Target-Based In Silico Screening for Phytoactive Compounds Targeting SARS-CoV-2

Zhao, Yong; Tian, Yu; Chenling, Pan; Liang, Aihua; Zhang, Wei; Sheng, Yi

doi:10.1007/s12539-021-00461-4

Cited by 7 publications

(3 citation statements)

References 64 publications

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“…Mapping based of binding hotspots data showed that PL pro presents only one organic probe cluster (site 1 ), whereas for the 3CL pro the results suggest the existence of four organic probe clusters (site 1 , site 2 , site 3 , and site 4 ). The position of the interaction sites on both receptors identified here (PL pro and 3CL pro ) did not differ from those previously reported (Abdizadeh et al 2022;Zhao et al 2022).…”

Section: Domain Analysis and Linker Prediction Of The Target Receptorssupporting

confidence: 53%

Evaluation of the anti-diabetic drug sitagliptin as a novel attenuate to SARS-CoV-2 evidence-based in silico: molecular docking and molecular dynamics

et al. 2022

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The current outbreak of COVID-19 cases worldwide has been responsible for a significant number of deaths, especially in hospitalized patients suffering from comorbidities, such as obesity, diabetes, hypertension. The disease not only has prompted an interest in the pathophysiology, but also it has propelled a massive race to find new anti-SARS-CoV-2 drugs. In this scenario, known drugs commonly used to treat other diseases have been suggested as alternative or complementary therapeutics. Herein we propose the use of sitagliptin, an inhibitor of dipeptidyl peptidase-4 (DPP 4 ) used to treat type-II diabetes, as an agent to block and inhibit the activity of two proteases, 3CL pro and PL pro , related to the processing of SARS-CoV-2 structural proteins. Inhibition of these proteases may possibly reduce the viral load and infection on the host by hampering the synthesis of new viruses, thus promoting a better outcome. In silico assays consisting in the modeling of the ligand sitagliptin and evaluation of its capacity to interact with 3CL pro and PL pro through the prediction of the ligand bioactivity, molecular docking, overlapping of crystal structures, and molecular dynamic simulations were conducted. The experiments indicate that sitagliptin can interact and bind to both targets. However, this interaction seems to be stronger and more stable to 3CL pro (ΔG = −7.8 kcal mol −1 ), when compared to PL pro (ΔG = −7.5 kcal mol −1 ). This study suggests that sitagliptin may be suitable to treat COVID-19 patients, beyond its common use as an anti-diabetic medication. In vivo studies may further support this hypothesis.

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Section: Domain Analysis and Linker Prediction Of The Target Receptorssupporting

confidence: 53%

Evaluation of the anti-diabetic drug sitagliptin as a novel attenuate to SARS-CoV-2 evidence-based in silico: molecular docking and molecular dynamics

et al. 2022

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“…Molavi et al repurposed 1760 FDA-approved drugs to Mpro and RdRp, and Rajpoot et al repurposed 291 drugs to Mpro and PLpro. More similar works include refs , , , , , , , , , , and − .…”

Section: Methods and Approachesmentioning

confidence: 97%

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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“…Additionally, Zhao et al performed an in silico screening of a small herbal database to find potential direct-acting compounds against different non-structural SARS-CoV-2 targets. Accordingly, Amentoflavone with the highest affinity (-9.7 kcal.mol -1 )was highlighted as an nsp12 inhibitor [ 16 ]. Zhang et al translated the results of computational screening of 1906 approved drugs into in vitro assays.…”

mentioning

confidence: 99%

Digging for the Discovery of SARS-CoV-2 nsp12 Inhibitors: A Pharmacophore-Based and Molecular Dynamics Simulation Study

Askari¹,

Ebrahimi

Parhiz

et al. 2022

Future Virol.

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Aim: COVID-19 is a global health threat. Therapeutics are urgently needed to cure patients severely infected with COVID-19. Objective: to investigate potential candidates of nsp12 inhibitors by searching for druggable cavity pockets within the viral protein and drug discovery. Methods: A virtual screening of ZINC natural products on SARS-CoV-2 nsp12's druggable cavity was performed. A lead compound with the highest affinity to nsp12 was simulated dynamically for 10 ns. Results: ZINC03977803 was nominated as the lead compound. The results showed stable interaction between ZINC03977803 and nsp12 during 10 ns. Discussion: ZINC03977803 showed stable interaction with the catalytic subunit of SARS-CoV-2, nsp12. It could inhibit the SARS-CoV-2 life cycle by direct interaction with nsp12 and inhibit RdRp complex formation.

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Target-Based In Silico Screening for Phytoactive Compounds Targeting SARS-CoV-2

Cited by 7 publications

References 64 publications

Evaluation of the anti-diabetic drug sitagliptin as a novel attenuate to SARS-CoV-2 evidence-based in silico: molecular docking and molecular dynamics

Evaluation of the anti-diabetic drug sitagliptin as a novel attenuate to SARS-CoV-2 evidence-based in silico: molecular docking and molecular dynamics

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

Digging for the Discovery of SARS-CoV-2 nsp12 Inhibitors: A Pharmacophore-Based and Molecular Dynamics Simulation Study

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