Evidence map›Paper›PMID 35554909›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Bioinformatics-Based Approaches to Study Virus-Host Interactions During SARS-CoV-2 Infection.

Muhammad Saad Khan, Qudsia Yousafi, Shabana Bibi, Muhammad Azhar, Awais Ihsan

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Muhammad Saad KhanDepartment of Biosciences, COMSATS University Islamabad, Sahiwal, Pakistan.
Qudsia YousafiDepartment of Biosciences, COMSATS University Islamabad, Sahiwal, Pakistan.
Shabana BibiYunnan Herbal Laboratory, School of Ecology and Environmental Sciences, Yunnan University, Kunming, Yunnan, China.
Muhammad AzharDepartment of Biosciences, COMSATS University Islamabad, Sahiwal, Pakistan.
Awais IhsanDepartment of Biosciences, COMSATS University Islamabad, Sahiwal, Pakistan. awais.dr@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the knowledge of biomolecules is increasing from the last decades, it is helping the researchers to understand the unsolved issues regarding virology. Recent technologies in high-throughput sequencing are providing the swift generation of SARS-CoV-2 genomic data with the basic inside of viral infection. Owing to various virus-host protein interactions, high-throughput technologies are unable to provide complete details of viral pathogenesis. Identifying the virus-host protein interactions using bioinformatics approaches can assist in understanding the mechanism of SARS-CoV-2 infection and pathogenesis. In this chapter, recent integrative bioinformatics approaches are discussed to help the virologists and computational biologists in the identification of structurally similar proteins of human and SARS-CoV-2 virus, and to predict the potential of virus-host interactions. Considering experimental and time limitations for effective viral drug development, computational aided drug design (CADD) can reduce the gap between drug prediction and development. More research with respect to evolutionary solutions could be helpful to make a new pipeline for virus-host protein-protein interactions and provide more understanding to disclose the cases of host switch, and also expand the virulence of the pathogen and host range in developing viral infections.

Indexed as

COVID-19Computational BiologyHost Microbial InteractionsHost-Pathogen InteractionsHumansProteinsSARS-CoV-2ProteinsProtein domain interactionProtein interaction networksSARS-CoV-2 virusStructural bioinformaticsVirus–host protein–protein interactions

Identifiers

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Registered trials

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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.