In silico Exploration of Pharmacological and Molecular Descriptor Properties of Salacinol and Its Related Analogues

Year 2024, , 279 - 290, 04.02.2024

Yousif Hussein , Yousif Aziz , Idrees Mohammed Ahmed

https://doi.org/10.18596/jotcsa.1246781

Cited By: 1

Abstract

Salacinol and its related analogues have been known for their potent α-glucosidase inhibitor activity and making them interesting candidates for a new type of anti-diabetic agent. Therefore, it is essential to investigate the physicochemical properties, pharmacological parameters, and toxicity profile of these anti-diabetic agents. In this study, a comprehensive in-silico approach was used to explore the absorption, distribution, metabolism, excretion, and toxicity profiles of salacinol and its related analogues. In addition, to gain a better knowledge of structural and electrical characteristics, global and local reactivity descriptors, and molecular electrostatic potential were calculated and discussed by using DFT at the B3LYP/6–311++G (d, p) level of theory. The results explored that all the studied compounds have low GI absorption and are substrates for P-glycoprotein. None of the compounds can cross the BBB, and none of the compounds are inhibitors of cytochrome P450 isoenzymes. We also found that all compounds have various potential to interact with a wide range of biological targets, including GPCRs, enzymes, ion channels, kinases, and nuclear receptors. Additionally, all compounds have low toxicity and are unlikely to cause any major health hazards in terms of hepatotoxicity, mutagenicity, cardiotoxicity, cytotoxicity, and immunotoxicity. The molecular electrostatic potential map shows that the negative potential sites are in electronegative oxygen atoms, while the positive potential sites are around the hydrogen atoms. The present study concludes that salacinol and its analogues might be a promising safe and effective candidate for the development of therapeutic drugs derived from natural sources. However, some of their properties should be considered in the context of drug development and tissue protection strategies.

Keywords

Salacinol, Drug likeness, ADME, Toxicity profile, Density Functional Theory, Fukui Functions, Anti-diabetic

Supporting Institution

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Project Number

8

References

• 1. Akaki J, Morikawa T, Miyake S, Ninomiya K, Okada M, Tanabe G, et al. Evaluation of Salacia Species as Anti-diabetic Natural Resources Based on Quantitative Analysis of Eight Sulphonium Constituents: A New Class of α-Glucosidase Inhibitors. Phytochem Anal [Internet]. 2014 Nov 1;25(6):544–50. Available from: <URL>.
• 2. Federation ID. IDF diabetes atlas ninth. Dunia Idf. 2019;9:168.
• 3. Morikawa T, Akaki J, Ninomiya K, Kinouchi E, Tanabe G, Pongpiriyadacha Y, et al. Salacinol and Related Analogs: New Leads for Type 2 Diabetes Therapeutic Candidates from the Thai Traditional Natural Medicine Salacia chinensis. Nutrients [Internet]. 2015 Feb 27;7(3):1480–93. Available from: <URL>.
• 4. Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep [Internet]. 2017 Mar 3;7(1):42717. Available from: <URL>.
• 5. Banerjee P, Eckert AO, Schrey AK, Preissner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res [Internet]. 2018 Jul 2;46(W1):W257–63. Available from: <URL>.
• 6. Hussein YT, Azeez YH. DFT analysis and in silico exploration of drug-likeness, toxicity prediction, bioactivity score, and chemical reactivity properties of the urolithins. J Biomol Struct Dyn [Internet]. 2023 Mar 4;41(4):1168–77. Available from: <URL>.
• 7. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev [Internet]. 1997 Jan 15;23(1–3):3–25. Available from: <URL>.
• 8. Veber DF, Johnson SR, Cheng H-Y, Smith BR, Ward KW, Kopple KD. Molecular Properties That Influence the Oral Bioavailability of Drug Candidates. J Med Chem [Internet]. 2002 Jun 1;45(12):2615–23. Available from: <URL>.
• 9. Rahuman MH, Muthu S, Raajaraman BR, Raja M, Umamahesvari H. Investigations on 2-(4-Cyanophenylamino) acetic acid by FT-IR,FT-Raman, NMR and UV-Vis spectroscopy, DFT (NBO, HOMO-LUMO, MEP and Fukui function) and molecular docking studies. Heliyon [Internet]. 2020 Sep 1;6(9):e04976. Available from: <URL>.
• 10. Gaussian 09 RA, Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, et al. Gaussian 16, Revision A. 02, Gaussian. Inc, Wallingford CT. 2016;2.
• 11. Gnanamozhi P, Pandiyan V, Srinivasan P, David Stephen A. Exploring the Structure, Electron Density and HOMOLUMO Studies of Tetrathiafulvalene (TTF) as Organic Superconductors: A DFT and AIM Analysis. J At Mol Condens Nano Phys. 2019;10(1):33–43.
• 12. Choudhary V, Bhatt A, Dash D, Sharma N. DFT calculations on molecular structures, HOMO–LUMO study, reactivity descriptors and spectral analyses of newly synthesized diorganotin(IV) 2‐chloridophenylacetohydroxamate complexes. J Comput Chem [Internet]. 2019 Oct 15;40(27):2354–63. Available from: <URL>.
• 13. R D, Kumar D. Tuning the properties of truxene by successive substitution of nitrogen and sulphur heteroatoms: a DFT insight. J Mol Model [Internet]. 2022 Jan 4;28(1):27. Available from: <URL>.
• 14. Mu T, Xi Y, Huang M, Chen G. Search for optimal monomers for fabricating active layers in thin-film composite osmosis membranes by conceptual density functional theory. J Mol Model [Internet]. 2020 Dec 6;26(12):334. Available from: <URL>.
• 15. Gohlke H, Klebe G. Approaches to the Description and Prediction of the Binding Affinity of Small-Molecule Ligands to Macromolecular Receptors. Angew Chemie Int Ed [Internet]. 2002 Aug 2;41(15):2644–76. Available from: <URL>.
• 16. Husain A, Ahmad A, Khan SA, Asif M, Bhutani R, Al-Abbasi FA. Synthesis, molecular properties, toxicity and biological evaluation of some new substituted imidazolidine derivatives in search of potent anti-inflammatory agents. Saudi Pharm J [Internet]. 2016 Jan 1;24(1):104–14. Available from: <URL>.
• 17. Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol [Internet]. 2004 Dec 1;1(4):337–41. Available from: <URL>.
• 18. Hammoudi N-E-H, Benguerba Y, Attoui A, Hognon C, Lemaoui T, Sobhi W, et al. In silico drug discovery of IKK-β inhibitors from 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives based on QSAR, docking, molecular dynamics and drug-likeness evaluation studies. J Biomol Struct Dyn [Internet]. 2022 Jan 22;40(2):886–902. Available from: <URL>.
• 19. Finch A, Pillans P. P-glycoprotein and its role in drug-drug interactions. Aust Prescr [Internet]. 2014 Aug 1;37(4):137–9. Available from: <URL>.
• 20. Fromm MF. Importance of P-glycoprotein at blood–tissue barriers. Trends Pharmacol Sci [Internet]. 2004 Aug 1;25(8):423–9. Available from: <URL>.
• 21. Kim RB, Fromm MF, Wandel C, Leake B, Wood AJ, Roden DM, et al. The drug transporter P-glycoprotein limits oral absorption and brain entry of HIV-1 protease inhibitors. J Clin Invest [Internet]. 1998 Jan 15;101(2):289–94. Available from: <URL>.
• 22. Kirchmair J, Göller AH, Lang D, Kunze J, Testa B, Wilson ID, et al. Predicting drug metabolism: experiment and/or computation? Nat Rev Drug Discov [Internet]. 2015 Jun 24;14(6):387–404. Available from: <URL>.
• 23. van Waterschoot RAB, Schinkel AH. A Critical Analysis of the Interplay between Cytochrome P450 3A and P-Glycoprotein: Recent Insights from Knockout and Transgenic Mice. Scott EE, editor. Pharmacol Rev [Internet]. 2011 Jun 1;63(2):390–410. Available from: <URL>.
• 24. Cheng F, Li W, Zhou Y, Shen J, Wu Z, Liu G, et al. admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. J Chem Inf Model [Internet]. 2012 Nov 26;52(11):3099–105. Available from: <URL>.
• 25. Kishino E, Ito T, Fujita K, Kiuchi Y. A mixture of Salacia reticulata (Kotala himbutu) aqueous extract and cyclodextrin reduces body weight gain, visceral fat accumulation, and total cholesterol and insulin increases in male Wistar fatty rats. Nutr Res [Internet]. 2009 Jan 1;29(1):55–63. Available from: <URL>.
• 26. Flammang AM, Cifone MA, Erexson GL, Stankowski LF. Genotoxicity testing of a fenugreek extract. Food Chem Toxicol [Internet]. 2004 Nov 1;42(11):1769–75. Available from: <URL>.
• 27. Im R, Mano H, Nakatani S, Shimizu J, Wada M. Safety Evaluation of the Aqueous Extract Kothala Himbutu ( Salacia reticulata ) Stem in the Hepatic Gene Expression Profile of Normal Mice Using DNA Microarrays. Biosci Biotechnol Biochem [Internet]. 2008 Dec 23;72(12):3075–83. Available from: <URL>.
• 28. Jihong Y, Shaozhong L, Jingfeng S, Kobayashi M, Akaki J, Yamashita K, et al. Effects of Salacia chinensis extract on reproductive outcome in rats. Food Chem Toxicol [Internet]. 2011 Jan 1;49(1):57–60. Available from: <URL>.
• 29. Jayawardena MHS, de Alwis NMW, Hettigoda V, Fernando DJS. A double blind randomised placebo controlled cross over study of a herbal preparation containing Salacia reticulata in the treatment of type 2 diabetes. J Ethnopharmacol [Internet]. 2005 Feb 28;97(2):215–8. Available from: <URL>.
• 30. Oda Y, Yuasa A, Ueda F, Kakinuma C. A subchronic oral toxicity study of Salacia reticulata extract powder in rats. Toxicol Reports [Internet]. 2015 Jan 1;2:1136–44. Available from: <URL>.
• 31. Ganesan M, Paranthaman S. Molecular structure, interactions, and antimicrobial properties of curcumin-PLGA Complexes—a DFT study. J Mol Model [Internet]. 2021 Nov 28;27(11):329. Available from: <URL>.
• 32. Suvitha A, El-Mansy MAM, Kothandan G, Steephen A. Molecular Structure, FT-RAMAN, IR, NLO, NBO, HOMO–LUMO analysis, physicochemical descriptors, adme parameters, and pharmacokinetic bioactivity of 2, 3, 5, 6-tetrachloro-p-benzoquinone. J Struct Chem [Internet]. 2021 Sep 26;62(9):1339–56. Available from: <URL>.
• 33. Grillo IB, Urquiza‐Carvalho GA, Chaves EJF, Rocha GB. Semiempirical methods do Fukui functions: Unlocking a modeling framework for biosystems. J Comput Chem [Internet]. 2020 Apr 5;41(9):862–73. Available from: <URL>.
• 34. Cardoso FJB, de Figueiredo AF, da Silva Lobato M, de Miranda RM, de Almeida RCO, Pinheiro JC. A study on antimalarial artemisinin derivatives using MEP maps and multivariate QSAR. J Mol Model [Internet]. 2008 Jan 30;14(1):39–48. Available from: <URL>.
• 35. Obiol-Pardo C, Cordero A, Rubio-Martinez J, Imperial S. Homology modeling of Mycobacterium tuberculosis 2C-methyl-d-erythritol-4-phosphate cytidylyltransferase, the third enzyme in the MEP pathway for isoprenoid biosynthesis. J Mol Model [Internet]. 2010 Jun 15;16(6):1061–73. Available from: <URL>.
• 36. El-Shamy NT, Alkaoud AM, Hussein RK, Ibrahim MA, Alhamzani AG, Abou-Krisha MM. DFT, ADMET and Molecular Docking Investigations for the Antimicrobial Activity of 6,6′-Diamino-1,1′,3,3′-tetramethyl-5,5′-(4-chlorobenzylidene)bis[pyrimidine-2,4(1H,3H)-dione]. Molecules [Internet]. 2022 Jan 18;27(3):620. Available from: <URL>.
• 37. Haddadi Z, Meghezzi H, Amar A, Boucekkine A, Bennamane N, Nedjar-Kolli B, et al. DFT and QSAR investigations of substituent effects in pyrazolooxazine derivatives: Activity prediction. J Theor Comput Chem [Internet]. 2019 Feb 10;18(01):1950001. Available from: <URL>.