20.500.12556/RUL-160545 Simulation- and AI-directed optimization of 4,6-substituted 1,3,5-triazin-2(1H)-ones as inhibitors of human DNA topoisomerase IIα The 4,6-substituted-1,3,5-triazin-2(1H)-ones are promising inhibitors of human DNA topoisomerase IIα. To further develop this chemical class targeting the enzymes ATP binding site, the triazin-2(1H)-one substitution position 6 was optimized. Inspired by binding of preclinical substituted 9H-purine derivative, bicyclic substituents were incorporated at position 6 and the utility of this modification was validated by a combination of molecular simulations, dynamic pharmacophores, and free energy calculations. Considering also predictions of Deepfrag, a software developed for structure-based lead optimization based on deep learning, compounds with both bicyclic and monocyclic substitutions were synthesized and investigated for their inhibitory activity. The SAR data showed that the bicyclic substituted compounds exhibited good inhibition of topo IIα, comparable to their mono-substituted counterparts. Further evaluation on a panel of human protein kinases showed selectivity for the inhibition of topo IIα. Mechanistic studies indicated that the compounds acted predominantly as catalytic inhibitors, with some exhibiting topo IIα poison effects at higher concentrations. Integration of STD NMR experiments and molecular simulations, provided insights into the binding model and highlighted the importance of the Asn120 interaction and hydrophobic interactions with substituents at positions 4 and 6. In addition, NCI-60 screening demonstrated cytotoxicity of the compounds with bicyclic substituents and identified sensitive human cancer cell lines, underlining the translational relevance of our findings for further preclinical development of this class of compounds. The study highlights the synergy between simulation and AI-based approaches in efficiently guiding molecular design for drug optimization, which has implications for further preclinical development of this class of compounds. molecular design molecular simulations deep learning human DNA topoisomerase IIα catalytic inhibitors anticancer agents molekularna zasnova molekularne simulacije globoko učenje človeška DNA topoizomeraza IIα katalitični inhibitorji sredstva proti raku rak medicina farmacevtska kemija true false true Angleški jezik Slovenski jezik Članek v reviji 2024-08-30 11:03:50 2024-08-30 11:03:59 2025-01-31 10:53:17 0000-00-00 00:00:00 2024 0 0 Str. 2995-3018 Vol. 23 Dec. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 615.4:54:616-006 2001-0370 10.1016/j.csbj.2024.06.037 200950531 1-s2.0-S2001037024002344-main.pdf 1-s2.0-S2001037024002344-main.pdf 1 C7B05950999F6F152304245830C749CD f809d28e7924d61623f7f90c42a134a4a5ddae1264a604ed3b30feaf3c40bdd2 ff0d3a3f-66af-11ef-8f74-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=189274 https://www.sciencedirect.com/science/article/pii/S2001037024002344 1 8f6f4381-66ae-11ef-8f74-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=189273 Fakulteta za farmacijo 0 0 0