In Silico Drug Discovery for Treatment of Virus Diseases.

Shikha Joon, Rajeev K Singla, Bairong Shen

Abstract read

In one paragraph

Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shikha Joon *Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Rajeev K Singla *Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Bairong ShenInstitutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China. bairong.shen@scu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral infections have remained a serious public health burden despite significant improvements in medical and pharmaceutical research in recent years. In silico approaches for drug discovery and design are fruitful for the management of a plethora of viral diseases. Virtual screening of libraries is performed using various computational tools to search for potential antiviral compounds. For this, a rational approach is used that comprises filtration of the screened compounds using docking, ligand- or pharmacophore-based similarity searches. The selected candidates are then tested in vitro to ascertain their biological activity. This minimizes the overall cost and time incurred in conventional drug designing methods. In this book chapter, we have discussed various methods of drug discovery and design, and their applications for the development of effective antiviral compounds. A descriptive methodology for the management of some common and notorious viral diseases is also outlined.

Indexed as

Drug DiscoveryVirus DiseasesAntiviral AgentsDrug DesignHumansLigandsMolecular Docking SimulationAntiviral AgentsLigandsAntiviral compoundsDockingIn silico drug discovery and designLigandPharmacophoreViral diseasesVirtual screening

Identifiers

PMID35594021

DOI10.1021/ja1098325

What OpenQuestion holds

Textmetadata

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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.