From in silico and machine learning model to validation: discovery of novel amide-functionalized imidazopyridines as PIM-1 kinase inhibitors using an integrated ligand and structure-based hopping approach

RSC Advances 2026 Open access

Read full text
Authors: Vinayak S. Walhekar, Shubham Dhadil, Ankit Ganeshpurkar, Srilakshmi SINGAGARI, Ayesha Begum Khadernaick, Amol Muthal, Vaibhav Shinde, Ashwin Mali, Raghavendra S Kulkarni, Raghavendra S Kulkarni, Ravindra Kulkarni, Ravindra Kulkarni
DOI: 10.1039/d6ra00514d
Cited by: 1
References: 43

Abstract

ADME and drug-likeness profiles, including high predicted absorption and absence of hepatotoxicity. These findings establish 6h as a promising lead scaffold for the development of PIM1-1 targeted anticancer agents. The integration of pharmacophore modeling, machine learning prediction, and experimental validation highlights a viable strategy for accelerating kinase inhibitor discovery.

Fields of Study & Subjects

Cancer Mechanisms and Therapy Synthesis and biological activity FOXO transcription factor regulation

Publication details

Journal / source
RSC Advances
Publisher
Royal Society of Chemistry (RSC)
Volume
16
Issue
22
Pages
20224–20240
Publication date
1 January 2026
Language
EN