Evidence map›Paper›PMID 38516192›Full record

ArticleFrontiers in molecular biosciences2024

Revealing innovative JAK1 and JAK3 inhibitors: a comprehensive study utilizing QSAR, 3D-Pharmacophore screening, molecular docking, molecular dynamics, and MM/GBSA analyses.

Abdelmoujoud Faris, Ivana Cacciatore, Radwan Alnajjar, Hadni Hanine, Adnane Aouidate, Ramzi A Mothana, Abdullah R Alanzi, Menana Elhallaoui

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2024. 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
5.1field-weighted citation impact, top 4% 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

6 citing papers in PubMed, 14 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

8 authors at 5 institutions in 4 countries.

Abdelmoujoud FarisLIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
Ivana CacciatoreDepartment of Pharmacy, University 'G. d'Annunzio' of Chieti-Pescara, Chieti, Italy.
Radwan AlnajjarCADD Unit, PharmD, Faculty of Pharmacy, Libyan International Medical University, Benghazi, Libya.
Hadni HanineLIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
Adnane AouidateSchool of Applied Sciences of Ait Melloul, Ibn Zohr University, Fez, Morocco.
Ramzi A MothanaDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Abdullah R AlanziDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Menana ElhallaouiLIMAS, Department of Chemical Sciences, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
Sidi Mohamed Ben Abdellah University · MAKing Saud University · SALibyan International Medical University · LYUniversité Ibn Zohr · MAUniversity of Chieti-Pescara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The heterocycle compounds, with their diverse functionalities, are particularly effective in inhibiting Janus kinases (JAKs). Therefore, it is crucial to identify the correlation between their complex structures and biological activities for the development of new drugs for the treatment of rheumatoid arthritis (RA) and cancer. In this study, a diverse set of 28 heterocyclic compounds selective for JAK1 and JAK3 was employed to construct quantitative structure-activity relationship (QSAR) models using multiple linear regression (MLR). Artificial neural network (ANN) models were employed in the development of QSAR models. The robustness and stability of the models were assessed through internal and external methodologies, including the domain of applicability (DoA). The molecular descriptors incorporated into the model exhibited a satisfactory correlation with the receptor-ligand complex structures of JAKs observed in X-ray crystallography, making the model interpretable and predictive. Furthermore, pharmacophore models ADRRR and ADHRR were designed for each JAK1 and JAK3, proving effective in discriminating between active compounds and decoys. Both models demonstrated good performance in identifying new compounds, with an ROC of 0.83 for the ADRRR model and an ROC of 0.75 for the ADHRR model. Using a pharmacophore model, the most promising compounds were selected based on their strong affinity compared to the most active compounds in the studied series each JAK1 and JAK3. Notably, the pharmacokinetic, physicochemical properties, and biological activities of the selected compounds (As compounds ZINC79189223 and ZINC66252348) were found to be consistent with their therapeutic effects in RA, owing to their non-toxic, cholinergic nature, absence of P-glycoprotein, high gastrointestinal absorption, and ability to penetrate the blood-brain barrier. Furthermore, ADMET properties were assessed, and molecular dynamics and MM/GBSA analysis revealed stability in these molecules.

Indexed as

cancercytochrome P450FDA-drugimmune systeminterleukinJanus kinasesrheumatoid arthritis

Identifiers

PMID38516192
PMCPMC10956358
OpenAlexW4392552677

What OpenQuestion holds

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LicenceCC BY
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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.