Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation
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 mo...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Current Issues in Molecular Biology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1467-3045/47/5/339 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849327468666683392 |
|---|---|
| author | Vivash Naidoo Ikechukwu Achilonu Sheefa Mirza Rodney Hull Jeyalakshmi Kandhavelu Marushka Soobben Clement Penny |
| author_facet | Vivash Naidoo Ikechukwu Achilonu Sheefa Mirza Rodney Hull Jeyalakshmi Kandhavelu Marushka Soobben Clement Penny |
| author_sort | Vivash Naidoo |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1adaea5b0ab54fa8a8dd4a059f6238a5 |
| institution | Kabale University |
| issn | 1467-3037 1467-3045 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Current Issues in Molecular Biology |
| spelling | doaj-art-1adaea5b0ab54fa8a8dd4a059f6238a52025-08-20T03:47:52ZengMDPI AGCurrent Issues in Molecular Biology1467-30371467-30452025-05-0147533910.3390/cimb47050339Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic SimulationVivash Naidoo0Ikechukwu Achilonu1Sheefa Mirza2Rodney Hull3Jeyalakshmi Kandhavelu4Marushka Soobben5Clement Penny6Department of Internal Medicine, Medicine, Wits/MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South AfricaProtein Structure-Function Research Unit, School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Johannesburg 2050, South AfricaDepartment of Internal Medicine, Medicine, Wits/MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South AfricaSAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, Hatfield, Pretoria 0028, South AfricaDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown, University Medical Center, Washington, DC 20007, USAProtein Structure-Function Research Unit, School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Johannesburg 2050, South AfricaDepartment of Internal Medicine, Medicine, Wits/MRC Common Epithelial Cancer Research Centre, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2050, South AfricaProtein 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.https://www.mdpi.com/1467-3045/47/5/339glycosylationTunicamycinthymidine kinase 1protein kinase Amolecular dynamicstherapeutic targets |
| spellingShingle | Vivash Naidoo Ikechukwu Achilonu Sheefa Mirza Rodney Hull Jeyalakshmi Kandhavelu Marushka Soobben Clement Penny Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation Current Issues in Molecular Biology glycosylation Tunicamycin thymidine kinase 1 protein kinase A molecular dynamics therapeutic targets |
| title | Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation |
| title_full | Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation |
| title_fullStr | Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation |
| title_full_unstemmed | Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation |
| title_short | Computational Modelling of Tunicamycin C Interaction with Potential Protein Targets: Perspectives from Inverse Docking with Molecular Dynamic Simulation |
| title_sort | computational modelling of tunicamycin c interaction with potential protein targets perspectives from inverse docking with molecular dynamic simulation |
| topic | glycosylation Tunicamycin thymidine kinase 1 protein kinase A molecular dynamics therapeutic targets |
| url | https://www.mdpi.com/1467-3045/47/5/339 |
| work_keys_str_mv | AT vivashnaidoo computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT ikechukwuachilonu computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT sheefamirza computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT rodneyhull computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT jeyalakshmikandhavelu computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT marushkasoobben computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation AT clementpenny computationalmodellingoftunicamycincinteractionwithpotentialproteintargetsperspectivesfrominversedockingwithmoleculardynamicsimulation |