IN-SILICO PHARMACOKINETICS PREDICTION OF MAJOR COUMARINS PRESENT IN AEGLE MARMELOS L.

Abstract

Natural coumarins has enormous power as natural magical remedy for wide range of diseases, they are present in high concentrations in several dietary plant species like cinnamon, lemon, dill, soy oil, peanut oil, olive oil etc. In the larger category of nutraceuticals natural coumarins contribute for various activities, their pharmacotherapeutic aspects have been already published. A large amount of coumarin intake may have negative impact on health as the safety profile of coumarins was not thoroughly reviewed to present date [1-3]. The subtropical fruit Aegle marmelos L (A.M.) commonly known as Bael, a plant of Indian origin belongs to the Rutaceae family. Bael has been used as a medicine for diarrhea and dysentery treatment since 5000 B.C. [4]. Selective coumarins present in A.M. like umbelliferone, scopoletin, scoparone, xanthotoxol, marmesin, psoralen, imperatorin, alloimperatorin, and marmin [5-6] was taken for in silico ADME screening using SwissADME software [7]. In silico methods have the advantage that they can make fast predictions for a large set of compounds in a highthroughput mode. The earlier detection of PK/PD properties along with drug likeness and ADME profiling can save both money and time. It is also ensuring the safety and stability of the candidate-drugs or designed-drugs In Lipophilicity property, the rule says, “The larger the log P value greater the lipophilicity" [8]. XLOGP3 value of coumarins is in the range of -0.7 to + 5.0 size which indicates that they are lipophilic compounds, Log S (ESOL), Log S (ali), and Log S (SILICOS-IT) values of umbelliferone, scopoletin, scoparone, xanthotoxol, and marmesin shows good water solubility whereas psoralen, imperatorin, alloimperatorin, and marmin are moderately soluble in water [9]. According to pharmacokinetic properties, all other coumarins showed good GI absorption and penetration at BBB whereas marmin showed no penetration at BBB [10-13]. All coumarins showed no inhibition of the isoenzymes like CYP2D6, CYP3A4 as well as they are not good P-gp substrates which is clear indication of their low toxicity and no drug-drug interactions. The isoenzyme CYP1A2 found to be inhibited by all coumarins other than marmin whereas imperatoin, and alloimperatorin are inhibiting the isoenzymes like CYP2C19, CYP2C9 which leads to increase in bioavailability of drug. All selected coumarin were in the limit of Lipinski, Veber, and Egan filters which make them to have promising drug likeness properties. In the BOILED egg model, all coumarins found in yellow regions (i.e., regions of high BBB absorption and high GI absorption) except marmin which is located on the boundary of white and yellow region that means it has good GI absorption, and no BBB permeation property. This data supports to conduct pre-clinical and clinical trials of bael fruit-based products such as squash, jelly, candy, etc. which will increase their value as food and nutraceutical products by a huge margin.

Keywords

• Aegle marmelos L.
• coumarin
• in silico predictions
• SwissADME

References

1. [1] Heghes SC, Vostinaru O, Mogosan C, Miere D, Iuga CA, Filip L. Safety profile of nutraceuticals rich in coumarins: An update. Front Pharmacol. 2022;13:803338. [CrossRef]
2. [2] Sarkar T, Salauddin M, Chakraborty R. In-depth pharmacological and nutritional properties of bael (Aegle marmelos): A critical review. J Agric Food Res. 2020;2:100081. [CrossRef]
3. [3] Lončar M, Jakovljević M, Šubarić D, Pavlić M, Buzjak Služek V, Cindrić I, Molnar M. Coumarins in food and methods of their determination. Foods. 2020;9(5):645. [CrossRef]
4. [4] Patel P, Sahu J, Sahu L, Prajapati N. Aegle marmelos: A review on its medicinal properties. Int J Pharm Phytopharmacol Res. 2012;1:332–341.
5. [5] Sharma GN, Dubey SK, Sharma P, Sati N. Medicinal values of bael (Aegle marmelos L. Corr.): A review. Int J Curr Pharm Res. 2011;1(3):12–22.
6. [6] 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. 2017;7:42717. [CrossRef]
7. [7] Arnott AJ, Lobo Planey S. The influence of lipophilicity in drug discovery and design. Expert Opin Drug Discov. 2012;7(10):863–875. [CrossRef]
8. [8] Moriguchi I, Hirono S, Nakagome I, Hirano H. Comparison of reliability of log P values for drugs calculated by several methods. Chem Pharm Bull. 1994;42(4):976–978. [CrossRef]

9. [9] Ali J, Camilleri P, Brown MB, Hutt AJ, Kirton SB. Revisiting the general solubility equation: In silico prediction of aqueous solubility incorporating the effect of topographical polar surface area. J Chem Inf Model. 2012;52(2):420–428. [CrossRef]
10. [10] 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. 2001;46(1):3–26. [CrossRef]
11. [11] Ghose AK, Viswanadhan VN, Wendoloski JJ. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. A qualitative and quantitative characterization of known drug databases. J Comb Chem. 1998;1(1):55–68. [CrossRef]
12. [12] Veber DF, Johnson SR, Cheng HY, Smith BR, Ward KW, Kopple KD. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem. 2002;45(12):2615–2623. [CrossRef]
13. [13] Egan WJ, Baldwin JJ. Prediction of drug absorption using multivariate statistics. J Med Chem. 2000;43(21):3867–3877. [CrossRef]