Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR

Ja’far Umar; Turhadi Turhadi; Eko Suyanto; Titin Andri Wihastuti; Fatchiyah Fatchiyah

doi:10.12991/jrespharm.1798014

Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR

Abstract

Obesity-related hypercholesterolemia, a significant risk factor for cardiovascular disease, is metabolic disorder characterized by elevated fatty acid and cholesterol biosynthesis. Brown rice (Oryza sativa L.), a functional food with diverse pharmacological properties, is believed to possess potent anti-obesity and anti-cholesterol effects. This study aimed to identify a potent compound from brown rice that could inhibit key enzymes involved in lipid biosynthesis: fatty acid synthase (FASN), 3-hydroxy-3-methylglutaryl-CoA synthase 1 (HMGCS1), and 3-hydroxy-3- methylglutaryl-CoA reductase (HMGCR). To achieve this, bioactive compounds from brown rice were screened for drug-likeness, toxicity, and bioactivity. Molecular docking was performed to evaluate the binding affinities of selected compounds to the target proteins and was continued molecular dynamic simulation. Among the twenty-six compounds analyzed, five were identified as promising candidates for anti-obesity and anti-cholesterol activities. Trans-3- hydroxycinnamic acid emerged as the most potent compound, exhibiting strong binding affinities to the active sites of FASN (Leu2222, Phe2423), HMGCS1 (Cys129, Tyr171, Ser377), and HMGCR (Glu559, Gly806, Thr809, Met655). Importantly, this compound formed stronger and closer interactions with FASN (-7.4 kcal/mol) and HMGCS1 (-7.2 kcal/mol) compared to the respective drug controls (orlistat and hymeglusin). However, its binding affinity to HMGCR (-6.2 kcal/mol) was weaker than that of simvastatin (-8.3 kcal/mol). Notably, molecular dynamic results demonstrated that the interaction trans-3-hydroxycinnamic acid with FASN and HMGCR was stable. By effectively inhibiting FASN and HMGCR1, trans-3-hydroxycinnamic acid from brown rice has the potential to regulate lipid metabolism, suppress obesity, and prevent complications associated with hypercholesterolemia.

Keywords

References

[1] Mohajan D, Mohajan HK. Obesity and its related diseases: a new escalating alarming in global health. J Innov Med Res. 2023;2(3):12–23. https://doi.org/10.56397/JIMR/2023.03.04.
[2] Koliaki C, Dalamaga M, Liatis S. Update on the obesity epidemic: after the sudden rise, is the upward trajectory beginning to flatten? Curr Obes Rep. 2023;12(4):514–527. https://doi.org/10.1007/s13679-023-00527-y.
[3] Pratama RA, Astina J, Parikesit AA. In silico Screening of Potential Antidiabetic Phenolic Compounds from Banana (Musa spp.) Peel Against PTP1B Protein. J Trop Biodivers Biotechnol. 2023;8(3):1–15. https://doi.org/10.22146/jtbb.83124.
[4] Beheshti SO, Madsen CM, Varbo A, Nordestgaard BG. Worldwide prevalence of familial hypercholesterolemia: meta-analyses of 11 million subjects. J Am Coll Cardiol. 2020;75(20):2553–2566. https://doi.org/10.1016/j.jacc.2020.03.057.
[5] Akimova EV, Frolova EY, Petelina TI, Gakova AA. Obesity and hypercholesterolemia. Int Heart Vasc Dis J. 2019;7(24):10–15.
[6] Nussbaumerova B, Rosolova H. Obesity and dyslipidemia. Curr Atheroscler Rep. 2023;25(12):947–955. https://doi.org/10.1007/s11883-023-01167-2.
[7] Sinning D, Landmesser U. Hypercholesterolemia and cardiovascular risk. Dtsch Med Wochenschr. 2023;148(16):1025–1032. https://doi.org/10.1055/a-1932-6448.
[8] Zecchin KG, Rossato FA, Raposo HF, Melo DR, Alberici LC, Oliveira HC, Castilho RF, Coletta RD, Vercesi AE, Graner E. Inhibition of fatty acid synthase in melanoma cells activates the intrinsic pathway of apoptosis. Lab Invest. 2011 Feb;91(2):232-240. https://doi.org/10.1038/labinvest.2010.157.

[9] Jensen-Urstad APL, Semenkovich CF. Fatty acid synthase and liver triglyceride metabolism: housekeeper or messenger? Biochim Biophys Acta (BBA)-Molecular Cell Biol Lipids. 2012;1821(5):747–753. https://doi.org/10.1016/j.bbalip.2011.09.017.
[10] Panov A V, Mayorov VI, Dikalov SI. Role of Fatty Acids â-Oxidation in the Metabolic Interactions Between Organs. Int J Mol Sci. 2024;25(23):12740. https://doi.org/10.3390/ijms252312740.
[11] Liao P, Wang H, Hemmerlin A, Nagegowda DA, Bach TJ, Wang M, Chye ML. Past achievements, current status and future perspectives of studies on 3-hydroxy-3-methylglutaryl-CoA synthase (HMGS) in the mevalonate (MVA) pathway. Plant Cell Rep. 2014;33(7):1005-1022. https://doi.org/10.1007/s00299-014-1592-9.
[12] Sharpe LJ, Brown AJ. Controlling cholesterol synthesis beyond 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR). J Biol Chem. 2013;288(26):18707–18715. https://doi.org/10.1074/jbc.R113.479808.
[13] Esmail VAW, Al-Nimer MSM, Mohammed MO. Effects of orlistat or Telmisartan on the serum free fatty acids in non-alcoholic fatty liver disease patients: An open-labeled randomized controlled study. Turkish J Gastroenterol. 2022;33(5):421. https://doi.org/10.5152/tjg.2020.19365.
[14] Trub AG, Wagner GR, Anderson KA, Crown SB, Zhang GF, Thompson JW, Ilkayeva OR, Stevens RD, Grimsrud PA, Kulkarni RA, Backos DS, Meier JL, Hirschey MD. Statin therapy inhibits fatty acid synthase via dynamic protein modifications. Nat Commun. 2022;13(1):2542. https://doi.org/10.1038/s41467-022-30060-w.
[15] Brautbar A, Ballantyne CM. Pharmacological strategies for lowering LDL cholesterol: statins and beyond. Nat Rev Cardiol. 2011;8(5):253–265. https://doi.org/10.1038/nrcardio.2011.2.
[16] Zhu J, Hu M, Liang Y, Zhong M, Chen Z, Wang Z, Yang Y, Luo Z, Zeng W, Li J, Du Y, Liu Y, Yang C. Pharmacovigilance analysis of orlistat adverse events based on the FDA adverse event reporting system (FAERS) database. Heliyon. 2024;10(14):e34837. https://doi.org/10.1016/j.heliyon.2024.e34837.
[17] Abed W, Abujbara M, Batieha A, Ajlouni K. Statin induced myopathy among patients attending the National Center for Diabetes, Endocrinology, & Genetics. Ann Med Surg. 2022;74:103304. https://doi.org/10.1016/j.amsu.2022.103304.
[18] Lim M-J, Barathikannan K, Jeong Y-J, Chelliah R, Vijayalakshmi S, Park S-J, Oh D-H. Exploring the Impact of Fermentation on Brown Rice: Health Benefits and Value-Added Foods—A Comprehensive Meta-Analysis. Fermentation. 2024; 10(1):3. https://doi.org/10.3390/fermentation10010003.
[19] Borresen EC, Ryan EP. Rice bran: a food ingredient with global public health opportunities. In: Wheat and rice in disease prevention and health. Elsevier; 2014. pp. 301–310. https://doi.org/10.1016/B978-0-12-401716-0.00022-2.
[20] Ravichanthiran K, Ma ZF, Zhang H, Cao Y, Wang CW, Muhammad S, Aglago EK, Zhang Y, Jin Y, Pan B. Phytochemical Profile of Brown Rice and Its Nutrigenomic Implications. Antioxidants (Basel). 2018;7(6):71. https://doi.org/10.3390/antiox7060071
[21] Maiti S, Banik A. Strategies to fortify the nutritional values of polished rice by implanting selective traits from brown rice: A nutrigenomics-based approach. Food Res Int. 2023;113271. https://doi.org/10.1016/j.foodres.2023.113271.
[22] Matsumoto Y, Fujita S, Yamagishi A, Shirai T, Maeda Y, Suzuki T, Kobayashi KI, Inoue J, Yamamoto Y. Brown Rice Inhibits Development of Nonalcoholic Fatty Liver Disease in Obese Zucker (fa/fa) Rats by Increasing Lipid Oxidation Via Activation of Retinoic Acid Synthesis. J Nutr. 2021;151(9):2705-2713. https://doi.org/10.1093/jn/nxab188.
[23] Imam MU, Ishaka A, Ooi DJ, Zamri NDM, Sarega N, Ismail M, Esa NM. Germinated brown rice regulates hepatic cholesterol metabolism and cardiovascular disease risk in hypercholesterolaemic rats. J Funct Foods. 2014;8:193–203. https://doi.org/10.1016/j.jff.2014.03.013.
[24] Luo H, Mattes W, Mendrick DL, Hong H. Molecular docking for identification of potential targets for drug repurposing. Curr Top Med Chem. 2016;16(30):3636–3645. https://doi.org/10.2174/1568026616666160530181149.
[25] Agu PC, Afiukwa CA, Orji OU, Ezeh EM, Ofoke IH, Ogbu CO, Ugwuja EI, Aja PM. Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in diseases management. Sci Rep. 2023;13(1):13398. https://doi.org/10.1038/s41598-023-40160-2.
[26] Adelusi TI, Oyedele AQK, Boyenle ID, Ogunlana AT, Adeyemi RO, Ukachi CD, Idris MO, Olaoba OT, Adedotun IO, Kolawole OE, Xiaoxing Y, Abdul-Hammed M. Molecular modeling in drug discovery. Informatics Med Unlocked. 2022;29:100880. https://doi.org/10.1016/j.imu.2022.100880.
[27] Chen D, Oezguen N, Urvil P, Ferguson C, Dann SM, Savidge TC. Regulation of protein-ligand binding affinity by hydrogen bond pairing. Sci Adv. 2016;2(3):e1501240. https://doi.org/10.1126/sciadv.1501240.
[28] Liu Y, Yang X, Gan J, Chen S, Xiao ZX, Cao Y. CB-Dock2: Improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting. Nucleic Acids Res. 2022;50(W1):W159–164. https://doi.org/10.1093/nar/gkac394.
[29] Mateev E, Valkova I, Angelov B, Georgieva M, Zlatkov A. Validation through re-docking, cross-docking and ligand enrichment in various well-resoluted MAO-B receptors. Int J Pharm Sci Res. 2022;13:1000–1007. https://doi.org/10.13040/IJPSR.0975-8232.13(3).1099-07.
[30] Shivanika C, Deepak Kumar S, Ragunathan V, Tiwari P, SumithaA, Brindha Devi P. Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. J Biomol Struct Dyn. 2022;40(2):585-611. https://doi.org/10.1080/07391102.2020.1815584.
[31] Vieira TF, Sousa SF. Comparing AutoDock and Vina in ligand/decoy discrimination for virtual screening. Appl Sci. 2019;9(21):4538. https://doi.org/10.3390/app9214538.
[32] Maruyama Y, Igarashi R, Ushiku Y, Mitsutake A. Analysis of protein folding simulation with moving root mean square deviation. J Chem Inf Model. 2023;63(5):1529–1541. https://doi.org/10.1021/acs.jcim.2c01444.
[33] Widyananda MH, Wicaksono ST, Rahmawati K, Puspitarini S, Ulfa SM, Jatmiko YD, Masruri M, Widodo N. A Potential Anticancer Mechanism of Finger Root (Boesenbergia rotunda) Extracts against a Breast Cancer Cell Line. Scientifica (Cairo). 2022;2022:9130252. https://doi.org/10.1155/2022/9130252.
[34] Bickerton GR, Paolini G V, Besnard J, Muresan S, Hopkins AL. Quantifying the chemical beauty of drugs. Nat Chem. 2012;4(2):90–98. https://doi.org/10.1038/nchem.1243.
[35] Banerjee P, Eckert AO, Schrey AK, Preissner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2018;46(W1):W257–263. https://doi.org/10.1093/nar/gky318.
[36] Dmitriev AV, Filimonov DA, Rudik AV, Pogodin PV, Karasev DA, Lagunin AA, Poroikov VV. Drug-drug interaction prediction using PASS. SAR QSAR Environ Res. 2019;30(9):655-664. https://doi.org/10.1080/1062936X.2019.1653966.
[37] Arslan Ö, Akdemir FNE. Antioxidant effect of trans-3 hydroxycinnamic acid against liver damage methotrexate induced in rats. JAPS J Anim Plant Sci. 2018;28(6): 1574-1578.
[38] Teixeira J, Gaspar A, Garrido EM, Garrido J, Borges F. Hydroxycinnamic acid antioxidants: an electrochemical overview. Biomed Res Int. 2013;2013(1):251754. https://doi.org/10.1155/2013/251754.
[39] Alam MA, Subhan N, Hossain H, Hossain M, Reza HM, Rahman MM, Ullah MO. Hydroxycinnamic acid derivatives: a potential class of natural compounds for the management of lipid metabolism and obesity. Nutr Metab (Lond). 2016;13:27. https://doi.org/10.1186/s12986-016-0080-3.
[40] Angeles TS, Hudkins RL. Recent advances in targeting the fatty acid biosynthetic pathway using fatty acid synthase inhibitors. Expert Opin Drug Discov. 2016;11(12):1187–1199. https://doi.org/10.1080/17460441.2016.1245286.
[41] Zhu JJ, Luo J, Sun YT, Shi HB, Li J, Wu M, Yu K, Haile AB, Loor JJ. Short communication: Effect of inhibition of fatty acid synthase on triglyceride accumulation and effect on lipid metabolism genes in goat mammary epithelial cells. J Dairy Sci. 2015 May;98(5):3485-3491. https://doi.org/10.3168/jds.2014-8202.
[42] Schumacher MM, DeBose-Boyd RA. Posttranslational regulation of HMG CoA reductase, the rate-limiting enzyme in synthesis of cholesterol. Annu Rev Biochem. 2021;90(1):659–679. https://doi.org/10.1146/annurev-biochem-081820-101010.
[43] Zhang C, Jin DD, Wang XY, Lou L, Yang J. Key enzymes for the mevalonate pathway in the cardiovascular system. J Cardiovasc Pharmacol. 2021;77(2):142–152. https://doi.org/10.1097/FJC.0000000000000952.
[44] Ishaka A, Imam MU, Ismail M, Mahmud R, Bakar ZZA. Nanoemulsified gamma-oryzanol rich fraction blend regulates hepatic cholesterol metabolism and cardiovascular disease risk in hypercholesterolaemic rats. J Funct Foods. 2016;26:338–349. https://doi.org/10.1016/j.jff.2016.08.015.
[45] Rafieian-Kopaei M, Setorki M, Doudi M, Baradaran A, Nasri H. Atherosclerosis: process, indicators, risk factors and new hopes. Int J Prev Med. 2014;5(8):927-946.
[46] 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(1):42717. https://doi.org/10.1038/srep42717.
[47] Duan Y, Gong K, Xu S, Zhang F, Meng X, Han J. Regulation of cholesterol homeostasis in health and diseases: from mechanisms to targeted therapeutics. Signal Transduct Target Ther. 2022;7(1):265. https://doi.org/10.1038/s41392-022-01125-5.
[48] Wen X, Zhang B, Wu B, Xiao H, Li Z, Li R, Xu X, Li T. Signaling pathways in obesity: mechanisms and therapeutic interventions. Signal Transduct Target Ther. 2022;7(1):298. doi: 10.1038/s41392-022-01149-x. Erratum in: Signal Transduct Target Ther. 2022;7(1):369. https://doi.org/10.1038/s41392-022-01149-x.
[49] Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, Doncheva NT, Legeay M, Fang T, Bork P, Jensen LJ, von Mering C. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49(D1):D605-D612. https://doi.org/10.1093/nar/gkaa1074.
[50] Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, Wu S, Wang Y. SRplot: A free online platform for data visualization and graphing. PLoS One. 2023;18(11):e0294236. https://doi.org/10.1371/journal.pone.0294236.
[51] Castro-Alvarez A, Costa AM, Vilarrasa J. The performance of several docking programs at reproducing protein–macrolide-like crystal structures. Molecules. 2017;22(1):136. https://doi.org/10.3390/molecules22010136.
[52] Chaput L, Martinez-Sanz J, Saettel N, Mouawad L. Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance. J Cheminform. 2016;8:56. https://doi.org/10.1186/s13321-016-0112-z.
[53] Umar J, Suyanto E, Wihastuti TA, Fatchiyah F. Virtual selection of γ-oryzanol derivatives of brown rice (Oryza sativa L.) blocking HMG-CoA reductase in hypercholesterolemia disease. Berk Penelit Hayati. 2025;31(1):19–27. http://dx.doi.org/10.23869/bphjbr.31.1.20244.
[54] Ozvoldik K, Stockner T, Krieger E. YASARA model–interactive molecular modeling from two dimensions to virtual realities. J Chem Inf Model. 2023;63(20):6177–6182. https://doi.org/10.1021/acs.jcim.3c01136.
[55] Pemble CW 4th, Johnson LC, Kridel SJ, Lowther WT. Crystal structure of the thioesterase domain of human fatty acid synthase inhibited by Orlistat. Nat Struct Mol Biol. 2007;14(8):704-9. doi:10.1038/nsmb1265
[56] Shafqat N, Turnbull A, Zschocke J, Oppermann U, Yue WW. Crystal structures of human HMG-CoA synthase isoforms provide insights into inherited ketogenesis disorders and inhibitor design. J Mol Biol. 2010;398(4):497-506. doi:10.1016/j.jmb.2010.03.034
[57] Gesto DS, Pereira CM, Cerqueira NM, Sousa SF. An atomic-level perspective of HMG-CoA-reductase: the target enzyme to treat hypercholesterolemia. Molecules. 2020;25(17):3891. doi:10.3390/molecules25173891

Details

Primary Language

English

Subjects

Toxicology

Journal Section

Research Article

Authors

Ja’far Umar This is me
0009-0005-7860-2516
Indonesia

Turhadi Turhadi
0000-0003-4906-3769
Indonesia

Eko Suyanto
0000-0002-0748-4242
Indonesia

Titin Andri Wihastuti
0000-0001-6476-0541
Indonesia

Fatchiyah Fatchiyah ^*
0000-0001-6241-9665
Indonesia

Publication Date

November 2, 2025

Submission Date

December 23, 2024

Acceptance Date

February 22, 2025

Published in Issue

Year 2025 Volume: 29 Number: 6

DOI

https://doi.org/10.12991/jrespharm.1798014

IZ

https://izlik.org/JA29FJ34JB

Cite

RIS / Bibtex

APA

Umar, J., Turhadi, T., Suyanto, E., Wihastuti, T. A., & Fatchiyah, F. (2025). Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR. Journal of Research in Pharmacy, 29(6), 2486-2507. https://doi.org/10.12991/jrespharm.1798014

AMA

1.Umar J, Turhadi T, Suyanto E, Wihastuti TA, Fatchiyah F. Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR. J. Res. Pharm. 2025;29(6):2486-2507. doi:10.12991/jrespharm.1798014

Chicago

Umar, Ja’far, Turhadi Turhadi, Eko Suyanto, Titin Andri Wihastuti, and Fatchiyah Fatchiyah. 2025. “Computational Screening of the Potent Bioactive Compound of Brown Rice (Oryza Sativa L.) Against Obesityrelated Hypercholesterolemia by Targeting FASN, HMGCS1, and HMGCR”. Journal of Research in Pharmacy 29 (6): 2486-2507. https://doi.org/10.12991/jrespharm.1798014.

EndNote

Umar J, Turhadi T, Suyanto E, Wihastuti TA, Fatchiyah F (November 1, 2025) Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR. Journal of Research in Pharmacy 29 6 2486–2507.

IEEE

[1]J. Umar, T. Turhadi, E. Suyanto, T. A. Wihastuti, and F. Fatchiyah, “Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR”, J. Res. Pharm., vol. 29, no. 6, pp. 2486–2507, Nov. 2025, doi: 10.12991/jrespharm.1798014.

ISNAD

Umar, Ja’far - Turhadi, Turhadi - Suyanto, Eko - Wihastuti, Titin Andri - Fatchiyah, Fatchiyah. “Computational Screening of the Potent Bioactive Compound of Brown Rice (Oryza Sativa L.) Against Obesityrelated Hypercholesterolemia by Targeting FASN, HMGCS1, and HMGCR”. Journal of Research in Pharmacy 29/6 (November 1, 2025): 2486-2507. https://doi.org/10.12991/jrespharm.1798014.

JAMA

1.Umar J, Turhadi T, Suyanto E, Wihastuti TA, Fatchiyah F. Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR. J. Res. Pharm. 2025;29:2486–2507.

MLA

Umar, Ja’far, et al. “Computational Screening of the Potent Bioactive Compound of Brown Rice (Oryza Sativa L.) Against Obesityrelated Hypercholesterolemia by Targeting FASN, HMGCS1, and HMGCR”. Journal of Research in Pharmacy, vol. 29, no. 6, Nov. 2025, pp. 2486-07, doi:10.12991/jrespharm.1798014.

Vancouver

1.Ja’far Umar, Turhadi Turhadi, Eko Suyanto, Titin Andri Wihastuti, Fatchiyah Fatchiyah. Computational screening of the potent bioactive compound of brown rice (Oryza sativa L.) against obesityrelated hypercholesterolemia by targeting FASN, HMGCS1, and HMGCR. J. Res. Pharm. 2025 Nov. 1;29(6):2486-507. doi:10.12991/jrespharm.1798014

Cited By

Impact of γ-oryzanol rich–brown rice extract on body weight, cholesterol profile, and histopathology of adipose, liver, and kidney tissue in hypercholesterolemic rats

CyTA - Journal of Food

https://doi.org/10.1080/19476337.2025.2604377

The Therapeutic Potential of Moringa oleifera in Inflammation-Induced Insulin Resistance: An Informatics Approach

Biointerface Research in Applied Chemistry

https://doi.org/10.33263/BRIAC161.010