Computational Identification of Azole Derivatives Targeting the mTOR Rapamycin Binding Domain for Therapeutic Development
Keywords:
Autophagy, Ligand, Receptor, mTOR, Binding energy.
Abstract
This study investigates the potential of eight azole-derived compounds (KR1–KR8) as inhibitors of the mammalian target of rapamycin (mTOR), a critical protein involved in regulating autophagy and associated with diseases such as cancer, obesity, and aging. Using in silico molecular docking, we evaluated the interaction of these compounds with the rapamycin binding (FRB) domain of mTOR. Drug-likeness assessments revealed that all compounds adhered to Lipinski’s rule, indicating favorable oral bioavailability, with optimal values for molecular weight, LogP, and total polar surface area (TPSA). In addition, the compounds demonstrated low toxicity profiles and high absorption potential, with minimal interactions with cytochrome P450 enzymes, suggesting a favorable pharmacokinetic profile. Among the tested compounds, KR4 showed the most promising results, exhibiting a strong binding affinity to mTOR with a docking score of -7.61 kcal/mol. KR4 specifically interacted with key residues of the FRB domain (LEU-2031, SER-2035, PHE-2039, TRP-2101, TYR-2105, and PHE-2108), closely resembling the binding mode of rapamycin. Further Prime MM-GBSA analysis confirmed KR4’s stable binding within the mTOR binding site, with a predicted binding energy of -3.00 kcal/mol. These findings suggest that KR4 holds significant potential as a lead compound for developing selective mTOR inhibitors, which could provide new avenues for targeted therapies in cancer and other mTOR-related diseases.
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16. Dienstmann, R., Rodon, J., Serra, V., & Tabernero, J. (2014). Picking the point of inhibition: A comparative review of PI3K/AKT/mTOR pathway inhibitors. Molecular Cancer Therapeutics, 13(5), 1021–1031. https://doi.org/10.1158/1535-7163.MCT-13-0639
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23. Khan, M.F.; Alam, M.M.; Verma, G.; Akhtar, W.; Akhter, M.; Shaquiquzzaman, M (2016). The therapeutic voyage of pyrazole and its analogs: A review. Eur. J. Med. Chem., 120, 170-201.
24. Krämer, S. D., & Testa, B. (2009). The Biochemistry of Drug Metabolism - An Introduction. Chemistry & Biodiversity, 6(7), 1144–1144. https://doi.org/10.1002/cbdv.200990008
25. Levin, G. M. (2012). P-glycoprotein: Why this drug transporter may be clinically important. Current Psychiatry, 11(3), 38–40.
26. Levine, B., & Klionsky, D. J. (2004). Development by self-digestion: Molecular mechanisms and biological functions of autophagy. Developmental Cell, 6(4), 463–477. https://doi.org/10.1016/S1534-5807(04)00099-1
27. Li, J. (2001). for Discovering Leads. 40(2).
28. Limban, C., Nuţă, D. C., Chiriţă, C., Negreș, S., Arsene, A. L., Goumenou, M., … Sarigiannis, D. A. (2018). The use of structural alerts to avoid the toxicity of pharmaceuticals. Toxicology Reports, 5, 943–953. https://doi.org/10.1016/j.toxrep.2018.08.017
29. Lipinski, C. A. (2000). Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological and Toxicological Methods, 44(1), 235–249. https://doi.org/10.1016/S1056-8719(00)00107-6
30. Lokesh R, Jeyakanthan J, Kannabiran K. (2020) Targeting VEGFR2 protein by marine Streptomyces globosus VITLGK011‐derived compound BECA: An in vitro and in silico analysis. J Basic Microbiol.1–11. https://doi.org/10.1002/jobm.202000461
31. Lounkine, E., Keiser, M. J., Whitebread, S., Mikhailov, D., Hamon, J., Jenkins, J. L., … Urban, L. (2012). Large-scale prediction and testing of drug activity on side-effect targets. Nature, 486(7403), 361–367. https://doi.org/10.1038/nature11159
32. Lu, Z., Dono, K., Gotoh, K., Shibata, M., Koike, M., Marubashi, S., … Monden, M. (2005). Participation of autophagy in the degeneration process of rat hepatocytes after transplantation following prolonged cold preservation. Archives of Histology and Cytology, 68, pp. 71–80. https://doi.org/10.1679/aohc.68.71
33. Lynch, T., & Price, A. (2007). The effect of cytochrome P450 metabolism on drug response, interactions, and adverse effects. American Family Physician, 76(3), 391–396.
34. Mahmoud, H. K., Farghaly, T. A., Abdulwahab, H. G., Al-Qurashi, N. T., & Shaaban, M. R. (2020). Novel 2-indolinone thiazole hybrids as sunitinib analogues: Design, synthesis, and potent VEGFR-2 inhibition with potential anti-renal cancer activity. European Journal of Medicinal Chemistry, 208, 112752.
35. Mohanty, M., & Mohanty, P. S. (2023). Molecular docking in organic, inorganic, and hybrid systems: a tutorial review. Monatshefte für Chemie-Chemical Monthly, 1-25.
36. Mondal, P., Natesh, J., Abdul salam, A. ajees, Thiyagarajan, S., & Meeran, S. M. (2020). Traditional medicinal plants against replication, maturation and transmission targets of SARS-CoV-2: computational investigation. Journal of Biomolecular Structure and Dynamics, 40(6), 2715–2732. https://doi.org/10.1080/07391102.2020.1842246
37. Monika, G., Punam, G., Sarbjot, S., & Gupta, G. D. (2010). An overview on molecular docking. International Journal of Drug Development & Research, 2(2).
38. Morris, G. M., Ruth, H., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). Software news and updates AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
39. Muhammad, Z. A., Farghaly, T. A., Althagafi, I., Al‐Hussain, S. A., Zaki, M. E., & Harras, M. F. (2021). Synthesis of antimicrobial azoloazines and molecular docking for inhibiting COVID‐19. Journal of heterocyclic chemistry, 58(6), 1286-1301.
40. Paramashivam, S. K., Elayaperumal, K., Natarajan, B., Ramamoorthy, M., Balasubramanian, S., & Dhiraviam, K. (2015). Insilico pharmacokinetic and molecular docking studies of small molecules derived from Indigofera aspalathoides Vahl targeting receptor tyrosine kinases. Bioinformation, 11(2), 73–84. https://doi.org/10.6026/97320630011073
41. Patrick Walters, W., Stahl, M. T., & Murcko, M. A. (1998). Virtual screening - An overview. Drug Discovery Today, 3(4), 160–178. https://doi.org/10.1016/s1359-6446(97)01163-x
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How to Cite
Rathika Regurajan, Asha Santhi, Venkatesh Subramanian, & Krishnaveni Muthan. (1). Computational Identification of Azole Derivatives Targeting the mTOR Rapamycin Binding Domain for Therapeutic Development. Revista Electronica De Veterinaria, 25(2), 497-507. https://doi.org/10.69980/redvet.v25i2.1411
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