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In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs

Year 2026, Volume: 10 Issue: 3, 60 - 70

Abstract

Triosephosphate isomerase (TPI1) has been suggested as a candidate oncogene, with multiple cancer types showing overexpression of it, such asintrahepatic cholangiocarcinoma (ICC), gastric ,lung, and prostate cancer.Serum biomarker TPI1 has been identified in cancer patients, including BC patients. Because molecular docking approaches may predict the experimental binding mechanism, affinity, and position of a small molecule (ligand) within the binding site of the target receptor (macromolecule), they are crucial in the design and development of innovative drugs. In our current study, molecular docking ,molecular dynamic simulation were applied for thirty nine of flavonoids compounds were selected to be used as inhibitors of TPI1 enzyme in order to obtain the lead compound and use it experimentally to inhibit the enzyme. These substances were selected in order to assess their binding effectiveness and reactivity with the TPI1 enzyme (PDB ID: 2jk2).The simulation results obtained from the molecular docking and molecular dynamics showed that vitexin compound could bind with the TPI1 enzyme better than the others.

References

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  • [3] T. Chen, Z. Huang, Y. Tian, B. Lin, R. He, H. Wang, P. Ouyang, H. Chen, et al.,Clinical significance and prognostic value of Triosephosphate isomerase expression in gastric cancer, J Med.96 (2017) e6865.
  • [4] M. A. Ansari-Lari, D. M. Muzny, J. Lu, F. Lu, C. E. Lilley, S. Spanos, T. Malley , et al., A gene-rich cluster between the CD4 and triosephosphate isomerase genes at human chromosome 12p13,Genome Res. 6 (1996) 314–326.
  • [5] L. E. Maquat, R. Chilcote , P. M. Ryan, Human triosephosphate isomerase cDNA and protein structure. Studies of triosephosphate isomerase deficiency in man,JBC. 260 (1985) 3748–3753.
  • [6] W.-L. Yu, G. Yu, H. Dong, K. Chen, J. Xie, H. Yu, Y. Ji, G.-S. Yang, A.-J. Li, W.-M. Cong, et al., Proteomics analysis identified TPI1 as a novel biomarker for predicting recurrence of intrahepatic cholangiocarcinoma, J.Gastroenterol. 55 (2020) 1171–1182.
  • [7] F. Yang, Z.-Q. Xiao, X.-Z. Zhang, C. Li, P.-F. Zhang, M.-Y. Li, Y. Chen, G.-Q. Zhu, Y. Sun, Y.-F. Liu, et al., Identification of tumor antigens in human lung squamous carcinoma by serological proteome analysis, J Proteome Res.6(2) (2006) 751–758.
  • [8] X. Zhang, Z. Xiao, C. Li, Z. Xiao, F. Yang, D. Li, M. Li, F. Li , Z. Chen, Triosephosphate isomerase and peroxiredoxin 6, two novel serum markers for human lung squamous cell carcinoma, Cancer Sci.100 (2009) 2396–2401.
  • [9] W.Z.Chen, et al., Differential proteome analysis of conditioned medium of BPH-1 and LNCaP cells, Chin Med J .124(22) (2011) 3806-3809.
  • [10] M.S. Tamesa, Y. Kuramitsu, M. Fujimoto, N. Maeda, Y. Nagashima, T. Tanaka, S. Yamamoto, M. Oka, et al.,, Detection of autoantibodies against cyclophilin A and triosephosphate isomerase in sera from breast cancer patients by proteomic analysis, Electrophor. 30 (2009) 2168–2181,
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  • [12] L. Li, S.-H. Chen, C.-H. Yu, Y.-M. Li and S.-Q. Wang, Identification of Hepatocellular-Carcinoma-Associated Antigens, et al., Autoantibodies by Serological Proteome Analysis Combined with Protein Microarray, J Proteome Res. (2007) 611–620.
  • [13] Z. Liu, Y. Liu, G. Zeng, B. Shao, M. Chen, Z. Li, Y. Jiang, Y. Liu, Y. Zhang , et al., Application of molecular docking for the degradation of organic pollutants in the environmental remediation: A review, Chemosphere, 203 (2018) 139–150.
  • [14] T. Tuccinardi, G. Poli, V. Romboli, A. Giordano , et al., Extensive consensus docking evaluation for ligand pose prediction and virtual screening studies, JCIM. 54 (2014) 2980–2986
  • [15] A.M.Dar, S.Mir , Molecular docking: approaches, types, applications and basic challenges, J Anal Bioanal Tech .8(2) (2017) 1-3.
  • [16] C. Rodríguez-Almazán, R. Arreola, D. Rodríguez-Larrea, B. Aguirre-López, M. T. De Gómez-Puyou, R. Pérez-Montfort, M. Costas, A. Gómez-Puyou , et al., Structural basis of human triosephosphate isomerase deficiency, JBC. 283 (2008) 23254–23263.
  • [17] A. M. K. Al-Azzawi , E. A. Hassan, Exploring Benzo[d]thiazol-2-Amine Derivatives, Synthesis, and Molecular Docking Insights Potential Anticancer Agents Targeting HER Enzyme and DNA, Appl Biochem Biotechnol. (2025) 1-14.
  • [18] O. A. Jwameer, E. A. Hassan, F. M. Al-Abady, Triose phosphate isomerase 1 in serum of women with breast cancer, Revista De Senología Y Patología Mamaria. 38 (2024) 100647.
  • [19] R.Huey, G. M. Morris, S. Forli ,Using AutoDock 4 and AutoDock vina with AutoDockTools: a tutorial,The Scripps Research Institute (MGL) .10550 (92037) (2012) 1000.
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  • [21] N. Guex , M. C. Peitsch, SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modeling, Electrophor .18 (1997) 2714–2723.
  • [22] C. Rodríguez-Almazán, R. Arreola, D. Rodríguez-Larrea, B. Aguirre-López, M. T. De Gómez-Puyou, R. Pérez-Montfort, M. Costas, A. Gómez-Puyou , et al., Structural basis of human triosephosphate isomerase deficiency, JBC . 283 (2008) 23254–23263.
  • [23] S. Yuan, H. C. S. Chan , Z. Hu, Using PyMOL as a platform for computational drug design, Wiley Interdiscip. Rev. Comput. Mol. Sci. 7(2) (2017) e1298.
  • [24] S. Ullah, Z. Zheng, W. Rahman, F. Ullah, A. Ullah, M. N. Iqbal, N. Iqbal , T. Gao, A computational approach to fighting type 1 diabetes by targeting 2C Coxsackie B virus protein with flavonoids, PLoS ONE, 18 (2023) e0290576.
  • [25] J.K.Bowers, J.Kevin., et al, Scalable algorithms for molecular dynamics simulations on commodity clusters. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. (2006) 84-es.
  • [26] K. A. Oluwafemi, R. B. Jimoh, D. A. Omoboyowa, A. Olonisakin, A. F. Adeforiti ,N. Iqbal, Investigating the effect of 1,2-Dibenzoylhydrazine on Staphylococcus aureus using integrated computational approaches, In Silico Pharmacol. 12(2) (2024) 1-15.
  • [27] O. Trott , A. J. Olson, AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading, J Comput Chem. 31 (2009) 455–461.
  • [28] Z. Basharat, S. Zaib and A. Yasmin, Computational study of some amoebicidal phytochemicals against heat shock protein of Naegleria fowleri, Gene Rep. 6 (2016) 158–162.
  • [29] P. A. Madero-Ayala, R. E. Mares-Alejandre , M. A. Ramos-Ibarra, In Silico Structural Analysis of Serine Carboxypeptidase Nf314, a Potential Drug Target in Naegleria fowleri Infections, Int J Mol Sci . 23(2022) 12203.
  • [30] P. W. Hildebrand, A. S. Rose , J. K. S. Tiemann, Bringing Molecular Dynamics Simulation Data into View, Trends Biochem. Sci, 44 (2019) 902–913.
  • [31] J. D. Romano , N. P. Tatonetti, Informatics and Computational Methods in Natural Product Drug Discovery: A review and Perspectives, Frontiers in Genetics. 10 (2019) 368.

Year 2026, Volume: 10 Issue: 3, 60 - 70

Abstract

References

  • [1] S. Enríquez-Flores, L. A. Flores-López, I. García-Torres, I. De La Mora, N.Cabrera, P. Gutiérrez-Castrellón, Y. Martínez-Pérez, et al.,Deamidated Human Triosephosphate Isomerase is a Promising Druggable Target,Biomol.10 (2020) 1050.
  • [2] G. Pekel , F. Ari, Therapeutic Targeting of Cancer Metabolism with Triosephosphate Isomerase,Chem Biodiversity.17(5) (2020): e2000012.
  • [3] T. Chen, Z. Huang, Y. Tian, B. Lin, R. He, H. Wang, P. Ouyang, H. Chen, et al.,Clinical significance and prognostic value of Triosephosphate isomerase expression in gastric cancer, J Med.96 (2017) e6865.
  • [4] M. A. Ansari-Lari, D. M. Muzny, J. Lu, F. Lu, C. E. Lilley, S. Spanos, T. Malley , et al., A gene-rich cluster between the CD4 and triosephosphate isomerase genes at human chromosome 12p13,Genome Res. 6 (1996) 314–326.
  • [5] L. E. Maquat, R. Chilcote , P. M. Ryan, Human triosephosphate isomerase cDNA and protein structure. Studies of triosephosphate isomerase deficiency in man,JBC. 260 (1985) 3748–3753.
  • [6] W.-L. Yu, G. Yu, H. Dong, K. Chen, J. Xie, H. Yu, Y. Ji, G.-S. Yang, A.-J. Li, W.-M. Cong, et al., Proteomics analysis identified TPI1 as a novel biomarker for predicting recurrence of intrahepatic cholangiocarcinoma, J.Gastroenterol. 55 (2020) 1171–1182.
  • [7] F. Yang, Z.-Q. Xiao, X.-Z. Zhang, C. Li, P.-F. Zhang, M.-Y. Li, Y. Chen, G.-Q. Zhu, Y. Sun, Y.-F. Liu, et al., Identification of tumor antigens in human lung squamous carcinoma by serological proteome analysis, J Proteome Res.6(2) (2006) 751–758.
  • [8] X. Zhang, Z. Xiao, C. Li, Z. Xiao, F. Yang, D. Li, M. Li, F. Li , Z. Chen, Triosephosphate isomerase and peroxiredoxin 6, two novel serum markers for human lung squamous cell carcinoma, Cancer Sci.100 (2009) 2396–2401.
  • [9] W.Z.Chen, et al., Differential proteome analysis of conditioned medium of BPH-1 and LNCaP cells, Chin Med J .124(22) (2011) 3806-3809.
  • [10] M.S. Tamesa, Y. Kuramitsu, M. Fujimoto, N. Maeda, Y. Nagashima, T. Tanaka, S. Yamamoto, M. Oka, et al.,, Detection of autoantibodies against cyclophilin A and triosephosphate isomerase in sera from breast cancer patients by proteomic analysis, Electrophor. 30 (2009) 2168–2181,
  • [11] C. Desmetz, F. Boissière, F. Bibeau, V. Bellet, P. Rouanet, T. Maudelonde, A.Mangé , et al., Proteomics-Based Identification of HSP60 as a Tumor-Associated Antigen in Early Stage Breast Cancer and Ductal Carcinoma in situ, J Proteome Res.7 (2008) 3830–3837.
  • [12] L. Li, S.-H. Chen, C.-H. Yu, Y.-M. Li and S.-Q. Wang, Identification of Hepatocellular-Carcinoma-Associated Antigens, et al., Autoantibodies by Serological Proteome Analysis Combined with Protein Microarray, J Proteome Res. (2007) 611–620.
  • [13] Z. Liu, Y. Liu, G. Zeng, B. Shao, M. Chen, Z. Li, Y. Jiang, Y. Liu, Y. Zhang , et al., Application of molecular docking for the degradation of organic pollutants in the environmental remediation: A review, Chemosphere, 203 (2018) 139–150.
  • [14] T. Tuccinardi, G. Poli, V. Romboli, A. Giordano , et al., Extensive consensus docking evaluation for ligand pose prediction and virtual screening studies, JCIM. 54 (2014) 2980–2986
  • [15] A.M.Dar, S.Mir , Molecular docking: approaches, types, applications and basic challenges, J Anal Bioanal Tech .8(2) (2017) 1-3.
  • [16] C. Rodríguez-Almazán, R. Arreola, D. Rodríguez-Larrea, B. Aguirre-López, M. T. De Gómez-Puyou, R. Pérez-Montfort, M. Costas, A. Gómez-Puyou , et al., Structural basis of human triosephosphate isomerase deficiency, JBC. 283 (2008) 23254–23263.
  • [17] A. M. K. Al-Azzawi , E. A. Hassan, Exploring Benzo[d]thiazol-2-Amine Derivatives, Synthesis, and Molecular Docking Insights Potential Anticancer Agents Targeting HER Enzyme and DNA, Appl Biochem Biotechnol. (2025) 1-14.
  • [18] O. A. Jwameer, E. A. Hassan, F. M. Al-Abady, Triose phosphate isomerase 1 in serum of women with breast cancer, Revista De Senología Y Patología Mamaria. 38 (2024) 100647.
  • [19] R.Huey, G. M. Morris, S. Forli ,Using AutoDock 4 and AutoDock vina with AutoDockTools: a tutorial,The Scripps Research Institute (MGL) .10550 (92037) (2012) 1000.
  • [20] P.D.Bank, Protein data bank. Nat New Biol, 233(223) (1971) 10-1038.
  • [21] N. Guex , M. C. Peitsch, SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modeling, Electrophor .18 (1997) 2714–2723.
  • [22] C. Rodríguez-Almazán, R. Arreola, D. Rodríguez-Larrea, B. Aguirre-López, M. T. De Gómez-Puyou, R. Pérez-Montfort, M. Costas, A. Gómez-Puyou , et al., Structural basis of human triosephosphate isomerase deficiency, JBC . 283 (2008) 23254–23263.
  • [23] S. Yuan, H. C. S. Chan , Z. Hu, Using PyMOL as a platform for computational drug design, Wiley Interdiscip. Rev. Comput. Mol. Sci. 7(2) (2017) e1298.
  • [24] S. Ullah, Z. Zheng, W. Rahman, F. Ullah, A. Ullah, M. N. Iqbal, N. Iqbal , T. Gao, A computational approach to fighting type 1 diabetes by targeting 2C Coxsackie B virus protein with flavonoids, PLoS ONE, 18 (2023) e0290576.
  • [25] J.K.Bowers, J.Kevin., et al, Scalable algorithms for molecular dynamics simulations on commodity clusters. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. (2006) 84-es.
  • [26] K. A. Oluwafemi, R. B. Jimoh, D. A. Omoboyowa, A. Olonisakin, A. F. Adeforiti ,N. Iqbal, Investigating the effect of 1,2-Dibenzoylhydrazine on Staphylococcus aureus using integrated computational approaches, In Silico Pharmacol. 12(2) (2024) 1-15.
  • [27] O. Trott , A. J. Olson, AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading, J Comput Chem. 31 (2009) 455–461.
  • [28] Z. Basharat, S. Zaib and A. Yasmin, Computational study of some amoebicidal phytochemicals against heat shock protein of Naegleria fowleri, Gene Rep. 6 (2016) 158–162.
  • [29] P. A. Madero-Ayala, R. E. Mares-Alejandre , M. A. Ramos-Ibarra, In Silico Structural Analysis of Serine Carboxypeptidase Nf314, a Potential Drug Target in Naegleria fowleri Infections, Int J Mol Sci . 23(2022) 12203.
  • [30] P. W. Hildebrand, A. S. Rose , J. K. S. Tiemann, Bringing Molecular Dynamics Simulation Data into View, Trends Biochem. Sci, 44 (2019) 902–913.
  • [31] J. D. Romano , N. P. Tatonetti, Informatics and Computational Methods in Natural Product Drug Discovery: A review and Perspectives, Frontiers in Genetics. 10 (2019) 368.
There are 31 citations in total.

Details

Primary Language English
Subjects Molecular Imaging
Journal Section Research Article
Authors

Obaida Adnan Jwameer 0009-0003-7511-8046

Ekhlas Hassan 0000-0002-0410-0178

Faiz Al-abady 0000-0001-8859-6934

Early Pub Date October 27, 2025
Publication Date December 3, 2025
Submission Date February 28, 2025
Acceptance Date May 4, 2025
Published in Issue Year 2026 Volume: 10 Issue: 3

Cite

APA Jwameer, O. A., Hassan, E., & Al-abady, F. (2025). In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs. Turkish Computational and Theoretical Chemistry, 10(3), 60-70.
AMA Jwameer OA, Hassan E, Al-abady F. In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs. Turkish Comp Theo Chem (TC&TC). October 2025;10(3):60-70.
Chicago Jwameer, Obaida Adnan, Ekhlas Hassan, and Faiz Al-abady. “In Silico Study of Inhibition Triose Phosphate Isomerase 1 Using Flavonoids As Apossible Drugs”. Turkish Computational and Theoretical Chemistry 10, no. 3 (October 2025): 60-70.
EndNote Jwameer OA, Hassan E, Al-abady F (October 1, 2025) In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs. Turkish Computational and Theoretical Chemistry 10 3 60–70.
IEEE O. A. Jwameer, E. Hassan, and F. Al-abady, “In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs”, Turkish Comp Theo Chem (TC&TC), vol. 10, no. 3, pp. 60–70, 2025.
ISNAD Jwameer, Obaida Adnan et al. “In Silico Study of Inhibition Triose Phosphate Isomerase 1 Using Flavonoids As Apossible Drugs”. Turkish Computational and Theoretical Chemistry 10/3 (October2025), 60-70.
JAMA Jwameer OA, Hassan E, Al-abady F. In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs. Turkish Comp Theo Chem (TC&TC). 2025;10:60–70.
MLA Jwameer, Obaida Adnan et al. “In Silico Study of Inhibition Triose Phosphate Isomerase 1 Using Flavonoids As Apossible Drugs”. Turkish Computational and Theoretical Chemistry, vol. 10, no. 3, 2025, pp. 60-70.
Vancouver Jwameer OA, Hassan E, Al-abady F. In silico study of Inhibition Triose Phosphate Isomerase 1 using flavonoids as apossible drugs. Turkish Comp Theo Chem (TC&TC). 2025;10(3):60-7.

Journal Full Title: Turkish Computational and Theoretical Chemistry


Journal Abbreviated Title: Turkish Comp Theo Chem (TC&TC)