Computational modelling of Tunicamycin C interaction with potential protein targets : perspectives from inverse docking with molecular dynamic simulation

Abstract

Protein glycosylation plays a crucial role in cancer biology, influencing essential cellular processes such as cell signalling, immune recognition, and tumour metastasis. Therefore, this study highlights the therapeutic potential of targeting glycosylation in cancer treatment, as modulating these modifications could disrupt the fundamental mechanisms driving cancer progression and improve therapeutic outcomes. Recently, Tunicamycin C, a well-known glycosylation inhibitor, has shown promise in breast cancer treatment but remains unexplored in colorectal cancer (CRC). Thus, in this study, we aimed to understand the potential action of Tunicamycin C in CRC using in silico studies to identify possible drug targets for Tunicamycin C. First, we identified two target proteins using the HTDocking algorithm followed by GO and KEGG pathway searches: thymidine kinase 1 (TK1) and cAMP-dependent protein kinase catalytic subunit alpha (PKAc). Following this, molecular dynamics modelling revealed that Tunicamycin C binding induced a conformational perturbation in the 3D structures of TK1 and PKAc, inhibiting their activities. This interaction led to a stable design, promoting optimal binding of Tunicamycin C in the hydrophobic pockets of TK1 and PKAc. Serial validation studies highlighted the role of active site residues in binding stabilisation. Tunicamycin C exhibited high binding affinity with TK1 and PKAc. This study provides a way to explore and repurpose novel inhibitors of TK1 and PKAc and identify new therapeutic targets, which may block glycosylation in cancer treatment.