Evidence map›Paper›PMID 33348379›Full record

ReviewBriefings in bioinformatics2021

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies.

Vaishali P Waman, Neeladri Sen, Mihaly Varadi, Antoine Daina, Shoshana J Wodak, Vincent Zoete, Sameer Velankar, Christine Orengo

Open access · hybridAbstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 47 citations in OpenAlex.

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  17. Online biophysical predictions for SARS-CoV-2 proteins.BMC molecular and cell biology · 2021
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  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 3 countries.

Vaishali P WamanOrengo group, UCL.
Neeladri SenOrengo group, UCL.
Mihaly VaradiProtein Data Bank in Europe-Knowledge Base.
Antoine DainaMolecular Modeling Group at SIB, Swiss Institute of Bioinformatics.
Shoshana J WodakColumbia University, USA.
Vincent ZoeteDepartment of Fundamental Oncology at the University of Lausanne and Group leader at SIB.
Sameer VelankarProtein Data Bank in Europe.
Christine OrengoUniversity College London.
Worldwide Protein Data BankColumbia University · USSIB Swiss Institute of Bioinformatics · CHUniversity College London · GB

Funding

Wellcome Trust 104948
6 · The paper itself

Abstract

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

Indexed as

Computational BiologyCOVID-19 Drug TreatmentAntiviral AgentsCOVID-19HumansProtein ConformationSARS-CoV-2Viral ProteinsAntiviral AgentsViral Proteinsmutation/variationprotein 3D structuresSARS-CoV-2structural bioinformaticsstructure predictiontherapeutics

Identifiers

PMID33348379
PMCPMC7799268
OpenAlexW3114897634

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.