in viral replication and transcription. Thus, Mpro could be a promising target to inhibit SARS-CoV-2 infection. Natural compounds due to their structural diversity and safety are considered as an excellent source of antiviral drugs. In this study, we selected Herbacetin, Rhoifolin, Pectolinarin, Apigenin, Luteolin, Amentoflavone, Daidzein, Puerarin, Epigallocatechin, Gallocatechin gallate, Resveratrol, Maslinic acid, Piperine and Ganomycin B to target the SARS-CoV-2 main protease (Mpro) using in silico tools. These compounds were examined based on ADME, drug likeness, docking studies, MD simulations using CABS-flex 2.0, and prediction of major toxicity parameters (hepatotoxicity & cytotoxicity) to check the safety aspects of the selected compounds. We also investigated the similarity of these compounds, if any, with FDA approved drugs using Swiss similarity. The docking results were found in the order of Amentoflavone (-9.13 kcal/mol), Ritonavir (-8.52 kcal/mol), Lopinavir (-8.5 kcal/mol), Puerarin (-7.97 kcal/mol), Maslinic acid (-7.97 kcal/mol), Piperine (-7.65 kcal/mol), Gallocatechin gallate (-7.59 kcal/mol), Luteolin (-7.58 kcal/mol), Apigenin (-7.42 kcal/mol), Resveratrol (-7.41 kcal/mol), Herbacetin (-7.4 kcal/mol), Daidzein (-7.32 kcal/mol), Rhoifolin (-6.71 kcal/mol), Ganomycin B (-6.46 kcal/mol), Epigallocatechin (-6.13 kcal/mol), and Pectolinarin (-5.88 kcal/mol). Among these selected natural compounds, Amentoflavone and Puerarin were the two top leads which showed the lowest binding energies. Interestingly, Amentoflavone showed highest binding affinity among all the selected compounds. Our promising findings based on in-silico studies warrants further clinical trial in order to use these compounds as potential inhibitors of SARS-CoV-2 protease.

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