Proposition of a new allosteric binding site for potential SARS-CoV-2 3CL protease inhibitors by utilizing molecular dynamics simulations and ensemble docking

Novak, Jurica; Rimac, Hrvoje; Kandagalla, Shivananda; Pathak, Prateek; Naumovich, Vladislav; Grishina, Maria; Потемкин, В. А.

doi:10.1080/07391102.2021.1927845

Cited by 20 publications

(23 citation statements)

References 42 publications

(47 reference statements)

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“…Two studies reported that the Radotinib can be used for the prevention, alleviation, or treatment of viral respiratory disease. Specifically, the present invention can be used as a useful antiviral agent for the prevention or treatment of disease caused by infection of the SARS-CoV-2 and MERS-CoV [ 156 – 158 ]. A molecular docking simulation study suggested that Ivermectin may be an effective treatment for SARS-Cov2 infections [ 159 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Ahmed

Reza

Sarker³

et al. 2022

PLoS ONE

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Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

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Section: Discussionmentioning

confidence: 99%

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Ahmed

Reza

Sarker³

et al. 2022

PLoS ONE

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“…Present in the protease's catalytic dyads are other amino acids from CYS 145 and HIS 41, which are functional in eliminating Mpro enzymes. Dimerization and mutations of Mpro that engender enzymes with reduced activities are associated with interactions with the residues around GLU 288, ASP 289, and GLU 290 [59]. While CYS 145 and HIS 45 mediate the catalytic mechanism of the enzyme, mutation of these residues leads to the total annihilation of the Mpro activity [60,61].…”

Section: Discussionmentioning

confidence: 99%

Computational Study of the Therapeutic Potential of Novel Heterocyclic Derivatives against SARS-CoV-2

Babalola

Adetobi

Akinsuyi

et al. 2021

COVID

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Severe Acute Respiratory Syndrome Coronavirus- 2 (SARS-CoV-2), including the recently reported severe variant B.1.617.2, has been reported to attack the respiratory tract with symptoms that may ultimately lead to death. While studies have been conducted to evaluate therapeutic interventions against the virus, this study evaluated the inhibitory potential of virtually screened novel derivatives and structurally similar compounds towards SARS-CoV-2 via a computational approach. A molecular docking simulation of the inhibitory potentials of the compounds against the SARS-CoV-2 drug targets—main protease (Mpro), spike protein (Spro), and RNA-dependent RNA polymerase (RdRp)—were evaluated and achieved utilizing AutoDock Vina in PyRx workspace. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of these compounds were assessed using SwissADME and ADMETLab servers. All the compounds displayed high binding affinities for the SARS-CoV-2 drug targets. However, the C13 exhibited the highest binding affinity for the drug targets, Spro and RdRp, while C15 exhibited the highest binding affinity for Mpro. The compounds interacted with the LEU A:271, LEU A:287, ASP A:289, and LEU A:272 of Mpro and the HIS A:540, PRO A:415, PHE A:486, and LEU A:370 of the Spro receptor binding motif and some active site amino acids of RdRp. The compounds also possess a favourable ADMET profile and showed no tendency towards hERG inhibition, hepatotoxicity, carcinogenicity, mutagenicity, or drug-liver injury. These novel compounds could offer therapeutic benefits against SARS-CoV-2, and wet laboratory experiments are necessary to further validate the results of this computational study.

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“…Additionally, Novak et al. 391 first screened 8756 approved or experimental drugs by regular docking; then the best 10 drugs from regular docking were further evaluated by an ensemble docking strategy. The 10 drugs were docked to 5 conformation representatives of Mpro obtained from MD simulations and cluster analysis.…”

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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Proposition of a new allosteric binding site for potential SARS-CoV-2 3CL protease inhibitors by utilizing molecular dynamics simulations and ensemble docking

Cited by 20 publications

References 42 publications

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Computational Study of the Therapeutic Potential of Novel Heterocyclic Derivatives against SARS-CoV-2

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

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