Computational study of the inhibitory potential of Gongronema latifolium (benth) leave on farnesyl pyrophosphate synthase, a target enzyme in the treatment of osteoporosis. A molecular modelling approach
Subject Areas : Journal of Medicinal Herbs, "J. Med Herb" (Formerly known as Journal of Herbal Drugs or J. Herb Drug)
ساموئل اولوبود
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بانکول موتولیب
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پرسوس آکینوسی
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واسیو سالودین
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کهینده اوجوبولا
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اولاینکا آدانلاوو
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ابیگیل آیودل
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آدفونکه اوگونلاد
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عبداللهی آدرمی
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1 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
2 - گروه علوم شیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
3 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
4 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
5 - گروه علوم شیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
6 - گروه علوم شیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
7 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
8 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
9 - گروه بیوشیمی، دانشگاه آدکانله آجاسین آکونگبا آکوکو، ایالت اوندو نیجریه.
Keywords: Osteoporosis, Molecular docking, Farnesyl pyrophosphate synthase (FPPS), Gongronema latifolium, mevalonate pathway,
Abstract :
Background & Aim: Osteoporosis is an increasing medical threat which is referred to as a systemic skeletal disorder that is characterized mainly by low bone mass and microarchitectural wear of bone tissue and strength, which eventually results in an increase in the fragility of bone and makes bone to be susceptible to fracture. Osteoporosis is known globally as a severe health problem affecting approximately 200 million people worldwide. Therefore, a pharmacological solution is urgently needed. Studies have shown that farnesyl pyrophosphate synthase is a crucial enzyme in the mevalonate pathway that causes bone resorption, thus serving as a key pharmacological target.Experimental: Gongronema latifolium’s (Benth) phytoconstituents were screened against the mevalonate pathway enzyme farnesyl pyrophosphate synthase computationally using molecular docking, pharmacokinetics screening and Molecular Mechanics/Generalized Born Surface Area approach to identify compounds with the better inhibitorypotentials against this target in this study.Results: The study resulted that five compounds; hyperoside, rutin, epigallocatechin-3-gallate, kaempferol-3-arabinoside, and isoquercetin show a better inhibitory potential by binding to the active site of farnesyl pyrophosphate synthase compared with a co-crystalized ligand. These hit compounds were further subjected to pharmacokinetics studies to predict their drug-likeness and toxicity characteristics which show that all hit compounds except Rutin are drug-like leaving Kaempferol-3-Arabinoside as the most drug-like hit compound compared to the co-crystallized ligand.Recommended applications/industries: This study suggests that G. latifolium leaf could be a good plant source for a drug-like compound that may treat osteoporosis by inhibiting the farnesyl pyrophosphate synthase, in the mevalonate pathway, thereby stopping bone resorption.
Adebesin, A. O., Ayodele, A. O., Omotoso, O., Akinnusi, P. A. and Olubode, S. O. 2022. Computational evaluation of bioactive compounds from Vitis vinifera as a novel β-catenin inhibitor for cancer treatment. Bulletin of the National Research Centre, 46(1): 1-9.
Akinnusi, P. A., Olubode, S. O. and Salaudeen, W. A. 2022. Molecular binding studies of anthocyanins with multiple antiviral activities against SARS-CoV-2. Bulletin of the National Research Centre, 46(1): 102.
Asthana, S., Agarwal, T., Banerjee, I. and Ray, S. S. 2014. In silico screening to elucidate the therapeutic potentials of asparagamine A. International Journal of Pharmacy and Pharmaceutical Sciences, 6(3):247-253.
Bandyopadhyay, S., Abiodun, O. A., Ogboo, B. C., Kola-Mustapha, A. T., Attah, E. I., Edemhanria, L. and Adelakun, N. S. 2021. Polypharmacology of some medicinal plant metabolites against SARS-CoV-2 and host targets: Molecular dynamics evaluation of NSP9 RNA binding protein. Journal of Biomolecular Structure and Dynamics, 1-17.
Bathula, R., Muddagoni, N., Lanka, G., Dasari, M. and Potlapally, S. R. 2021. Glide docking, autodock, binding free energy and drug-likeness studies for prediction of potential inhibitors of cyclin-dependent kinase 14 protein in Wnt signaling pathway. Biointerface Research in Applied Chemistry, 12(2): 2473–2488.
Burge, R., Dawson‐Hughes, B., Solomon, D. H., Wong, J. B., King, A. and Tosteson, A. (2007). Incidence and economic burden of osteoporosis‐related fractures in the United States, 2005–2025. Journal of Bone and Mineral Research, 22(3): 465-475.
Cooper, C. 1999. Epidemiology of osteoporosis. Osteoporosis International, 9: S2.
Dehof, A. K., Rurainski, A., Bui, Q. B. A., Böcker, S., Lenhof, H. P. and Hildebrandt, A. 2011. Automated bond order assignment as an optimization problem. Bioinformatics, 27(5): 619-625.
DeLano, W. L. 2002. Pymol: An open-source molecular graphics tool. CCP4 Newsl. Protein Crystallogr, 40(1): 82-92.
Edim, E. H., Egomi, U. G., Ekpo, U. F. and Archibong, E. U. 2012. A review on Gongronemalatifolium (Utasi): A novel antibiotic against Staphylococcus aureus related infections. International Journal of Biochemistry and Biotechnology, 1(8): 204208.
Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A. and Klicic, J. J. JL. 2004. Glide: A new approach for rapid, accurate docking and scoring. 1. method and assessment of docking accuracy. Journal of Medicinal Chemistry, 47(7): 1739-1749.
Gabelli, S. B., McLellan, J. S., Montalvetti, A., Oldfield, E., Docampo, R. and Amzel, L. M. 2006. Structure and mechanism of the farnesyl diphosphate synthase from Trypanosoma cruzi: implications for drug design. PROTEINS: Structure, Function, and Bioinformatics, 62(1): 80-88.
Harder, E., Damm, W., Maple, J., Wu, C., Reboul, M., Xiang, J. Y. and Friesner, R. A. 2016. OPLS3: a force field providing broad coverage of drug-like small molecules and proteins. Journal of Chemical Theory and Computation, 12(1): 281-296.
Imo, C. and Uhegbu, F. O. 2015. Phytochemical analysis of Gongronema latifolium Benth leaf using gas chromatographic flame ionization detector. International Journal of Chemistry and Biomolecule Science, 1: 60-8.
Inyang, O. K., Omotuyi, O. I., Ogunleye, A. J., Eniafe, G. O. and Adewumi, B. 2017. Molecular interaction and inhibitory potential of polyphenol on DNA repair pathway in small cell lung cancer: A computational study. Journal of Analytical and Pharmaceutical Research, 6(3): 00178.
Jama, N. 2001. Consensus development panel on osteoporosis prevention, diagnosis, and therapy. Osteoporosis prevention, diagnosis, and therapy. Journal of the American Medicinal Association, 85: 785-95.
Kanis, J. A. and Johnell, O. 2005. Requirements for DXA for the management of osteoporosis in Europe. Osteoporosis International, 16(3): 229-238.
Kanis, J. A., Melton III, L. J., Christiansen, C., Johnston, C. C. and Khaltaev, N. 1994. The diagnosis of osteoporosis. Journal of Bone and Mineral Research, 9(8): 1137-1141.
Kenakin, T. 2016. Pharmacology in drug discovery and development: Understanding drug response. Academic Press.
Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A. and Wang, J. 2016. BS The PubChem Project. Nucleic Acids Research, 44(D1): D1202-13.
Lipinski, C. A. 2004. Lead-and drug-like compounds: the rule-of-five revolution. Drug Discovery Today: Technologies, 1(4): 337-341.
Madhavi Sastry, G., Adzhigirey, M., Day, T., Annabhimoju, R. and Sherman, W. 2013. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. Journal of Computer-aided Molecular Design, 27(3): 221-234.
Olubode, S. O., Bankole, M. O., Akinnusi, P. A., Adanlawo, O. S., Ojubola, K. I., Nwankwo, D. O., Edjebah, O. E., Adebesin, A. O. and Ayodele, A. O. 2022. Molecular modeling studies of natural inhibitors of androgen signaling in prostate cancer. Cancer Informatics, 21: 11769351221118556.
Olubode, S. O., Omotuyi, O. I. and Fadipe, D. O. 2021. Computational prediction of HCV RNA polymerase inhibitors from alkaloid library. Letters in Applied Nano BioScience, 11(3): 3661–3671.
Reginster, J. Y. and Burlet, N. 2006. Osteoporosis: a still increasing prevalence. Bone, 38(2): 4-8.
Release, S. 2017. 2: LigPrep, Schrödinger, LLC, New York, NY, 2017. New York, NY.
Riggs, B. L. and Melton Iii, L. J. 1995. The worldwide problem of osteoporosis: insights afforded by epidemiology. Bone, 17(5): S505-S511.
Schrödinger Release 2021-1: Epik, Schrödinger, LLC, New York, NY, 2021;
Schrödinger, L. L. C. 2017. Schrödinger, LLC; New York, NY: 2017. Schrödinger Suite, 2, 2017-1.
Seeley, D. G., Browner, W. S., Nevitt, M. C., Genant, H. K., Scott, J. C. and Cummings, S. R. 1991. Which fractures are associated with low appendicular bone mass in elderly women? Annals of Internal Medicine, 115(11): 837-842.
Shelley, J. C., Cholleti, A., Frye, L. L., Greenwood, J. R., Timlin, M. R. and Uchimaya, M. 2007. Epik: a software program for pK a prediction and protonation state generation for drug-like molecules. Journal of Computer-Aided Molecular Design, 21(12): 681-691.
Prevention, O. 2001. Diagnosis, and Therapy. NIH Consensus Development Panel on Osteoporosis. Jama, 285: 785-795.
Varma, M. V., Khandavilli, S., Ashokraj, Y., Jain, A., Dhanikula, A., Sood, A. and Panchagnula, R. 2004. Biopharmaceutic classification system: a scientific framework for pharmacokinetic optimization in drug research. Current Drug Metabolism, 5(5): 375-388.
Vijayakumar, R. and Büsselberg, D. 2016. Osteoporosis: An under-recognized public health problem: Local and global risk factors and its regional and worldwide prevalence. Journal of Local and Global Health Science, 2016(1): 2.
Wright, N. C., Looker, A. C., Saag, K. G., Curtis, J. R., Delzell, E. S., Randall, S. and Dawson Hughes, B. 2014. The recent prevalence of osteoporosis and low bone mass in the United States based on bone mineral density at the femoral neck or lumbar spine. Journal of Bone and Mineral Research, 29(11): 2520-2526.