Pharmacophore-Based 3D-QSAR and Molecular Docking Studies of Novel 1,3,4-Thiadiazole Derivatives as Potential α-Glucosidase Inhibitors

Abstract

Background: Metabolic Disorder Type 2 Diabetes mellitus (T2DM) is a chronic disease that involves hyperglycemia due to insulin resistance and impaired insulin secretion. α-glucosidase inhibition has been proven to be a therapeutic approach for controlling postprandial hyperglycemia and is a well-established treatment for T2DM. 1,3,4-thiadiazole is a promising pharmacophore among heterocyclic scaffolds due to its broad range of biological activities, including α-glucosidase inhibition.

Purpose: The present study was designed to identify and optimize novel 1,3,4-thiadiazole derivatives as α-glucosidase inhibitors using an integrated computer-aided drug design (CADD) approach that includes pharmacophore modeling, 3D-QSAR, molecular docking, optimization of R-groups, and ADMET prediction.

Methods: A total of 34 reported 1,3,4-thiadiazole derivatives were analyzed to build an optimal pharmacophore model (AADHR₃) as well as atom-based (R² = 0.799, Q² = 0.822) and Gaussian field-based 3D-QSAR models (R² = 0.967, Q² = 0.682). The structurally optimized lead compounds were then identified by molecular docking, R-group optimization, and ADMET prediction.

Results: The analysis of the contour map showed that bulky hydrophobic groups in the R₁ position and electron-withdrawing groups in the R₂ position were beneficial for enhancing α-glucosidase inhibitory activity. The docking score of five compounds was comparable or better than that of acarbose (−6.260 kcal/mol), with the best score being compound 25 (−6.686 kcal/mol). The designed derivatives (DM1 (−7.625 kcal/mol), DM2 (−7.418 kcal/mol), and DM3 (−7.284 kcal/mol)) showed better binding abilities and favorable interactions with Arg281, Asp282, Asp404,

Asp518, Asp616, His674, and Phe525, in addition to promising ADMET properties.

Conclusion: Pharmacophore analysis, 3D-QSAR, molecular docking, SAR, and ADMET studies indicated that the 1,3,4-thiadiazole scaffold could be a promising template for designing potent α-glucosidase inhibitors. The optimized derivatives, especially DM1–DM3, are good lead candidates for further development into therapeutic drugs for T2DM.

  • Page Number : 21-48
  • Published Date : 2026-08-17
  • Keywords
    α-Glucosidase inhibitors, 1,3,4-thiadiazole, Pharmacophore modelling, 3D-QSAR, Molecular docking
  • DOI Number
    10.15415/jptrm.2026.141002
  • Authors
    Debarshi Mondal, Priya Devi, Shalini Sharma and Harmel Singh Chahal

References

  • Acar Çevik, U., Celik, I., Işık, A., Ahmad, I., Patel, H., Özkay, Y., & Kaplancıklı, Z. A. (2023). Design, synthesis, molecular modeling, DFT, ADME and biological evaluation studies of some new 1, 3, 4-oxadiazole linked benzimidazoles as anticancer agents and aromatase inhibitors. Journal of Biomolecular Structure and Dynamics, 41(5), 1944–1958. https://doi.org/10.1080/07391102.2022.2025906
  • Akdağ, M., Çam, M. G., Ergen, D., Demir, Y., Beydemir, Ş., & Özçelik, A. B. (2025). Synthesis of new Pyridazinone derivatives and their dual inhibitory activity on aldose reductase and α-glucosidase. Bioorganic & Medicinal Chemistry Letters, 130498. https://doi.org/10.1016/j.bmcl.2025.130498
  • Asati, V., Bharti, S. K., & Budhwani, A. K. (2017). 3D-QSAR and virtual screening studies of thiazolidine-2, 4-dione analogs: Validation of experimental inhibitory potencies towards PIM-1 kinase. Journal of Molecular Structure, 1133, 278–293. https://doi.org/10.1016/j.molstruc.2016.12.006
  • Bischoff, H. B. A. G. (1994). Pharmacology of alpha-glucosidase inhibition. European Journal of Clinical Investigation, 24, 3–10. https://doi.org/10.1111/j.1365-2362.1994.tb02249.x
  • Bisht, P., Gautam, P., Bhattacharya, A., Singh, R., & Verma, S. K. (2025). Designing of xanthine-based DPP-4 inhibitors: A structure-guided alignment dependent Multifacet 3D-QSAR modeling, and molecular dynamics simulation study. Journal of Biomolecular Structure and Dynamics, 43(13), 6971–6995. https://doi.org/10.1080/07391102.2024.2329787
  • Chiba, S. (1997). Molecular mechanism in α-glucosidase and glucoamylase. Bioscience, Biotechnology, and Biochemistry, 61(8), 1233–1239. https://doi.org/10.1271/bbb.61.1233
  • Dawood, K. M., & Farghaly, T. A. (2017). Thiadiazole inhibitors: A patent review. Expert Opinion on Therapeutic Patents, 27(4), 477–505. https://doi.org/10.1080/13543776.2017.1272575
  • Gholami Rostami, E., & Fatemi, M. H. (2018). Comparative molecular field analysis and hologram quantitative structure activity relationship studies of pyrimidine series as potent phosphodiesterase 10A inhibitors. Journal of the Chinese Chemical Society, 65(11), 1293–1306. https://doi.org/10.1002/jccs.201700435
  • Gholami Rostami, E., & Fatemi, M. H. (2019). Molecular docking and receptor-based QASR studies on pyrimidine derivatives as potential phosphodiesterase 10A inhibitors. Structural Chemistry, 30(6), 2347–2368. https://doi.org/10.1007/s11224-019-01353-6
  • Gupta, S., Saha, M., Singh, R., Ahmed, S. B., & Asati, V. (2025). Multistage in silico approach to identify novel quinoline derivatives as potential c-kit kinase inhibitors. Journal of Biomolecular Structure and Dynamics, 43(11), 5313–5330. https://doi.org/10.1080/07391102.2024.2308759
  • Hanefeld, M., & Schaper, F. (2007). The role of alpha-glucosidase inhibitors (acarbose). In Pharmacotherapy of Diabetes: New Developments: Improving Life and Prognosis for Diabetic Patients (pp. 143–152). Springer US. https://doi.org/10.1007/978-0-387-69737-6_13
  • Haritha, M., Sreerag, M., & Suresh, C. H. (2024). Quantifying the hydrogen-bond propensity of drugs and its relationship with Lipinski's rule of five. New Journal of Chemistry, 48(11), 4896–4908. https://doi.org/10.1039/D3NJ05476D
  • Hosen, S. Z., Dash, R., Khatun, M., Akter, R., Bhuiyan, M. H. R., Karim, M. R., ... & Afrin, S. (2017). In silico ADME/T and 3D QSAR analysis of KDR inhibitors. Journal of Applied Pharmaceutical Science, 7(1), 120–128. https://doi.org/10.7324/JAPS.2017.70116
  • Hu, Y., Li, C. Y., Wang, X. M., Yang, Y. H., & Zhu, H. L. (2014). 1, 3, 4-Thiadiazole: Synthesis, reactions, and applications in medicinal, agricultural, and materials chemistry. Chemical Reviews, 114(10), 5572–5610. https://doi.org/10.1021/cr400131u
  • Inamdar, A., Pote, S., Sawant, S., Salve, P. S., Suryawanshi, S. S., & Palled, M. (2023). Physicochemical and pharmacokinetic properties’ screening of selected cardiovascular agents: An in-silico approach. https://doi.org/10.21203/rs.3.rs-2653667/v1
  • Jain, A. K., Sharma, S., Vaidya, A., Ravichandran, V., & Agrawal, R. K. (2013). 1, 3, 4‐Thiadiazole and its derivatives: A review on recent progress in biological activities. Chemical Biology & Drug Design, 81(5), 557–576. https://doi.org/10.1111/cbdd.12125
  • Kaya, B., Acar Çevik, U., Çiftçi, B., Duran, H. E., Türkeş, C., Işık, M., ... & Beydemir, S. (2024). Synthesis, α-glucosidase, α-amylase, and aldol reductase inhibitory activity with molecular docking study of novel imidazo [1, 2-a] pyridine derivatives. ACS Omega, 9(42), 42905–42914. https://doi.org/10.1021/acsomega.4c05619
  • Kaya, B., Acar Çevik, U., Necip, A., Duran, H. E., Çiftçi, B., Işık, M., ... & Beydemir, S. (2025). Design, synthesis, biological evaluation, and molecular docking studies of novel 1, 3, 4-Thiadiazole derivatives targeting both aldose reductase and α-Glucosidase for diabetes mellitus. ACS Omega, 10(18), 18812–18828. https://doi.org/10.1021/acsomega.5c00566
  • Matysiak, J. (2015). Biological and pharmacological activities of 1, 3, 4-thiadiazole based compounds. Mini Reviews in Medicinal Chemistry, 15(9), 762–775. https://doi.org/10.2174/1389557515666150519104057
  • Patel, P., Shah, D., Bambharoliya, T., Patel, V., Patel, M., Patel, D., ... & Patel, A. (2024). A review on the development of novel heterocycles as α-glucosidase inhibitors for the treatment of type-2 diabetes mellitus. Medicinal Chemistry, 20(5), 503–536. https://doi.org/10.2174/0115734064264591231031065639
  • Polya, G., & Read, R. C. (2012). Combinatorial enumeration of groups, graphs, and chemical compounds. Springer Science & Business Media. https://doi.org/10.1007/978-1-4612-4664-0
  • Sharma, R., Roy, S., & Kumar, A. (2025). Drug repurposing and virtual screening. In Advances in Pharmaceutical Product Development (pp. 399–421). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9230-6_16
  • Shen, X., Saburi, W., Gai, Z., Kato, K., Ojima-Kato, T., Yu, J., ... & Yao, M. (2015). Structural analysis of the α-glucosidase HaG provides new insights into substrate specificity and catalytic mechanism. Biological Crystallography, 71(6), 1382–1391. https://doi.org/10.1107/S139900471500721X
  • Shulgau, Z., Palamarchuk, I. V., Sergazy, S., Urazbayeva, A., Ramankulov, Y., & Kulakov, I. V. (2024). Synthesis, computational study, and in vitro α-Glucosidase inhibitory action of 1, 3, 4-Thiadiazole derivatives of 3-Aminopyridin-2 (1 H)-ones. Pharmaceuticals, 17(3), 377. https://doi.org/10.3390/ph17030377
  • Singh, Y., Jaswal, S., Singh, S., Verma, S. K., & Thareja, S. (2022). Dual aromatase-steroid sulfatase inhibitors (DASI’s) for the treatment of breast cancer: A structure guided ligand based designing approach. Journal of Biomolecular Structure & Dynamics, 41(20), 10604–10626. https://doi.org/10.1080/07391102.2022.2155702
  • Stitou, M., Toufik, H., Bouachrine, M., & Lamchouri, F. (2021). Quantitative structure–activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors. Journal of Biomolecular Structure and Dynamics, 39(1), 152–170. https://doi.org/10.1080/07391102.2019.1707122
  • Uddin, J., Ullah, S., Halim, S. A., Waqas, M., Ibrar, A., Khan, I., ... & Al-Harrasi, A. (2023). Triazolothiadiazoles and triazolothiadiazines as new and potent urease inhibitors: Insights from in vitro assay, kinetics data, and in silico assessment. ACS Omega, 8(35), 31890–31898. https://doi.org/10.1021/acsomega.3c03546
  • Van de Laar, F. A., Lucassen, P. L., Akkermans, R. P., Van de Lisdonk, E. H., Rutten, G. E., & Van Weel, C. (2005). α-Glucosidase inhibitors for patients with type 2 diabetes: Results from a Cochrane systematic review and meta-analysis. Diabetes Care, 28(1), 154–163. https://doi.org/10.2337/diacare.28.1.154
  • Vanajothi, R., Hemamalini, V., Jeyakanthan, J., & Premkumar, K. (2020). Ligand-based pharmacophore mapping and virtual screening for identification of potential discoidin domain receptor 1 inhibitors. Journal of Biomolecular Structure & Dynamics, 38(9), 2800–2808. https://doi.org/10.1080/07391102.2019.1640132
  • Veerasamy, R., Rajak, H., Jain, A., Sivadasan, S., Varghese, C. P., & Agrawal, R. K. (2011). Validation of QSAR models-strategies and importance. Int. J. Drug Des. Discov, 3, 511–519. https://doi.org/10.37285/ijddd.2.3.1
  • Verma, S. K., Kumar, N., & Thareja, S. (2021). Gaussian field-based comparative 3D QSAR modelling for the identification of favourable pharmacophoric features of chromene derivatives as selective inhibitors of ALR2 over ALR1. Structural Chemistry, 32(3), 1289–1298. https://doi.org/10.1007/s11224-020-01714-6
  • Vishwakarma, K., & Bhatt, H. (2021). Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques. Journal of Molecular Modeling, 27(2), 30. https://doi.org/10.1007/s00894-020-04648-2
  • Yadav, R., Imran, M., Dhamija, P., Chaurasia, D. K., & Handu, S. (2021). Virtual screening, ADMET prediction and dynamics simulation of potential compounds targeting the main protease of SARS-CoV-2. Journal of Biomolecular Structure and Dynamics, 39(17), 6617–6632. https://doi.org/10.1080/07391102.2020.1796812