Molecular Docking, Machine Learning-Guided Design, Synthesis, and Biological Evaluation of Novel Multitarget HDAC/ROCK Inhibitors

Histone deacetylases (HDACs) and Rho-associated coiled-coil containing protein kinases (ROCKs) are critical regulators of tumor development, progression and immunomodulation, particularly in aggressive cancers such as triple negative breast cancer (TNBC). Previous in silico and in vitro studies have demonstrated the therapeutic potential of multitarget HDAC/ROCK inhibition, leading to the identification of C-9 as the first-in-class multitarget HDAC/ROCK inhibitor. In the present study, C-9 served as a lead compound for the rational design of a new series of multitarget inhibitors. Structure-based drug design (SBDD) was used to develop a series of novel HDAC/ROCK multitarget inhibitors. Molecular docking and MM-GBSA binding free energy analysis confirmed strong and specific interactions with the catalytic sites of both targets. Based on these computational insights, ten compounds were synthesized and biologically evaluated using enzyme inhibition and cancer cell assays. Among the synthesized compounds, C-35 and C-40 showed remarkable cytotoxic activity against TNBC cell lines, with IC50 values of 17 µM and 27 µM against MDA-MB-231 cells and about 35 µM against MDA-MB-468 cells, respectively, outperforming known selective HDAC6 and ROCK inhibitors such as tubastatin A and fasudil. Further mechanistic studies revealed that these compounds induce early apoptosis, arrest cell cycle progression and downregulate PD-L1 expression. Remarkably, C-35 also increased the expression of MICA in MDA-MB-231 and MDA-MB-468 cells, possibly promoting the recognition and elimination of tumor cells by immune cells. To further support rational drug optimization, we used synthesized compounds and their IC50 values for the enzymes to form an external blind validation set that enabled the development of machine learning-based quantitative structure-activity relationships (QSAR) models for HDAC6 and ROCK2. These models, developed for the first time for both targets, showed strong predictive performance and were integrated into a comprehensive CADD workflow combining structure-based (molecular docking and MM-GBSA) and ligand-based (QSAR) methods for drug development. Overall, this study highlights the anti-cancer, anti-invasive, anti-migratory and immunomodulatory potential of multitarget HDAC/ROCK inhibition for the treatment of TNBC. Finally, it creates a robust computational-experimental pipeline for future development and optimization of multitarget HDAC/ROCK inhibitors.