ADMET informatics of Tetradecanoic acid (Myristic Acid) from ethyl acetate fraction of Moringa oleifera leaves
Abstract
In-silico Computer-Aided Drug Design (CADD) often comprehends virtual screening (VS) of datasets of natural pharmaco-active compounds for drug discovery protocols. Plant Based Natural Products (PBNPs) still, remains to be a prime source of pharmaco-active compounds due to their unique chemical structural scaffolds and functionalities with distinct chemical characteristic feature from natural source that are much acquiescent to drug metabolism and kinetics. In the Post-COVID-Era number of publications pertaining to PBNPs and publicly accessible plant based natural product databases (PBNPDBs) has significantly increased. Moreover, PBNPs are important sources of inspiration or starting points to develop novel therapeutic agents. However, a well-structured, in-depth ADME/Tox profile of PBNPs has been limited or lacking for many of such compounds, this hampers the successful exploitation of PBNPs by pharma industries. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties play key roles in the discovery/ development of drugs, pesticides, food additives, consumer products, and industrial chemicals. In the present study, ADMET-informatics of Tetradecanoic Acid (Myristic Acid) from ethyl acetate fraction of Moringa oleifera leaves to predict drug metabolism and pharmacokinetics (DMPK) outcomes has been taken up. This work contributes to the deeper understanding of Myristic acid as major source of drug from commonly available medicinal plant - Moringa oleifera with immense therapeutic potential. The data generated herein could be useful for NP based lead generation programs.
Keywords: Moringa oleifera; Secondary Metabolites; Bioactive Substances; Myristic acid (MA); DMPK; ADME/Tox; Natural Products (NPs); PBNPs; PBNPDBs
Keywords:
Moringa oleifera, Secondary Metabolites, Bioactive Substances, Myristic acid (MA), DMPK, ADME/Tox, Natural Products (NPs), PBNPs, PBNPDBsDOI
https://doi.org/10.22270/jddt.v12i4-S.5533References
Playfair L. On a new fat acid in the butter of nutmegs. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. 1841; 18(115):102-113. https://doi.org/10.1080/14786444108650255
Balvers MG, Verhoeckx KC, Plastina P, Wortelboer HM, Meijerink J, Witkamp RF. Docosahexaenoic acid and eicosapentaenoic acid are converted by 3T3-L1 adipocytes to N-acyl ethanolamines with anti-inflammatory properties. Biochimica et Biophysica Acta (BBA)-Molecular and Cell Biology of Lipids. 2010; 1801(10):1107-14. https://doi.org/10.1016/j.bbalip.2010.06.006
Mahmoudi R, Ghareghani M, Zibara K, Tajali Ardakani M, Jand Y, Azari H, Nikbakht J, Ghanbari A. Alyssum homolocarpum seed oil (AHSO), containing natural alpha linolenic acid, stearic acid, myristic acid and β-sitosterol, increases proliferation and differentiation of neural stem cells in vitro. BMC Complementary and Alternative Medicine. 2019; 19(1):1-1. https://doi.org/10.1186/s12906-019-2518-4
Udenwobele DI, Su RC, Good SV, Ball TB, Varma Shrivastav S, Shrivastav A. Myristoylation: An important protein modification in the immune response. Frontiers in immunology. 2017; 8:751. https://doi.org/10.3389/fimmu.2017.00751
Sarkic A, Stappen I. Essential oils and their single compounds in cosmetics-A critical review. Cosmetics. 2018; 5(1):11. https://doi.org/10.3390/cosmetics5010011
Padayachee B, Baijnath H. An overview of the medicinal importance of Moringaceae. Journal of Medicinal Plants Research. 2012; 6(48):5831-9.
Murugan M, Krishnaveni K, Sabitha M, Kandeepan C, Senthilkumar N, Loganathan T, Pushpalatha GL, Pandiarajan G, Ramya S, Jayakumararaj R. In silico Target Class Prediction and Probabilities for Plant Derived Omega 3 Fatty Acid from Ethyl Acetate Fraction of Moringa oleifera Leaf Extract. Journal of Drug Delivery and Therapeutics. 2022; 12(3):124-37. https://doi.org/10.22270/jddt.v12i3.5352
Meena R, Prajapati SK, Nagar R, Porwal O, Nagar T, Tilak VK, Jayakumararaj R, Arya RK, Dhakar RC. Application of Moringa oleifera in Dentistry. Asian Journal of Dental and Health Sciences. 2021; 1(1):10-3.
Parvathi K, Kandeepan C, Sabitha M, Senthilkumar N, Ramya S, Boopathi NM, Ramanathan L, Jayakumararaj R. In-silico Absorption, Distribution, Metabolism, Elimination and Toxicity profile of 9, 12, 15-Octadecatrienoic acid (ODA) from Moringa oleifera. Journal of Drug Delivery and Therapeutics. 2022; 12(2-S):142-50. https://doi.org/10.22270/jddt.v12i2-S.5289
Kou X, Li B, Olayanju JB, Drake JM, Chen N. Nutraceutical or pharmacological potential of Moringa oleifera Lam. Nutrients. 2018; 10(3):343. https://doi.org/10.3390/nu10030343
Saini RK, Sivanesan I, Keum YS. Phytochemicals of Moringa oleifera: a review of their nutritional, therapeutic and industrial significance. 3 Biotech. 2016; 6(2):1-4. https://doi.org/10.1007/s13205-016-0526-3
Rathnayake ARMHA, Navaratne SB, Uthpala TGG Moringa oleifera plant and the nutritional and medicinal properties of Moringa oleifera leaves Trends Pros. Process. Hort. Crops (2019), pp. 251-268
Luqman S, Srivastava S, Kumar R, Maurya AK, Chanda D. Experimental assessment of Moringa oleifera leaf and fruit for its antistress, antioxidant, and scavenging potential using in vitro and in vivo assays. Evidence-Based Complementary and Alternative Medicine. 2012; 2012. https://doi.org/10.1155/2012/519084
Jung IL. Soluble extract from Moringa oleifera leaves with a new anticancer activity. PloS one. 2014; 9(4):e95492. https://doi.org/10.1371/journal.pone.0095492
Manavalan N, Boopathi NM, Raveendran M. Medicinal and Therapeutic Properties of Moringa. In The Moringa Genome 2021 (pp. 31-39). Springer, Cham. https://doi.org/10.1007/978-3-030-80956-0_4
Abalaka ME, Daniyan SY, Oyeleke SB, Adeyemo SO. The antibacterial evaluation of Moringa oleifera leaf extracts on selected bacterial pathogens. Journal of Microbiology research. 2012; 2(2):1-4. https://doi.org/10.5923/j.microbiology.20120202.01
Patel P, Patel N, Patel D, Desai S, Meshram D. Phytochemical analysis and antifungal activity of Moringa oleifera. International Journal of Pharmacy and Pharmaceutical Sciences. 2014; 6(5):144-7.
Boopathi NM, Abubakar BY. Botanical Descriptions of Moringa spp. In The Moringa Genome 2021 (pp. 11-20). Springer, Cham. https://doi.org/10.1007/978-3-030-80956-0_2
Kandeepan C, Sabitha M, Parvathi K, Senthilkumar N, Ramya S, Boopathi NM, Jayakumararaj R. Phytochemical Screening, GCMS Profile, and In-silico properties of Bioactive Compounds in Methanolic Leaf Extracts of Moringa oleifera. Journal of Drug Delivery and Therapeutics. 2022 Mar 15; 12(2):87-99. https://doi.org/10.22270/jddt.v12i2.5250
Mabkhot YN, Alatibi F, El-Sayed NN, Al-Showiman S, Kheder NA, Wadood A, Rauf A, Bawazeer S, Hadda TB. Antimicrobial activity of some novel armed thiophene derivatives and petra/osiris/molinspiration (POM) analyses. Molecules. 2016; 21(2):222. https://doi.org/10.3390/molecules21020222
Beetge E, du Plessis J, Müller DG, Goosen C, van Rensburg FJ. The influence of the physicochemical characteristics and pharmacokinetic properties of selected NSAID's on their transdermal absorption. International journal of Pharmaceutics. 2000; 193(2):261-4. https://doi.org/10.1016/S0378-5173(99)00340-3
Hauser AS, Attwood MM, Rask-Andersen M, Schiöth HB, Gloriam DE. Trends in GPCR drug discovery: new agents, targets and indications. Nature reviews Drug discovery. 2017; 16(12):829-42. https://doi.org/10.1038/nrd.2017.178
Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific reports. 2017; 7(1):1-3. https://doi.org/10.1038/srep42717
Guan L, Yang H, Cai Y, Sun L, Di P, Li W, Liu G, Tang Y. ADMET-score-a comprehensive scoring function for evaluation of chemical drug-likeness. Medchemcomm. 2019; 10(1):148-57. https://doi.org/10.1039/C8MD00472B
Bose PP, Chatterjee U, Hubatsch I, Artursson P, Govender T, Kruger HG, Bergh M, Johansson J, Arvidsson PI. In vitro ADMET and physicochemical investigations of poly-N-methylated peptides designed to inhibit Aβ aggregation. Bioorganic & medicinal chemistry. 2010; 18(16):5896-902. https://doi.org/10.1016/j.bmc.2010.06.087
Radchenko EV, Dyabina AS, Palyulin VA, Zefirov NS. Prediction of human intestinal absorption of drug compounds. Russian Chemical Bulletin. 2016; 65(2):576-80. https://doi.org/10.1007/s11172-016-1340-0
Alam A, Kowal J, Broude E, Roninson I, Locher KP. Structural insight into substrate and inhibitor discrimination by human P-glycoprotein. Science. 2019; 363(6428):753-6. https://doi.org/10.1126/science.aav7102
Daina A, Zoete V. A boiled‐egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem. 2016; 11(11):1117-21. https://doi.org/10.1002/cmdc.201600182
Liao M, Jaw-Tsai S, Beltman J, Simmons AD, Harding TC, Xiao JJ. Evaluation of in vitro absorption, distribution, metabolism, and excretion and assessment of drug-drug interaction of rucaparib, an orally potent poly (ADP-ribose) polymerase inhibitor. Xenobiotica. 2020; 50(9):1032-42. https://doi.org/10.1080/00498254.2020.1737759
Cheng F, Li W, Zhou Y, Shen J, Wu Z, Liu G, Lee PW, Tang Y. admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. 2012; 3099-3105. https://doi.org/10.1021/ci300367a
Schyman, P., R. Liu, V. Desai, and A. Wallqvist. vNN web server for ADMET predictions. Frontiers in Pharmacology. 2017 December 4; 8:889. https://doi.org/10.3389/fphar.2017.00889
Liu, R., G. Tawa, and A. Wallqvist. Locally weighted learning methods for predicting dose-dependent toxicity with application to the human maximum recommended daily dose. Chemical Research in Toxicology. 2012; 25(10):2216-2226. https://doi.org/10.1021/tx300279f
Liu, R., and A. Wallqvist. Merging applicability domains for in silico assessment of chemical mutagenicity. Journal of Chemical Information and Modeling. 2014; 54(3):793-800. https://doi.org/10.1021/ci500016v
Liu, R., P. Schyman, and A. Wallqvist. Critically assessing the predictive power of QSAR models for human liver microsomal stability. Journal of Chemical Information and Modeling. 2015; 55(8):1566-1575. https://doi.org/10.1021/acs.jcim.5b00255
Schyman, P., R. Liu, and A. Wallqvist. Using the variable-nearest neighbor method to identify P-glycoprotein substrates and inhibitors. ACS Omega. 2016; 1(5):923-929. https://doi.org/10.1021/acsomega.6b00247
Muehlbacher, M., G. Spitzer, K. Liedl, J. Kornhuber. Qualitative prediction of blood-brain barrier permeability on a large and refined dataset. Journal of Computer-Aided Molecular Design. 2011; 25:1095. https://doi.org/10.1007/s10822-011-9478-1
Naef R. A generally applicable computer algorithm based on the group additivity method for the calculation of seven molecular descriptors: heat of combustion, logPO/W, logS, refractivity, polarizability, toxicity and logBB of organic compounds; scope and limits of applicability. Molecules. 2015; 20(10):18279-18351 https://doi.org/10.3390/molecules201018279
Xu, Y., Z. Dai, F. Chen, S. Gao, J. Pei, and L. Lai. Deep learning for drug-induced liver injury. 2015, 55 (10):2085-2093. https://doi.org/10.1021/acs.jcim.5b00238
Golshan Tafti A, Solaimani Dahdivan N, Yasini Ardakani SA. Physicochemical properties and applications of date seed and its oil. International Food Research Journal. 2017 Aug 1; 24(4).
Thakkar S, Chen M, Fang H, Liu Z, Roberts R, Tong W. The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury. Expert review of gastroenterology & hepatology. 2018 Jan 2; 12(1):31-8. https://doi.org/10.1080/17474124.2018.1383154
Yoshitomi S, Ikemoto K, Takahashi J, Miki H, Namba M, Asahi S. Establishment of the transformants expressing human cytochrome P450 subtypes in HepG2, and their applications on drug metabolism and toxicology. Toxicology in Vitro. 2001 Jun 1; 15(3):245-56. https://doi.org/10.1016/S0887-2333(01)00011-X
Lee PH, Cucurull-Sanchez L, Lu J, Du YJ. Development of in silico models for human liver microsomal stability. Journal of computer-aided molecular design. 2007; 21(12):665-73. https://doi.org/10.1007/s10822-007-9124-0
Pelkonen O, Turpeinen M, Hakkola J, Honkakoski P, Hukkanen J, Raunio H. Inhibition and induction of human cytochrome P450 enzymes: current status. Archives of toxicology. 2008; 82(10):667-715. https://doi.org/10.1007/s00204-008-0332-8
Nazar S, Jeyaseelan M, Jayakumararaj R. Local Health Traditions, Cultural Reflections and Ethno-taxonomical Information on Wild Edible Fruit Yielding Medicinal Plants in Melur Region of Madurai District, TamilNadu, India. Journal of Drug Delivery and Therapeutics. 2022; 12(3):138-57. https://doi.org/10.22270/jddt.v12i3.5405
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