Evidence map›Paper›PMID 35427787›Full record

ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2022

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India.

Chiranjib Chakraborty, Ashish Ranjan Sharma, Manojit Bhattacharya, Bidyut Mallik, Shyam Sundar Nandi, Sang-Soo Lee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. 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

6 authors.

Chiranjib ChakrabortyDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Barasat-Barrackpore Rd, Jagannathpur, Kolkata, West Bengal 700126, India. Electronic address: drchiranjib@yahoo.com.
Ashish Ranjan SharmaInstitute for Skeletal Aging &Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon, Gangwon-Do 24252, Republic of Korea.
Manojit BhattacharyaDepartment of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore 756020, Odisha, India.
Bidyut MallikDepartment of Applied Science, Galgotias College of Engineering and Technology, Knowledge Park-II, Greater Noida, Uttar Pradesh 201306, India.
Shyam Sundar NandiICMR-National Institute of Virology, (Mumbai unit), Indian Council of Medical Research, Haffkine Institute Compound, A. D. Marg, Parel, Mumbai, 400012, India.
Sang-Soo LeeInstitute for Skeletal Aging &Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon, Gangwon-Do 24252, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe massive increase in COVID-19 infection had generated a second wave in India during May-June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant.

methodsThis study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants.

resultsThe study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7.

conclusionThe increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.

Indexed as

COVID-19SARS-CoV-2Angiotensin-Converting Enzyme 2GenomicsHumansMutationPandemicsSpike Glycoprotein, CoronavirusUnited KingdomAngiotensin-Converting Enzyme 2Spike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Comparative genomicsEvolutionary epidemiologyReceptor bindingVariance of UK and India

Identifiers

PMID35427787
PMCPMC9005225

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.