Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning

Kadioglu, Onat; Saeed, Mohamed E.M.; Greten, Henry Johannes; Efferth, Thomas

doi:10.1016/j.compbiomed.2021.104359

Cited by 135 publications

(83 citation statements)

References 61 publications

(46 reference statements)

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“…The most targeted protein in these in silico approaches is the main protease (Mpro), for which 150 drugs have been suggested (50 of which approved by the FDA), followed by the spike protein (S), with 47 suggested drugs. The most suggested drug against Mpro is Lopinavir and ritonavir 52 , while gazoprevir is the most suggested drug targeting the spike protein 53 .…”

Section: Discussionmentioning

confidence: 99%

A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

Santos-Beneit

Raškevičius

Skeberdis

et al. 2021

Sci Rep

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In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed.

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Section: Discussionmentioning

confidence: 99%

A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

Santos-Beneit

Raškevičius

Skeberdis

et al. 2021

Sci Rep

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“…The residues with lowest binding energy in spike protein were Phe342, Phe338 and Trp436. These residues were observed to interact with various inhibitors identified till date (Kadioglu et al, 2021). In NSP3 the residues reported to interact with (Ile131, Phe132) were with the lowest binding free energy.…”

Section: Free Energy Of Binding Of Phytochemicals With Sars-cov-2 Targets As Computed By Mm/pbsamentioning

confidence: 97%

Free Energy Landscapes and Residue Network Analysis for Six SARS-CoV-2 Targets in Complex with Plausible Phytochemical Inhibitors from Withania Somnifera: 1 µS Molecular Dynamics Simulations

Kumar¹,

Parida²,

Dipak

et al. 2021

Preprint

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The pandemic is here to stay- evident from the second wave that is severely affecting global population. Though vaccination is now available, the population size restricts its efficacy, especially in the third world countries. Therefore, to avoid a third wave, natural preventive therapeutics are the need of the hour. In this work the efficiency of phytochemicals from <i>Withania somnifera</i> to bind to a total of six SARS-CoV-2 targets have been shown.1 µs molecular dynamics simulations and essential dynamic analyses shed light on the changes induced by the phytochemicals and highlights their multipotent capabilities- 27-Hydroxywithanolide B was able to bind to three targets. Relative free energy of binding for all the phytochemicals were calculated by MM/PBSA. Minimum energy structures were extracted from their free energy landscapes and were subjected to PSN-ENM-NMA and network centrality analysis. Results showed that the phytochemical binding changes the residue-residue interaction network. Network communities increase while hubs and links decrease. Metapath rewiring occurs through residues Phe456 in spike protein, Thr26 and Tyr118 in main protease, Val49 and Phe156 in NSP3, Leu98 in NSP9, Leu4345 in NSP10, Phe440 and Phe843 in NSP12. This work tries to understand the mechanism of possible inhibition by the phytochemicals to combat SARS-CoV-2 with their capability of targeting multiple proteins. The insight from this study can be of great relevance to explore the changes in network properties induced by reported potential inhibitors against SARS-CoV-2 targets.

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“…In another report, an integrative technique combining network-based and deep-learning approaches, termed CoV-KGE, has identified a total of 41 repurposable drugs, of which some has been validated through transcriptomics and proteomics data derived from existing clinical trials ( Zeng et al, 2020 ). Besides existing approved drugs, novel compounds such as anti-HCV drug IDX-184, have also been identified for SARS-CoV-2 using virtual screening and supervised machine learning methods ( Kadioglu, Saeed, Greten, & Efferth, 2021 ).…”

Section: Drug Repurposing Approachesmentioning

confidence: 99%

Drug repurposing for COVID-19: Approaches, challenges and promising candidates

Salim

Chu

2021

Pharmacology & Therapeutics

106

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Traditional drug development and discovery has not kept pace with threats from emerging and re-emerging diseases such as Ebola virus, MERS-CoV and more recently, SARS-CoV-2. Among other reasons, the exorbitant costs, high attrition rate and extensive periods of time from research to market approval are the primary contributing factors to the lag in recent traditional drug developmental activities. Due to these reasons, drug developers are starting to consider drug repurposing (or repositioning) as a viable alternative to the more traditional drug development process. Drug repurposing aims to find alternative uses of an approved or investigational drug outside of its original indication. The key advantages of this approach are that there is less developmental risk, and it is less time-consuming since the safety and pharmacological profile of the repurposed drug is already established. To that end, various approaches to drug repurposing are employed. Computational approaches make use of machine learning and algorithms to model disease and drug interaction, while experimental approaches involve a more traditional wet-lab experiments. This review would discuss in detail various ongoing drug repurposing strategies and approaches to combat the current COVID-19 pandemic, along with the advantages and the potential challenges.

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Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning

Cited by 135 publications

References 61 publications

A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

Free Energy Landscapes and Residue Network Analysis for Six SARS-CoV-2 Targets in Complex with Plausible Phytochemical Inhibitors from Withania Somnifera: 1 µS Molecular Dynamics Simulations

Drug repurposing for COVID-19: Approaches, challenges and promising candidates

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