Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike

Trigueiro-Louro, João; Correia, Vanessa; Figueiredo-Nunes, Inês; Gíria, Marta; Rebelo-de-Andrade, Helena

doi:10.1016/j.csbj.2020.07.017

Cited by 30 publications

(42 citation statements)

References 101 publications

(134 reference statements)

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“…All five of the favorable sites reported ( Fig 16 ) were also predicted within specific sequence regions identified by Trigueiro-Louro et al, as having favorable druggability properties [ 120 ]. The overlap of our results for S2 and the residues identified by Trigueiro-Louro et al, [ 120 ] are shown in ( Fig 17 ).…”

Section: Resultsmentioning

confidence: 73%

“…We present results for five favorable representative aromatic pharmacophore sites identified within the TOP50 S2 Spike segment ( Fig 16 ). The S2 segment also has been recently analyzed in detail Trigueiro-Louro et al, to identify segments that are attractive to target with regards to sequence/structure conservation between beta coronavirus strains as well as predicted druggability by residue [ 120 ]. All five of the favorable sites reported ( Fig 16 ) were also predicted within specific sequence regions identified by Trigueiro-Louro et al, as having favorable druggability properties [ 120 ].…”

Section: Resultsmentioning

confidence: 99%

“…The S2 segment also has been recently analyzed in detail Trigueiro-Louro et al, to identify segments that are attractive to target with regards to sequence/structure conservation between beta coronavirus strains as well as predicted druggability by residue [ 120 ]. All five of the favorable sites reported ( Fig 16 ) were also predicted within specific sequence regions identified by Trigueiro-Louro et al, as having favorable druggability properties [ 120 ]. The overlap of our results for S2 and the residues identified by Trigueiro-Louro et al, [ 120 ] are shown in ( Fig 17 ).…”

Section: Resultsmentioning

confidence: 99%

“… All residues identified as having a high druggability and sequence-conservation by [ 120 ] are shown as small gray or black squares at the top of the figure. Black indicates a higher sequence conservation compared to gray between more distantly related coronaviruses (SARS, MERs, etc).…”

Section: Resultsmentioning

confidence: 99%

“…Ligand efficiencies of the TOP50 sites (according to residues provided S1 Table in S1 File ) are shown as either blue or red dots as a function of residue. Blue dots are pharmacophore sites (and corresponding residues) not identified in the analysis of Trigueiro-Louro et al, [ 120 ] whereas red dots indicate binding site residues identified as a Union of both datasets. The residues that define pharmacophore Sites 01, 02, 03, 05, and 07 exhibit high relative ligand efficiency to other sites on the S2 Spike protein and were also identified by Trigueiro-Louro et al, [ 120 ].…”

Section: Resultsmentioning

confidence: 99%

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Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

Freidel

Armen

2021

PLoS ONE

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The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2’-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein.

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Section: Resultsmentioning

confidence: 73%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

Freidel

Armen

2021

PLoS ONE

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Using machine‐learning‐driven approaches to boost hot‐spot's knowledge

Rosário‐Ferreira

Bonvin

Moreira

2022

WIREs Comput Mol Sci

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Understanding protein-protein interactions (PPIs) is fundamental to describe and to characterize the formation of biomolecular assemblies, and to establish the energetic principles underlying biological networks. One key aspect of these interfaces is the existence and prevalence of hot-spots (HS) residues that, upon mutation to alanine, negatively impact the formation of such proteinprotein complexes. HS have been widely considered in research, both in case studies and in a few large-scale predictive approaches. This review aims to pre-

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COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity

et al. 2022

Self Cite

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COVID-19 is a new complex multisystem disease caused by the novel coronavirus SARS-CoV-2. In slightly over 2 years, it infected nearly 500 million and killed 6 million human beings worldwide, causing an unprecedented coronavirus pandemic. Currently, the international scientific community is engaged in elucidating the molecular mechanisms of the pathophysiology of SARS-CoV-2 infection as a basis of scientific developments for the future control of COVID-19. Global exome and genome analysis efforts work to define the human genetics of protective immunity to SARS-CoV-2 infection. Here, we review the current knowledge regarding the SARS-CoV-2 infection, the implications of COVID-19 to Public Health and discuss genotype to phenotype association approaches that could be exploited through the selection of candidate genes to identify the genetic determinants of severe COVID-19.

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Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike

Abstract: Graphical abstract

Cited by 30 publications

References 101 publications

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

Using machine‐learning‐driven approaches to boost hot‐spot's knowledge

COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity

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