Evidence map›Paper›PMID 38058625›Full record

ArticleHeliyon2023

Yasir Arfat, Imran Zafar, Sheikh Arslan Sehgal, Mazhar Ayaz, Muhammad Sajid, Jamal Muhammad Khan, Muhammad Ahsan, Mohd Ashraf Rather, Azmat Ali Khan, Jamilah M Alshehri and 4 more

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

14 authors at 9 institutions in 5 countries.

Yasir ArfatDepartment of Biotechnology, Faculty of Life Sciences, University of Okara, Okara, 56300, Pakistan.
Imran ZafarDepartment of Bioinformatics and Computational Biology, Virtual University, Punjab, 54700, Pakistan.
Sheikh Arslan SehgalDepartment of Bioinformatics, Institute of Biochemistry, Biotechnology and Bioinformatics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan.
Mazhar AyazDepartment of Parasitology, Faculty of Veterinary Science, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan.
Muhammad SajidDepartment of Biotechnology, Faculty of Life Sciences, University of Okara, Okara, 56300, Pakistan.
Jamal Muhammad KhanDepartment of Parasitology, Faculty of Veterinary Science, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan.
Muhammad AhsanDepartment of Environmental Sciences, Institute of Environmental and Agricultural Sciences, University of Okara, Okara, 56300, Pakistan.
Mohd Ashraf RatherDivision of Fish Genetics and Biotechnology, Faculty of Fisheries, Rangil- Gandarbal (SKAUST-K), India.
Azmat Ali KhanPharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia.
Jamilah M AlshehriPharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia.
Shopnil AkashDepartment of Pharmacy, Faculty of Allied Health Sciences, Daffodil International, University, Dhaka, Bangladesh.
Eugenie NepovimovaDepartment of Chemistry, Faculty of Science, University of Hradec Králové, Hradec Králové, 50 003, Czech Republic.
Kamil KucaDepartment of Chemistry, Faculty of Science, University of Hradec Králové, Hradec Králové, 50 003, Czech Republic.
Rohit SharmaDepartment of Rasashastra and Bhaishajya Kalpana, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India.
University of Okara · PKKing Saud University · SAUniversity of Veterinary and Animal Sciences · PKDaffodil International University · BDInstitute of Medical Sciences · INIslamia University of Bahawalpur · PKUniversity Hospital Hradec Králové · CZUniversity of Hradec Králové · CZVirtual University of Pakistan · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the role of the mitogen-activated protein kinases (MAPKs) signalling pathway is essential in advancing treatments for neurodegenerative disorders like Alzheimer's. In this study, we investigate in-silico techniques involving computer-based methods to extract the MAPK1 sequence. Our applied methods enable us to analyze the protein's structure, evaluate its properties, establish its evolutionary relationships, and assess its prevalence in populations. We also predict epitopes, assess their ability to trigger immune responses, and check for allergenicity using advanced computational tools to understand their immunological properties comprehensively. We apply virtual screening, docking, and structure modelling to identify promising drug candidates, analyze their interactions, and enhance drug design processes. We identified a total of 30 cell-targeting molecules against the MAPK1 protein, where we selected top 10 CTL epitopes (PAGGGPNPG, GGGPNPGSG, SAPAGGGPN, AVSAPAGGG, AGGGPNPGS, ATAAVSAPA, TAAVSAPAG, ENIIGINDI, INDIIRTPT, and NDIIRTPTI) for further evaluation to determine their potential efficacy, safety, and suitability for vaccine design based on strong binding potential. The potential to cover a large portion of the world's population with these vaccines is substantial-88.5 % for one type and 99.99 % for another. In exploring the molecular docking analyses, we examined a library of compounds from the ZINC database. Among them, we identified twelve compounds with the lowest binding energy. Critical residues in the MAPK1 protein, such as VAL48, LYS63, CYS175, ASP176, LYS160, ALA61, LEU165, TYR45, SER162, ARG33, PRO365, PHE363, ILE40, ASN163, and GLU42, are pivotal for interactions with these compounds. Our result suggests that these compounds could influence the protein's behaviour. Moreover, our docking analyses revealed that the predicted peptides have a strong affinity for the MAPK1 protein. These peptides form stable complexes, indicating their potential as potent inhibitors. This study contributes to the identification of new drug compounds and the screening of their desired properties. These compounds could potentially help reduce the excessive activity of MAPK1, which is linked to Alzheimer's disease.

Indexed as

AlzheimerMAPK1Molecular dockingMultiepitopePharmacophoreVaccine designVirtual screeningZebrafish

Identifiers

PMID38058625
PMCPMC10695983
OpenAlexW4388609506

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.