Corpus overview


Overview

MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

NSP2 (19)

NSP3 (8)

ComplexRdRp (7)

ProteinS (7)

NSP12 (4)


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SARS-CoV-2 Proteins
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    The SARS-CoV-2 Nsp3 HGNC macrodomain reverses PARP9 HGNC/ DTX3L HGNC-dependent ADP-ribosylation MESHD induced by interferon signalling

    Authors: Lilian Cristina Russo; Rebeka Tomasin; Isaac Araújo Matos; Antonio Carlos Manucci; Sven T Sowa; Katie Dale; Keith W Caldecott; Lari Lehtiö; Deborah Schechtman; Flávia Carla Meotti; Alexandre Bruni-Cardoso; Nicolas Carlos Hoch

    doi:10.1101/2021.04.06.438552 Date: 2021-04-07 Source: bioRxiv

    SARS-CoV- 2 non-structural protein PROTEIN 3 ( Nsp3 HGNC) contains a macrodomain that is essential for virus replication and is thus an attractive target for drug development. This macrodomain is thought to counteract the host interferon (IFN) response, an important antiviral signalling cascade, via the removal of ADP-ribose modifications catalysed by host poly(ADP-ribose) polymerases ( PARPs HGNC). Here, we show that activation of the IFN HGNC response induces ADP-ribosylation of host proteins MESHD and that ectopic expression of the SARS-CoV-2 Nsp3 HGNC macrodomain reverses this modification in human cells. We further demonstrate that this can be used to screen for cell-active macrodomain inhibitors without the requirement for BSL-3 facilities. This IFN HGNC-induced ADP-ribosylation MESHD is dependent on the PARP9 HGNC/ DTX3L HGNC heterodimer, but surprisingly the expression of Nsp3 HGNC macrodomain or PARP9 HGNC/ DTX3L HGNC deletion do not impair STAT1 HGNC phosphorylation or the induction of IFN HGNC-responsive genes. Our results suggest that PARP9 HGNC/ DTX3L HGNC-dependent ADP-ribosylation MESHD is a downstream effector of the host IFN HGNC response and that the cellular function of the SARS-CoV-2 Nsp3 HGNC macrodomain is to hydrolyse this end product of IFN HGNC signalling, and not to suppress the IFN HGNC response itself.

    Differential mutational profile of SARS-CoV-2 proteins across deceased and asymptomatic patients

    Authors: Rezwanuzzaman Laskar; Safdar Ali

    doi:10.1101/2021.03.31.437815 Date: 2021-03-31 Source: bioRxiv

    The SARS-CoV-2 infection MESHD spread at an alarming rate with many places showed multiple peaks in incidence. Present study involves a total of 332 SARS-CoV-2 sequences from 114 Asymptomatic and 218 Deceased patients from twenty-one different countries. The mining of mutations was done using the GISAID CoVSurver (www.gisaid.org/epiflu-applications/covsurver-mutations-app) with the reference sequence hCoV-19/Wuhan/WIV04/2019 present in NCBI with Accession number NC-045512.2. The impact of the mutations on SARS-CoV-2 proteins mutation was predicted using PredictSNP1(loschmidt.chemi.muni.cz/predictsnp1) which is a meta-server integrating six predictor tools: SIFT, PhD-SNP, PolyPhen-1, PolyPhen-2, MAPP and SNAP. The iStable integrated server (predictor.nchu.edu.tw/iStable) was used to predict shifts in the protein stability due to mutations. A total of 372 variants were observed in the 332 SARS-CoV-2 sequences with several variants incident in multiple patients accounting for a total of 1596 incidences. Asymptomatic and Deceased specific mutants constituted 32% and 62% of the repertoire respectively indicating their exclusivity. However, the most prevalent mutations were those present in both. Though some parts of the genome are more variable than others but there was clear difference between incidence and prevalence. NSP3 HGNC NSP3 PROTEIN with 68 variants had total occurrence of only 105 whereas Spike protein PROTEIN had 346 occurrences with just 66 variants. For Deleterious variants, NSP3 HGNC NSP3 PROTEIN had the highest incidence of 25 followed by NSP2 HGNC NSP2 PROTEIN (16), ORF3a PROTEIN (14) and N (14). Spike protein PROTEIN had just 7 Deleterious variants out of 66. Deceased patients have more Deleterious than Neutral variants as compared to the symptomatic ones. Further, it appears that the Deleterious variants which decrease protein stability are more significant in pathogenicity of SARS-CoV-2.

    Structure, Mechanism and Crystallographic fragment screening of the SARS-CoV-2 NSP13 PROTEIN helicase

    Authors: Joseph A Newman; Alice Douangamath; Setayesh Yazdani; Yuliana Yosaatmadja; Anthony Aimon; Jose Brandao-Neto; Louise Dunnett; Tyler Gorrie-Stone; Rachael Skyner; Daren Fearon; Matthieu Schapira; Frank von Delft; Opher Gileadi

    doi:10.1101/2021.03.15.435326 Date: 2021-03-15 Source: bioRxiv

    The global COVID-19 pandemic MESHD is caused by the SARS-CoV-2 virus MESHD and has infected over 100 million and caused over 2 million fatalities worldwide at the point of writing. There is currently a lack of effective drugs to treat people infected MESHD with SARS-CoV-2. The SARS-CoV- 2 Non-structural protein PROTEIN 13 ( NSP13 PROTEIN) is a superfamily1B helicase that has been identified as a possible target for anti-viral drugs due to its high sequence conservation and essential role in viral replication. In this study we present crystal structures of SARS-CoV-2 NSP13 PROTEIN solved in the APO form and in the presence of both phosphate and the non-hydrolysable ATP analogue (AMP-PNP). Comparisons of these structures reveal details of global and local conformational changes that are induced by nucleotide binding and hydrolysis and provide insights into the helicase mechanism and possible modes of inhibition. Structural analysis reveals two pockets on NSP13 PROTEIN that are classified as "druggable" and include one of the most conserved sites in the entire SARS-CoV-2 proteome. To identify possible starting points for anti-viral drug development we have performed a crystallographic fragment screen against SARS-CoV-2 NSP13 PROTEIN helicase. The fragment screen reveals 65 fragment hits across 52 datasets, with hot spots in pockets predicted to be of functional importance, including the druggable nucleotide and nucleic acid binding sites, opening the way to structure guided development of novel antiviral agents.

    Repurposing Multi-Targeting Plant Natural Product Scaffolds In Silico Against SARS-CoV- 2 Non-Structural Proteins PROTEIN Implicated in Viral Pathogenesis

    Authors: Von Novi de Leon; Joe Anthony Manzano; Delfin Yñigo H. Pilapil; Rey Arturo T. Fernandez; James Kyle Ching; Mark Tristan J. Quimque; Kin Israel Notarte; Allan Patrick Macabeo

    doi:10.26434/chemrxiv.14125433.v1 Date: 2021-03-01 Source: ChemRxiv

    Background: Accessing COVID-19 MESHD vaccines is a challenge despite successful clinical trials. This burdens the COVID-19 MESHD treatment gap, thereby requiring accelerated discovery of anti-SARS-CoV-2 agents. Thus, this study explored the potential of anti-HIV reverse transcriptase (RT) phytochemicals as inhibitors of SARS-CoV- 2 non-structural proteins PROTEIN (nsps) by targeting in silico key sites in the structures of SARS-CoV-2 nsps. Moreover, structures of the anti-HIV compounds were considered for druggability and toxicity MESHD. 104 anti-HIV phytochemicals were subjected to molecular docking with papain-like protease PROTEIN ( nsp3 HGNC), 3-chymotrypsin-like protease ( nsp5 HGNC), RNA-dependent RNA polymerase PROTEIN (nsp12), helicase HGNC (nsp13), SAM-dependent 2’-O-methyltransferase (nsp16) and its cofactor (nsp10), and endoribonuclease (nsp15). Drug-likeness MESHD and ADME (absorption, distribution, metabolism, and excretion) properties of the top ten compounds per nsp were predicted using SwissADME. Their toxicity MESHD was also determined using OSIRIS Property Explorer. Results: Among the twenty-seven top-scoring compounds, the polyphenolic natural products amentoflavone (1), robustaflavone (4), punicalin (9), volkensiflavone (11), rhusflavanone (13), morelloflavone (14), hinokiflavone (15), and michellamine B (19) were multi-targeting and had the strongest affinities to at least two of the nsps (Binding Energy = -7.7 to -10.8 kcal/mol). Friedelin (2), pomolic acid (5), ursolic acid (10), garcisaterpenes A (12), hinokiflavone (15), and digitoxigenin-3-O-glucoside (17) were computationally druggable. Moreover, compounds 5 and 17 showed good gastrointestinal absorptive property. Most of the compounds were also predicted to be non-toxic. Conclusions: Twenty anti-HIV RT phytochemicals showed multi-targeting inhibitory potential against SARS-CoV-2 nsp3 HGNC, 5, 10, 12, 13, 15, and 16, and can therefore be used as prototypes for anti- COVID-19 MESHD drug design.

    Detection of the new SARS-CoV-2 variant B.1.526 with the Spike E484K mutation in South America

    Authors: Juan Fernández Cadena; Mindy Muñoz; Gabriel Morey León; Rubén Armas-González; Darlyn Amaya Márquez; Katheryn Sacheri Viteri; Paúl Cárdenas & USFQ-COVID Consortium; Fernando Valiente-Echeverría; Ricardo Soto Rifo; Derly Andrade Molina

    doi:10.21203/rs.3.rs-248965/v1 Date: 2021-02-17 Source: ResearchSquare

    Here, we report two sequences of the new SARS-CoV-2 variant recently detected and designed as B.1.526. This variant carries the immune escape-associated mutation E484K and additional mutations in the S, N, NSP2 PROTEIN NSP2 HGNC, NSP3 HGNC NSP3 PROTEIN, NSP4 PROTEIN NSP4 HGNC, NSP6 PROTEIN, NSP8 PROTEIN, NSP12 PROTEIN and NSP13 PROTEIN genes. Viral sequences were obtained from an individual traveling from the US to Equator with a negative RT-PCR and from one of his closest contacts that became infected. These cases should be considered an alert for the potential circulation of a new variant of concern with the E484K mutation in South America

    Identification of novel candidate CD8 HGNC+ T cell epitopes of the SARS-CoV2 with homology to other seasonal coronaviruses

    Authors: Pradeep Pushpakumara; Deshan Madusanka; Saubhagyagya Danasekara; Chandima Jeewandara; Graham Ogg; Gathsaurie Neelika Malavige

    doi:10.21203/rs.3.rs-228306/v1 Date: 2021-02-10 Source: ResearchSquare

    Background Individuals who have not been exposed to the SARS-CoV2 virus have been shown to have T cells that respond to the virus, possibly due to the presence of cross-reactive T cell responses to other seasonal human coronaviruses (HCoVs). Such cross-reactive T cell immunity may lead to immunopathology or protection.Results To understand the influence of such cross-reactive T cell responses, we used IEDB (Immune epitope database) and NetMHCpan (ver. 4.1) to identify candidate CD8 HGNC + T cell epitopes, restricted through HLA-A and B alleles, which are seen in a frequency of > 10% in the Sri Lankan population. Conservation analysis was carried out for these candidate epitopes with the HCoVs, OC43, HKU1, NL63 and with the current circulating different variants of SARS-CoV2. 12/18 the candidate CD8 HGNC + T cell epitopes (binding score of ≥ 0.90), which had a high degree of homology (> 75%) with the other three HCoVs were within the NSP12 PROTEIN and NSP13 PROTEIN proteins. They were predicted to be restricted through HLA-A HGNC*2402, HLA-A HGNC*201, HLA-A HGNC*206 and HLA-B HGNC alleles B*3501. 31 candidate CD8 HGNC + T cell epitopes that were specific to SARS-CoV2 virus (< 25% homology with other HCoVs) were predominantly identified within the structural proteins (spike PROTEIN, envelop, membrane and nucleocapsid) and the NSP1 HGNC, NSP2 PROTEIN NSP2 HGNC and NSP3 PROTEIN NSP3 HGNC. They were predominantly restricted through HLA-B HGNC*3501 (6/31), HLA-B HGNC*4001 (6/31), HLA-B HGNC*4403(7/31) and HLA-A HGNC*2402 (8/31). The candidate CD8 HGNC + T cell epitopes that were homologous or were specific, with a binding score of ≥ 0.90, were found to be highly conserved within the SARS-CoV2 variants identified so far.Conclusions It would be crucial to understand T cell responses that associate with protection and the differences in the functionality and phenotype of epitope specific T cell responses, presented through different HLA alleles common in different geographical groups in order to understand disease pathogenesis.

    Genomic diversity analysis of SARS-CoV-2 genomes in Rwanda

    Authors: Nzungize Lambert; Ndishimye Pacifique; Fathiah Zakham; François Balloux; Meghna Sobti; Peter Schofield; Helen Lenthall; Jennifer Jackson; Stephanie Ubiparipovic; Jake Y Henry; Arunasingam Abayasingam; Deborah Burnett; Anthony Kelleher; Robert Brink; Rowena A Bull; Stuart Turville; Alastair G Stewart; Christopher C Goodnow; William D Rawlinson; Daniel Christ; Randeep Guleria; Krishna Ella; Balram Bhargava; Steven De Jonghe; Jasper Rymenants; Vincenzo Summa; Enzo Tramontano; Andrea Rosario Beccari; Pieter Leyssen; Paola Storici; Johan Neyts; Philip Gribbon; Andrea Zaliani

    doi:10.1101/2020.12.14.422793 Date: 2020-12-15 Source: bioRxiv

    COVID-19 MESHD ( Coronavirus disease 2019 MESHD) is an emerging pneumonia-like respiratory disease MESHD of humans and is recently spreading across the globe. To analyze the genome sequence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2 MESHD) isolated from Rwanda with other viral strains from African countries. We downloaded 75 genomes sequences of clinical SARS-CoV-2 from the GISAID (global initiative on sharing all influenza data) database and we comprehensively analyzed these SARS-CoV-2 genomes sequences alongside with Wuhan SARS-CoV-2 MESHD sequences as the reference strains. We analyzed 75 genomes sequences of SARS-CoV-2 isolated in different African countries including 10 samples of SARS-CoV-2 isolated in Rwanda between July and August 2020. The phylogenetic analysis of the genome sequence of SARS-CoV-2 revealed a strong identity with reference strains between 90-95%. We identified a missense mutation in four proteins including orf1ab polyprotein, NSP2 HGNC NSP2 PROTEIN, 2'-O-ribose methyltransferase and orf1a PROTEIN polyprotein. The most common changes in the base are C > T. We also found that all clinically SARS-CoV-2 isolated from Rwanda had genomes belonging to clade G and lineage B.1. Tracking the genetic evolution of SARS-CoV-2 over time is important to understand viral evolution pathogenesis. These findings may help to implement public health measures in curbing COVID-19 MESHD in Rwanda.

    Computational Analysis of Dynamic Allostery and Control in the three SARS-CoV- 2 non-structural proteins PROTEIN

    Authors: Igors Dubanevics; Charles Heaton; Carlos Riechmann; Tom C B McLeish; Theresa A Ramelot; Thomas B. Acton; Elena Moreno; Thomas Kehrer; Catherine A. Royer; Adolfo Garcia-Sastre; Robert M Krug; Gaetano T. Montelione

    doi:10.1101/2020.12.12.422477 Date: 2020-12-14 Source: bioRxiv

    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the COVID-19 pandemic MESHD, has no vaccine or antiviral drugs available to the public, at the time of writing. The virus non-structural proteins are promising drug targets because of their vital role in the viral cycle. A significant body of work has been focused on finding inhibitors which covalently and competitively bind the active site of the non-structural proteins, but little has been done to address regions other than the active site, i.e. for non-competitive inhibition. Here we extend previous work on the SARS-CoV-2 Mpro PROTEIN ( nsp5 HGNC) to three other SARS-CoV-2 proteins: host shutoff factor PROTEIN ( nsp1 HGNC), papain-like protease PROTEIN ( nsp3 HGNC, also known as PLpro PROTEIN) and RNA-dependent RNA-polymerase PROTEIN (nsp12, also known as RdRp) in complex PROTEIN with nsp7 and nsp8 cofactors. Using open-source software (DDPT) to construct Elastic Network Models (ENM) of the chosen proteins we analyse their fluctuation dynamics and thermodynamics, as well as using this protein family to study convergence and robustness of the ENM. Exhaustive 2-point mutational scans of the ENM and their effect on fluctuation free energies suggest several new candidate regions, distant from the active site, for control of the proteins function, which may assist the drug development based on the current small molecule binding screens. The results also provide new insights, including non-additive effects of double-mutation or inhibition, into the active biophysical research field of protein fluctuation allostery and its underpinning dynamical structure.

    Different mutations in SARS-CoV-2 associate with severe and mild outcome

    Authors: Adam Nagy; Sandor Pongor; Balazs Gyorffy

    doi:10.1101/2020.10.16.20213710 Date: 2020-10-20 Source: medRxiv

    Introduction. Genomic alterations in a viral genome can lead to either better or worse outcome and identifying these mutations is of utmost importance. Here, we correlated protein-level mutations in the SARS-CoV-2 virus to clinical outcome. Methods. Mutations in viral sequences from the GISAID virus repository were evaluated by using hCoV-19/Wuhan/WIV04/2019 as the reference. Patient outcomes were classified as mild disease, hospitalization and severe disease ( death MESHD or documented treatment in an intensive-care unit). Chi-square test was applied to examine the association between each mutation and patient outcome. False discovery rate was computed to correct for multiple hypothesis testing and results passing a FDR cutoff of 5% were accepted as significant. Results. Mutations were mapped to amino acid changes for 2,120 non-silent mutations. Mutations correlated to mild outcome were located in the ORF8 PROTEIN, NSP6 PROTEIN, ORF3a PROTEIN, NSP4 PROTEIN NSP4 HGNC, and in the nucleocapsid phosphoprotein N. Mutations associated with inferior outcome were located in the surface ( S) glycoprotein PROTEIN, in the RNA dependent RNA polymerase PROTEIN, in the 3'-to5' exonuclease, in ORF3a PROTEIN, NSP2 HGNC NSP2 PROTEIN and N. Mutations leading to severe outcome with low prevalence were found in the surface ( S) glycoprotein PROTEIN and in NSP7 PROTEIN. Five out of 17 of the most significant mutations mapped onto a 10 amino acid long phosphorylated stretch of N indicating that in spite of obvious sampling restrictions the approach can find functionally relevant sites in the viral genome. Conclusions. We demonstrate that mutations in the viral genes may have a direct correlation to clinical outcome. Our results help to quickly identify SARS-CoV-2 infections MESHD harboring mutations related to severe outcome.

    Global BioID-based SARS-CoV-2 proteins proximal interactome unveils novel ties between viral polypeptides and host factors involved in multiple COVID19 MESHD-associated mechanisms

    Authors: Estelle MN Laurent; Yorgos Sofianatos; Anastassia Komarova; Jean-Pascal Gimeno; Payman Samavarchi Tehrani; Dae-Kyum Kim; Hala Abdouni; Marie Duhamel; Patricia Cassonnet; Jennifer J Knapp; Da Kuang; Aditya Chawla; Dayag Sheykhkarimli; Ashyad Rayhan; Roujia Li; Oxana Pogoutse; David E Hill; Mike E Calderwood; Pascal Falter-Braun; Patrick Aloy; Ulrich Stelzl; Marc Vidal; Anne-Claude Gingras; Georgios A Pavlopoulos; Sylvie Van Der Werf; Isabelle Fournier; Frederick P Roth; Michel Salzet; Caroline Demeret; Yves Jacob; Etienne Coyaud; Joseph Newman; Amin S Asfor; Alison Burman; Sylvia Crossley; John Hammond; Elma Tchilian; Bryan Charleston; Dalan Bailey; Tobias J Tuthill; Simon Graham; Tomas Malinauskas; Jiandong Huo; Julia Tree; Karen Buttigieg; Ray Owens; Miles Carroll; Rod Daniels; John McCauley; Kuan-Ying A Huang; Mark Howarth; Alain Townsend

    doi:10.1101/2020.08.28.272955 Date: 2020-08-29 Source: bioRxiv

    The worldwide SARS-CoV-2 outbreak poses a serious challenge to human societies and economies. SARS-CoV-2 proteins orchestrate complex pathogenic mechanisms that underlie COVID-19 MESHD disease. Thus, understanding how viral polypeptides rewire host protein networks enables better-founded therapeutic research. In complement to existing proteomic studies, in this study we define the first proximal interaction network of SARS-CoV-2 proteins, at the whole proteome level in human cells. Applying a proximity-dependent biotinylation (BioID)-based approach greatly expanded the current knowledge by detecting interactions within poorly soluble compartments, transient, and/or of weak affinity in living cells. Our BioID study was complemented by a stringent filtering and uncovered 2,128 unique cellular targets (1,717 not previously associated with SARS-CoV-1 or 2 proteins) connected to the N- and C-ter BioID-tagged 28 SARS-CoV-2 proteins by a total of 5,415 (5,236 new) proximal interactions. In order to facilitate data exploitation, an innovative interactive 3D web interface was developed to allow customized analysis and exploration of the landscape of interactions (accessible at http://www.sars-cov-2-interactome.org/). Interestingly, 342 membrane proteins including interferon and interleukin pathways factors, were associated with specific viral proteins. We uncovered ORF7a PROTEIN and ORF7b PROTEIN protein proximal partners that could be related to anosmia and ageusia symptoms. Moreover, comparing proximal interactomes in basal and infection-mimicking conditions (poly(I:C) treatment) allowed us to detect novel links with major antiviral response pathway components, such as ORF9b PROTEIN with MAVS HGNC and ISG20 HGNC; N with PKR HGNC and TARB2; NSP2 PROTEIN NSP2 HGNC with RIG-I HGNC and STAT1 HGNC; NSP16 PROTEIN with PARP9 HGNC- DTX3L HGNC. Altogether, our study provides an unprecedented comprehensive resource for understanding how SARS-CoV-2 proteins orchestrate host proteome remodeling and innate immune response evasion, which can inform development of targeted therapeutic strategies.

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins


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