Evidence map›Paper›PMID 33344905›Full record

ArticleACS pharmacology & translational science2020

Vaccine Formulation and Optimization for Human Herpes Virus-5 through an Immunoinformatics Framework.

Neeraj Kumar, Damini Sood, Ramesh Chandra

Open access · greenAbstract read
In one paragraph

Article in ACS pharmacology & translational science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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 at 1 institution in 1 country.

Neeraj KumarDepartment of Chemistry, University of Delhi, Delhi 110007, India.
Damini SoodDepartment of Chemistry, University of Delhi, Delhi 110007, India.
Ramesh ChandraDepartment of Chemistry, University of Delhi, Delhi 110007, India.
University of Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current situation, the importance of vaccines for viral diseases has become the need of the hour. The scientific community in the field of virology has taken it upon themselves to develop vaccines for viral infections before an epidemic or pandemic situation arises. Human herpes virus-5 is an emerging situation that has alarming cases with major health concerns, including congenital impairments and infections leading to cancer states. Vaccination is the route most likely to succeed in the battleground with viral infections and consequences. Hence in the present manuscript, we have formulated the multiepitope subunit vaccine and optimized it with the advanced computational immunological framework. As a result, we report the subunit vaccine for HHV-5, comprised of promiscuous cytotoxic T-lymphocytes epitopes, helper T-lymphocytes, and B-cell epitopes engineered with putative adjuvants to ensure the strong immune response. The formulated subunit vaccine depicted high antigenicity and immunogenicity along with sustainable physicochemical characteristics. Molecular dynamics simulation analyses revealed the strong binding of the vaccine with MHC receptors (MHC-1 and MHC-2) and the virus progression specific membrane receptor TLR2 for a 100 ns MD simulation run. The interacting trajectory analysis of the vaccine showed stable binding with minimal deviations through RMSD, RMSF, and secondary structure confinement plot analyses for a long span of 100 ns. Interestingly, the vaccine showed robust immune response statistics for a prolonged time with evoking T-cell and B-cell populations with other vital players of the immune system, through the machine learning-based immune simulation approach. This study paved the way to a multiepitope vaccine for HHV-5 employing the immunoinformatics networks.

Identifiers

PMID33344905
PMCPMC7737318
OpenAlexW3105752868

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.