Predicting Pharmacokinetic Profiles of Sunflower’s (Helianthus annuus L.) Active Compounds using in Silico Approach

Alif Firman Firdausy, Roihatul Muti'ah, Eka Kartini Rahmawati

Abstract


Introduction: Sunflower (Heliantus annuus L.) widely known as medicinal plant for treating several diseases, such as hypertension, allergy, pain, inflammation, and cancer. It contains various bioactive compounds which some of them were hellianuols. Hellianuols are a sesquiterpene lactones which marked by benzene fused 6- to 8-membered cyclic ether ring structure. To make sure that hellianuols were adequate for development as a new chemical entities, we predicted some pharmacokinetic parameters of several hellianuols compounds (A to L) through in silico approach.

Methods: We constructed 3 dimensional structures of hellianuol A, B, C, D, E, F, G, H, I, J, K and L then generated the SMILE codes of each compound. These codes then used as main material for running pkCSM online tool to predict absorption, distribution, metabolism, and excretion profile of each compounds.

Results: Helianuols predicted to be well absorbed in intestine (90,793% to 95,384% permeability), skin (Log Kp: -2,662 to -3,570), and high permeability against monolayer Caco-2 cell lines (LogPapp: 1,186 to 1,341 ×10-6cm/s). Unfortunately, it had been predicted that hellianuols does not well distributed in the body based on volume of distribution at steady state (VDSS: 0,094 to 0,317) value. But its also predicted that most of hellianuols had a capability to pass through blood-brain barriers (LogBBB: up to 0,389) and penetrated into central nervous system as well. Only hellianuol G, H and K predicted to be metabolized by CYP1A2 inhibitor and only hellianuol A, B, D, E and K metabolized by CYP2C19. Also predicted that hellianuols were excreted in around 0,719 to 1,082 mg/kg/day.

Conclusion: Hellianuols contained in leaf aqueous extract of sunflower predicted to be a good new pharmaceutical entities candidate based on its pharmacokinetic profiles.

Keywords: Hellianuol, sunflower, pharmacokinetic profie, pkCSM online tool


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References


Chiaradia LD, Martins PGA, Cordeiro MNS, Guido RVC, Ecco G, Andricopulo AD, et al. Synthesis, biological evaluation, and molecular modeling of chalcone derivatives as potent inhibitors of Mycobacterium tuberculosis protein tyrosine phosphatases (PtpA and PtpB). J Med Chem. 2012;55(1):390–402.

Hosea NA, Jones HM. Predicting pharmacokinetic profiles using in silico derived parameters. Mol Pharm. 2013;10(4):1207–15.

Macías FA, Varela RM, Torres A, Molinillo JMG. Hellianuol E. A novel bioactive sesquiterpene of the heliannane family. Tetrahedron Lett. 1999;40(25):4725–8.

Macías FA, Varela RM, Torres A, Molinillo JMG. New bioactive plant hellianuols from cultivar sunflower leaves. J Nat Prod. 1999;62(12):1636–9.

Chen K, Li Y, Du Z, Tao Z. Total Syntheses of Hellianuols: An Overview. Synth Commun. 2015;45(6):673–701.

Kuntala N, Telu JR, Banothu V, Babu NS, Anireddy JS, Pal S. Novel benzoxepine–1,2,3-triazole hybrids: Synthesis and pharmacological evaluation as potential antibacterial and anticancer agents. Med Chem Commun. 2015;6(9):1612–9.

Tandon VK, Chandra A. 3,4-Dihydro-l(2H)-Benzoxepine. 1993;6:221–5.

Heffron TP, Wei B, Olivero A, Staben ST, Tsui V, Do S, et al. Rational design of phosphoinositide 3-kinase inhibitors that exhibit selectivity over the phosphoinositide 3-kinase isoform. J Med Chem. 2011;54(22):7815–33.

Lloyd DG, Hughes RB, Zisterer DM, Williams DC, Fattorusso C, Catalanotti B, et al. Benzoxepin-Derived Estrogen Receptor Modulators : A Novel Molecular Scaffold for the Estrogen Receptor. 2004;(Scheme 1):5612–5.

Eto MS, Ramaki YA, Moto HI, Ikawa KA, Da TO. Orally Active CCR5 Antagonists as Anti-HIV-1 Agents 2 : Synthesis and Biological Activities of Anilide Derivatives Containing a Pyridine N -Oxide. 2004;52(7):818–29.

Doi F, Ohara T, Ogamino T, Sugai T, Higashinakasu K, Yamada K, et al. Plant-growth inhibitory activity of hellianuol derivatives. Phytochemistry. 2004;65(10):1405–11.

Chander S, Tang CR, Al-Maqtari HM, Jamalis J, Penta A, Hadda T Ben, et al. Synthesis and study of anti-HIV-1 RT activity of 5-benzoyl-4-methyl-1,3,4,5-tetrahydro-2H-1,5-benzodiazepin-2-one derivatives. Bioorg Chem [Internet]. 2017;72:74–9. Available from: http://dx.doi.org/10.1016/j.bioorg.2017.03.013

Hassan M, Shahzadi S, Seo SY, Alashwal H, Zaki N, Moustafa AA. Molecular docking and dynamic simulation of AZD3293 and solanezumab effects against BACE1 to treat alzheimer’s disease. Front Comput Neurosci. 2018;12(June):1–11.

O’Hagan S, Kell DB. The apparent permeabilities of Caco-2 cells to marketed drugs: Magnitude, and independence fromboth biophysical properties and endogenite similarities. PeerJ. 2015;2015(11).

FDA. Waiver of In Vivo Bioavailability and Bioequivalence Studies for Immediate-Release Solid Oral Dosage Forms Based on a Biopharmaceutics Classification System: Guidance for Industry [Internet]. 1005598 FNL 2017. Available from: https://www.fda.gov/media/70963/download

Lagorce D, Douguet D, Miteva MA, Villoutreix BO. Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep. 2017;7(April):1–15.

Yates JWT, Arundel PA. On the Volume of Distribution at Steady State and Its Relationship With Two‐Compartmental Models. J Pharm Sci [Internet]. 2008 Jan;97(1):111–22. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0022354916324479

pkCSM. Theory - How to interpret pkCSM results [Internet]. 2020 [cited 2020 Feb 17]. Available from: http://biosig.unimelb.edu.au/pkcsm/theory

Pires DEV, Blundell TL, Ascher DB. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J Med Chem. 2015;58(9):4066–72.

Norinder U, Haeberlein M. Computational approaches to the prediction of the blood-brain distribution. Adv Drug Deliv Rev. 2002;54(3):291–313.

Han Y, Zhang J, Hu CQ, Zhang X, Ma B, Zhang P. In silico ADME and toxicity prediction of ceftazidime and its impurities. Front Pharmacol. 2019;10(APR):1–12.

Hardjono S. Prediksi Sifat Farmakokinetik , Toksisitas dan Aktivitas sebagai Calon Obat Antikanker melalui Pemodelan Molekul ( Prediction of Pharmacokinetic Properties , Toxicity and Derivatives as Anticancer Drugs Candidate through Molecular Modeling ). 2017;14(2):246–55.




DOI: https://doi.org/10.18860/jim.v4i1.8840

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