Identification of Known Drugs As Potential SARS-CoV-2 Mpro Inhibitors Using ligand- and Structure-Based Virtual Screening

Federico, Leonardo Bruno; Silva, Guilherme Martins; Hage‐Melim, Lorane Izabel da Silva; Gomes, Suzane Quintana; Barcelos, Mariana Pegrucci; Francischini, Isaque Antônio Galindo; Silva, Carlos Henrique Tomich de Paula da

doi:10.4155/fmc-2021-0025

Cited by 9 publications

(6 citation statements)

References 63 publications

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“…The SARS-CoV virus evades the body's defenses by binding to chemokine receptors. The inflammation caused by viral infection in cells and tissues may also be mitigated by these molecules [54].…”

Section: Discussionmentioning

confidence: 99%

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A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

Sokouti

2023

Exploration of Targeted Anti-Tumor Therapy

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The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.

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Section: Discussionmentioning

confidence: 99%

“…Through AutoDock Vina and PyRx, the authors checked the LOPAC library for molecules that bind to ACE2 and S-RBD of SARS-CoV-2. MD simulations were run on the ACE2 protein and the S-RBD protein using the GROMOS96 43a1 force field [54].…”

Section: Literature Informationmentioning

confidence: 99%

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

Sokouti

2023

Exploration of Targeted Anti-Tumor Therapy

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“… 221 As a result, diosmin, hesperidin, and MK-3207, with a docking score of −10.1 kcal/mol, were suggested as the most potent inhibitors. A collection of 8625 drugs or compounds from FDA, drugbank, and Zinc data sets were docked to Mpro, 222 and seven drugs such as metyrapone could maintain key interactions within the active site of the enzyme suggested by the crystallographic complex structures, revealing their repurposing potential. Additionally, Sencanski et al 223 and Gurung et al 224 both screened about 1400 FDA-approved drugs with docking, predicting that dihydroergotamine has a promising affinity.…”

Section: Methods and Approachesmentioning

confidence: 99%

“…In a screening of roughly 7100 molecules, several natural molecules such as δ-viniferin, myricitrin, taiwanhomoflavone A, lactucopicrin 15-oxalate, nympholide A, afzelin, biorobin, hesperidin, and phyllaemblicin B were identified . Many other studies ,− have also docked and repurposed existing drugs against SARS-CoV-2 Mpro.…”

Section: Methods and Approachesmentioning

confidence: 99%

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Gao¹,

Wang²,

Chen³

et al. 2022

Chem. Rev.

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Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein–protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

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“…Structure-based virtual screening (SBVS) of diverse ligand databases, many of them containing drug repurposing candidates and natural products, has been extensively applied to identify potential 3CL pro inhibitors (Wu C. et al, 2020;Chowdhury et al, 2020;Jukic et al, 2020;Meyer-Almes, 2020;Olubiyi et al, 2020;Selvaraj et al, 2020;Federico et al, 2021;Gogoi et al, 2021;Guedes et al, 2021;Kumar et al, 2021;Lokhande et al, 2021;Naik et al, 2021;Rajpoot et al, 2021;Rehman et al, 2021;Sisakht et al, 2021). In several cases, this approach has led to the successful identification of compounds displaying in vitro inhibitory activity against 3CL pro (Ghahremanpour et al, 2020;Gupta et al, 2020;Jin et al, 2020;Li et al, 2020;Alves et al, 2021;Banerjee et al, 2021;Gunther et al, 2021;Guo et al, 2021;Gupta et al, 2021;Hamdy et al, 2021;Pathak et al, 2021;Yang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease

González

Eberle

Willbold

et al. 2022

Front. Mol. Biosci.

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The SARS-CoV-2 main protease, also known as 3-chymotrypsin-like protease (3CLpro), is a cysteine protease responsible for the cleavage of viral polyproteins pp1a and pp1ab, at least, at eleven conserved sites, which leads to the formation of mature nonstructural proteins essential for the replication of the virus. Due to its essential role, numerous studies have been conducted so far, which have confirmed 3CLpro as an attractive drug target to combat Covid-19 and have reported a vast number of inhibitors and their co-crystal structures. Despite all the ongoing efforts, D-peptides, which possess key advantages over L-peptides as therapeutic agents, have not been explored as potential drug candidates against 3CLpro. The current work fills this gap by reporting an in silico approach for the discovery of D-peptides capable of inhibiting 3CLpro that involves structure-based virtual screening (SBVS) of an in-house library of D-tripeptides and D-tetrapeptides into the protease active site and subsequent rescoring steps, including Molecular Mechanics Generalized-Born Surface Area (MM-GBSA) free energy calculations and molecular dynamics (MD) simulations. In vitro enzymatic assays conducted for the four top-scoring D-tetrapeptides at 20 μM showed that all of them caused 55–85% inhibition of 3CLpro activity, thus highlighting the suitability of the devised approach. Overall, our results present a promising computational strategy to identify D-peptides capable of inhibiting 3CLpro, with broader application in problems involving protein inhibition.

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Identification of Known Drugs As Potential SARS-CoV-2 Mpro Inhibitors Using ligand- and Structure-Based Virtual Screening

Cited by 9 publications

References 63 publications

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

A Computer-Aided Approach for the Discovery of D-Peptides as Inhibitors of SARS-CoV-2 Main Protease

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