Evidence map›Paper›PMID 41907306›Full record

ReviewPharmaceutical science advances2026

Next-generation Janus kinase inhibitors: Integrating synthetic innovation, structural biology, and computational design for precision drug discovery.

Karthik K Karunakar, Binoy Varghese Cheriyan, Sowmiya Philiph, Rajesh Kumar Shanmugam, Josme Sree

Abstract readReview
In one paragraph

Review in Pharmaceutical science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Karthik K KarunakarDepartment of Pharmacology, Saveetha College of Pharmacy, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.
Binoy Varghese CheriyanDepartment of Pharmaceutical Chemistry, Saveetha College of Pharmacy, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.
Sowmiya PhiliphDepartment of Pharmacology, Saveetha College of Pharmacy, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.
Rajesh Kumar ShanmugamNanobiomedicine Lab, Department of Anatomy, Saveetha Medical College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.
Josme SreeDepartment of Pharmacology, Saveetha College of Pharmacy, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Janus kinase (JAK) dysregulation plays a central role in the pathogenesis of inflammatory, autoimmune, and malignant disorders, making the JAK family an essential therapeutic target across multiple disease domains. Over the past two decades, the field has progressed from the identification of early JAK2 inhibitors to the approval of several first-generation agents, including ruxolitinib, tofacitinib, baricitinib, and fedratinib, which validated the clinical feasibility of JAK blockade. However, limitations related to safety, isoform selectivity, long-term tolerability, and off-target kinase interactions continue to restrict their broader application and highlight the need for next-generation molecules. In this review, we provide a comprehensive and strategic assessment of the molecular features underpinning JAK2 and JAK3 selectivity, including signaling features directly relevant to inhibitor design, mutational landscapes, and structural determinants such as the uniquely targetable Cys909 residue in JAK3. Although the JAK family comprises four kinases, this review intentionally focuses on JAK2 and JAK3, where structural divergence, disease relevance, and emerging selectivity strategies provide the strongest opportunities for next-generation precision inhibitor design. We integrate recent advances in synthetic chemistry, including hinge-binding optimization, heterocyclic diversification, multicomponent reactions, and scaffold-hopping strategies, with computational methodologies such as molecular docking, molecular dynamics simulations, QM/MM calculations, and machine-learning-based predictive modelling. Together, these multidisciplinary approaches have accelerated hit discovery, refined selectivity, and improved the pharmacokinetic and safety profiles of emerging JAK inhibitors. By consolidating progress across medicinal chemistry, structural biology, and computational design, this review outlines key opportunities and remaining challenges in developing next-generation JAK inhibitors with enhanced precision and therapeutic value for oncology, immunology, and chronic inflammatory diseases.

Indexed as

Computational medicinal chemistryJAK2/JAK3 selectivityJanus kinase inhibitorsSignal transducer and activator of transcription (STAT) pathwayStructure-based drug design

Identifiers

PMID41907306
PMCPMC13019105

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.