Evidence map›Paper›PMID 41094020›Full record

ArticleScientific reports2025

Identification of novel DYRK1A inhibitors as treatment options for alzheimer's disease through comprehensive in silico approaches.

Ibrahim Akindeji Makinde, Sheriffdeen Oladimeji Hammed, Neeraj Kumar, Najwa Ahmad Kuthi, Haruna Isiyaku Umar, Temitayo Abidat Hassan, Idayat Oyinkansola Kehinde, Ridwan Opeyemi Bello, Abdullahi Tunde Aborode, Tajudeen Ogundare Jimoh and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Ibrahim Akindeji MakindeDepartment of Information Systems, School of Computing (SOC), Federal University of Technology Akure, P.M.B 704, Akure, Nigeria.
Sheriffdeen Oladimeji HammedDepartment of Biotechnology, Federal University of Technology, P. M. B. 704, Akure, Nigeria.
Neeraj KumarDepartment of Pharmaceutical Chemistry, Bhupal Nobles' College of Pharmacy, Udaipur, 313001, Rajasthan, India.
Najwa Ahmad KuthiDepartment of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia.
Haruna Isiyaku UmarComputer-Aided Therapeutic Discovery and Design Laboratory, Federal University of Technology, P. M. B. 704, Akure, Nigeria. ariwajoye3@gmail.com.
Temitayo Abidat HassanComputer-Aided Therapeutic Discovery and Design Laboratory, Federal University of Technology, P. M. B. 704, Akure, Nigeria.
Idayat Oyinkansola KehindeComputer-Aided Therapeutic Discovery and Design Laboratory, Federal University of Technology, P. M. B. 704, Akure, Nigeria.
Ridwan Opeyemi BelloComputer-Aided Therapeutic Discovery and Design Laboratory, Federal University of Technology, P. M. B. 704, Akure, Nigeria.
Abdullahi Tunde AborodeComputer-Aided Therapeutic Discovery and Design Laboratory, Federal University of Technology, P. M. B. 704, Akure, Nigeria.
Tajudeen Ogundare JimohDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Al-Djazouli O MahamatFaculty of Exact Applied and Sciences, Department of Earth Sciences, N Djamena University, N Djamena, Chad. djazoulimahamatresearcher@gmail.com.
Mohammad KhalidDepartment of Pharmaceutics, College of Pharmacy, King Khalid University, Abha, 61421, Asir, Saudi Arabia.
Omar A AlmohammedDepartment of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. oalmohammed@KSU.EDU.SA.

Funding

King Saud University ORF-2025-77
6 · The paper itself

Abstract

This study aims to identify potential DYRK1A inhibitors from a curated database and utilize a QSAR model to predict the bioactivity of drug compounds in inhibiting the enzyme involved in tau protein oligomerization, a key process in AD pathology. 192 compounds were sourced from the SuperNatural 3.0 database and docked against DYRK1A using Maestro 12.5. The top five lead compounds and the reference drug Abemaciclib underwent ADMET profiling via the AI Drug Lab Server and a 200 nanosecond molecular dynamics simulation using Desmond. A machine learning-based Quantitative Structure-Activity Relationship (QSAR) analysis was then performed to predict their biological activity based on pIC

Indexed as

Alzheimer DiseaseProtein Kinase InhibitorsProtein Serine-Threonine KinasesProtein-Tyrosine KinasesAminopyridinesBenzimidazolesComputer SimulationDyrk KinasesHumansMolecular Docking SimulationMolecular Dynamics SimulationQuantitative Structure-Activity RelationshipabemaciclibAminopyridinesBenzimidazolesDyrk KinasesProtein Kinase InhibitorsProtein Serine-Threonine KinasesProtein-Tyrosine KinasesAlzheimer’s diseaseDYRK1A inhibitorsMachine learningMolecular dockingQSARVirtual screening

Identifiers

PMID41094020
PMCPMC12528759

What OpenQuestion holds

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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.