Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences

Adhikari, Nilanjan; Banerjee, S.; Baidya, Sandip Kumar; Ghosh, Balaram; Jha, Tarun

doi:10.1016/j.molstruc.2021.132041

Cited by 13 publications

(9 citation statements)

References 98 publications

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“…Remdesivir can also inhibit the SARS-CoV-2 RdRp [51,53,[73][74][75]. Remdesivir can also dock the 3CLpro replicase [49,51,76,77]. These results are consistent with in vitro data demonstrating that it inhibits SARS-CoV-2 viral replication only at the post-entry stage in Vero E6 cells and not at the entry stage [21].…”

Section: Discussionsupporting

confidence: 87%

Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants

et al. 2022

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Over the past two years, several variants of SARS-CoV-2 have emerged and spread all over the world. However, infectivity, clinical severity, re-infection, virulence, transmissibility, vaccine responses and escape, and epidemiological aspects have differed between SARS-CoV-2 variants. Currently, very few treatments are recommended against SARS-CoV-2. Identification of effective drugs among repurposing FDA-approved drugs is a rapid, efficient and low-cost strategy against SARS-CoV-2. One of those drugs is ivermectin. Ivermectin is an antihelminthic agent that previously showed in vitro effects against a SARS-CoV-2 isolate (Australia/VI01/2020 isolate) with an IC50 of around 2 µM. We evaluated the in vitro activity of ivermectin on Vero E6 cells infected with 30 clinically isolated SARS-CoV-2 strains belonging to 14 different variants, and particularly 17 strains belonging to six variants of concern (VOC) (variants related to Wuhan, alpha, beta, gamma, delta and omicron). The in vitro activity of ivermectin was compared to those of chloroquine and remdesivir. Unlike chloroquine (EC50 from 4.3 ± 2.5 to 29.3 ± 5.2 µM) or remdesivir (EC50 from 0.4 ± 0.3 to 25.2 ± 9.4 µM), ivermectin showed a relatively homogeneous in vitro activity against SARS-CoV-2 regardless of the strains or variants (EC50 from 5.1 ± 0.5 to 6.7 ± 0.4 µM), except for one omicron strain (EC50 = 1.3 ± 0.5 µM). Ivermectin (No. EC50 = 219, mean EC50 = 5.7 ± 1.0 µM) was, overall, more potent in vitro than chloroquine (No. EC50 = 214, mean EC50 = 16.1 ± 9.0 µM) (p = 1.3 × 10−34) and remdesivir (No. EC50 = 201, mean EC50 = 11.9 ± 10.0 µM) (p = 1.6 × 10−13). These results should be interpreted with caution regarding the potential use of ivermectin in SARS-CoV-2-infected patients: it is difficult to translate in vitro study results into actual clinical treatment in patients.

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Section: Discussionsupporting

confidence: 87%

Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants

et al. 2022

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“…Saquinavir and simeprevir are inhibitors of proteases from HIV and HCV, respectively. Saquinavir was also indicated as a viable inhibitor of M pro after applying QSAR and HQSAR models [57] , while the latter compound was identified as an M pro inhibitor using molecular docking [58] . Candesartan cilexetil, which according to our study can inhibit spike from various lineages, had an IC50 value of approximately 67 μM against M pro in a FRET-based activity assay [59] .…”

Section: Discussionmentioning

confidence: 99%

Drug repurposing for identification of potential spike inhibitors for SARS-CoV-2 using molecular docking and molecular dynamics simulations

Łażniewski

Dermawan

Hidayat

et al. 2022

Methods

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“…Furthermore, to identify essential physicochemical and structural characters for SARS-CoV-2 Mpro inhibition, a nonlinear QSAR model assisted by ANN and SVM was designed with 69 structurally diverse chemicals with potential SARS-CoV-2 Mpro inhibitory property as descriptors. 772 Furthermore, ComboNet was designed to predict (1) the interaction between a drug and multiple biological targets, (2) the intrinsic antiviral activity of a drug, and (3) the synergy of drugs. 773 ComnoNet is composed of two subnetworks: a drug–target interaction (DTI) and a target–disease association network, which enabled an effective in silico search for synergistic combinations against SARS-CoV-2 (see Figure 13 ).…”

Section: Methods and Approachesmentioning

confidence: 99%

“…Moreover, Izumi et al used the FASTA file for a deep neural network to predict sequence-based super secondary structure codes. Furthermore, to identify essential physicochemical and structural characters for SARS-CoV-2 Mpro inhibition, a nonlinear QSAR model assisted by ANN and SVM was designed with 69 structurally diverse chemicals with potential SARS-CoV-2 Mpro inhibitory property as descriptors . Furthermore, ComboNet was designed to predict (1) the interaction between a drug and multiple biological targets, (2) the intrinsic antiviral activity of a drug, and (3) the synergy of drugs .…”

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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Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences

Cited by 13 publications

References 98 publications

Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants

Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants

Drug repurposing for identification of potential spike inhibitors for SARS-CoV-2 using molecular docking and molecular dynamics simulations

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

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