Structure-based screening of natural product libraries in search of potential antiviral drug-leads as first-line treatment to COVID-19 infection

Rao, S.J. Aditya; Shetty, Nandini P.

doi:10.1016/j.micpath.2022.105497

Cited by 11 publications

(5 citation statements)

References 65 publications

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“…Table 1 shows that only one author published one article [ 37 ]. The other three articles were published by two authors [ 23 , 32 , 41 ]. More than two authors published all the remaining twenty-nine studies.…”

Section: Resultsmentioning

confidence: 99%

“…Human proteases such as TMPRSS2 [ 17 , 24 ] and other SARS-CoV-2 proteins such as RdRp [ 32 , 42 ], spike protein [ 43 ], nsp12 [ 41 ], SARS-CoV-2 spike receptor-binding domain (RBD) [ 38 ], and nsp16 [ 15 ] have also been used as the sole drug targets in specific studies. In those respective studies, Shi et al [ 15 ] discovered C1 with CAS ID 1224032-33-0 and C2 with CAS ID 1224020-56-7 as nsp16 inhibitors after employing the following in-silico techniques: pharmacophore modeling using phase, pharmacophore-based virtual screening using phase, MD using glide, and MDS using Gromacs 2021.…”

Section: Resultsmentioning

confidence: 99%

“…Muhseen et al [ 38 ] opted for MDS and structure-based virtual screening to obtain NPACT01552, NPACT01557, and NPACT00631 as probable inhibitors of the SARS-CoV-2 spike receptor-binding domain (RBD). Rao and Shetty [ 41 ] performed virtual screening, pharmacokinetic and pharmacodynamics properties examination, molecular docking, and MDS and discovered 12,28-oxa-8-hydroxymanzamine A as a potential inhibitor of nsp12. In the last study, Pandey et al [ 43 ] utilized the same in silico models employed by several other researchers: molecular docking, MDS, and ADME analysis.…”

Section: Resultsmentioning

confidence: 99%

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In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

Onyango

2023

Advances in Pharmacological and Pharmaceutical Sciences

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The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms “In silico model,” “COVID-19,” “Anti-COVID-19 drug,” “Drug discovery,” “Computational drug designing,” and “Computer-aided drug design.” Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

Onyango

2023

Advances in Pharmacological and Pharmaceutical Sciences

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“… Target Molecular docking software Binding affinity Kcal/mol Hydrogen bond with Ref 6M71 Autodock Vina -9 ASN781, HIS133, SER709, TYR129 LYS A47, ASP711 [156] 6M71 Autodock Vina − 8 LYS47, TYR129, SER709, ASP711, ASN781 [146] 6M71 Autodock Vina − 7.1 Lys621, Cys622, Asp761, Lys798, Glu811. [157] 7VH8 AutoDock 4.2 -8.56 GLY143 CYS145 LEU167 TYR54 CYS145 GLU166 [158] 6M71 AutoDock Vina -7.8 Gly143, Ser144 (2), Cys145, Glu166, Asn142 [159] 7BV2 AutoDockVina -7.2 ILE23, LEU126, GLY48 [160] 7BTF DOCK 6 -8.8 ALA 550, LYS 55, ARG 55, CYS 813, SER814, GLN 815 [161] Legend: ASN, asparagine; HIS, histidine; SER, serine; TYR, tyrosine; LYS, lysine; ASP, aspartic acid; ALA, alanine; ARG, arginine; CYS, cysteine; GLN, glutamine; GLY, glycine; LEU, leucine; GLU, glutamic acid; ILE, isoleucine. …”

Section: Targeted Proteins Using In Silico Methodsmentioning

confidence: 99%

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Negru

Miculas

Behl

et al. 2022

Biomedicine & Pharmacotherapy

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“…Scientists are investigating COVID-19 prevention strategies that employ both chemical and natural substances. Natural bioactive compounds are currently being screened using molecular docking to assess their affinity for molecular targets of COVID-19 in silico, with the benefit that natural products are free from harmful or adverse effects [ 11 ]. Several natural substances, including bee product alkaloids, terpenoids, marine products, and other natural products, have been confirmed as potential inhibitors against COVID-19 for targeting M pro , RdRp and Nsp of SARS-CoV-2 [ 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Identification of Bioactive Compounds of Cannabinoids in Silico for Inhibition of SARS-CoV-2 and SARS-CoV

et al. 2022

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Despite the approval of multiple vaccinations in different countries, the majority of the world’s population remains unvaccinated due to discrepancies in vaccine distribution and limited production capacity. The SARS-CoV-2 RBD-ACE2 complex (receptor binding domain that binds to ACE2) could be a suitable target for the development of a vaccine or an inhibitor. Various natural products have been used against SARS-CoV-2. Here, we docked 42 active cannabinoids to the active site of the SARS-CoV-2 and SARS-CoV complex of RBD-ACE2. To ensure the flexibility and stability of the complex produced after docking, the top three ligand molecules with the best overall binding energies were further analyzed through molecular dynamic simulation (MDS). Then, we used the webserver Swissadme program and binding free energy to calculate and estimate the MMPBSA and ADME characteristics. Our results showed that luteolin, CBGVA, and CBNA were the top three molecules that interact with the SARS-CoV-2 RBD-ACE2 complex, while luteolin, stigmasterol, and CBNA had the strongest contact with that SARS-CoV. Our findings show that luteolin may be a potential inhibitor of infections caused by coronavirus-like pathogens such as COVID-19, although further in vivo and in vitro research is required.

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Structure-based screening of natural product libraries in search of potential antiviral drug-leads as first-line treatment to COVID-19 infection

Cited by 11 publications

References 65 publications

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Analysis and Identification of Bioactive Compounds of Cannabinoids in Silico for Inhibition of SARS-CoV-2 and SARS-CoV

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