Aug 2026· Molecular diversity· 0 citations· 41 references
Medicine
TL;DR
GSK3BMTPred, a multitask deep neural network model, was developed for simultaneous prediction of inhibitor classification and inhibitory potency and identified compounds showing stable interactions with key Adenosine Triphosphate (ATP) residues and favorable predicted absorption, distribution, metabolism, excretion, and toxicity properties.
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...
It is elucidated that HY-18,623 achieves high-affinity binding through persistent hydrogen bonds with hinge residues Val96 (CDK4) and Val101 (CDK6) and Val101 (CDK6) as a promising lead candidate for further therapeutic development in oncology.
Yu-Xin Wang, Lin-Xia Fang, Quan-Fang Liu et al.· Molecular diversity· 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 computational pipeline combining neural network-based potency prediction with molecular dynamics simulations for CDK8 inhibitor discovery was developed and novel molecular structures beyond the training distribution were generated.
B. Awad, M. Sargolzaei, H. Nikoofard· SAR and QSAR in environmenta...· 0 citations
This study provides a generalized DTA tool for early-stage drug development, and identifies S3 as a novel LSD1 inhibitor with potent anti-AD efficacy, by addressing unmet demands for AI-assisted anti-AD lead discovery.
Zhong-Hua Li, Tiancheng Sun, M. Han et al.· Bioorganic chemistry (Print)· 0 citations
An integrated computational workflow combining explainable machine learning, virtual screening, molecular dynamics simulations, and binding free-energy calculations to identify novel inhibitors of this drug-resistant EGFR variant may support the development of new therapeutic strategies for overcoming resistance in EGF...
Jurica Novak· International Journal of Mol...· 0 citations
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