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
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 MLK...
Afnan A. Alzaghari, S. Daoud, Husam Nassar et al.· Journal of Pharmaceutical In...· 0 citations
The computationally prioritized candidates can be subjected to further experimental testing, as the conducted docking, MD simulations, and end-point free energy analyses cannot establish overall compound binding, cell-based activity, pharmacological mechanism, or therapeutic efficacy.
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
Histone deacetylase 8 (HDAC8) is an emerging epigenetic target implicated in cancer, neurodegenerative disorders, and other human diseases, driving the urgent need for potent and selective inhibitors. In this study, we developed and validated a deep learning-based computational pipeline for the accurate prediction of H...
M. Sargolzaei, H. Nikoofard· Journal of Molecular Graphic...· 0 citations
The natural product compounds CNP0456830 and CNP0467494 exhibited the lowest binding free energies for both EGFR and PIK3CA, identifying them as the most promising dual-target inhibitors.
Si-miao Lu, Yi Zhu, Yong-Tao Han et al.· Diseases of the esophagus· 0 citations
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