Aug 2026· Journal of Pharmaceutical Innovation· Vol 22· 0 citations· 81 references
TL;DR
These findings introduce H_1 as a computationally prioritized, putative MLK4-binding lead and provide a hypothesis-generating framework for MLK4-targeted scaffold prioritization, while recognizing that experimental activity and kinome selectivity profiling remain necessary before H_1 can be described as a confirmed MLK4 inhibitor or MLK4-selective compound.
The proposed workflow efficiently reduced a large chemical space to a focused set of TNKS1 inhibitor candidates while substantially reducing the experimental screening burden, highlighting the value of integrating consensus ML, SBVS, and experimental validation to accelerate early-stage hit discovery for TNKS1 and othe...
M. Bilotta, Adriana Gargano, R. Rocca et al.· Pharmaceuticals· 0 citations
An integrated computational framework combining machine learning (ML), deep learning (DL), and structure-based docking with experimental validation identifies AO65 as a promising lead for further TDP1-focused investigation.
Huang Zeng, Man-Yi Zhang, Bo Qiu et al.· RSC Advances· 0 citations
This work demonstrates that integrating docking-derived pharmacophores with conformational ensemble-based machine learning provides an effective approach for discovering novel inhibitors against underexplored kinase targets.
G. Shakhatreh, M. Taha, S. Daoud· RSC Advances· 0 citations
How explainable ML can be used in combination with structure-based docking to expedite the drug discovery process against FYN kinase is highlighted and can be applied to other kinase targets.
Ahmet Turan Demir· Intelligent Systems Research...· 4 citations
An integrated computer-aided drug design (CADD) and artificial intelligence (AI) framework to systematically identify selective ALDH1A1 inhibitors from a heterocyclic compound library is developed and suggests that LDN-27219 exhibits favorable binding characteristics and represents a promising lead candidate for subseq...
A scalable, machine-learning-integrated virtual screening framework designed to explore ultra-large chemical space spanning an input search space of approximately 884 million compounds from ZINC20 and 199,854 purchasable compounds from the SPECS database is reported.
R. Muthuraj, Manasa Pacharla, Nehal Arvind Kumar et al.· Journal of Computer-Aided Mo...· 0 citations
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