Insilico molecular docking and ADME/T studies of flavonol compounds against selected proteins involved in inflammation mechanism

Narendra Pentu; Ajitha  Azhakesan; Pasupuleti Kishore Kumar

doi:10.69857/joapr.v13i1.706

Authors

Narendra Pentu Department of Pharmaceutics, CMR College of Pharmacy, Hyderabad, India https://orcid.org/0000-0001-6255-9254
Ajitha Azhakesan Department of Pharmaceutical Chemistry, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India https://orcid.org/0000-0003-0270-2842
Pasupuleti Kishore Kumar Department of Pharmacology, CMR College of Pharmacy, Hyderabad, India

DOI:

https://doi.org/10.69857/joapr.v13i1.706

Keywords:

Insilico study, Inflammation, Flavonols, Molecular docking, ADME/T, pkCSM

Abstract

Background: Using computational tools in drug discovery advanced the research in identifying new drug candidates for the benefit of the pharmaceutical industry and assessing the safety and pharmacokinetic profiles of phytochemicals. Understanding the inflammatory mechanism is not possible, but inflammatory signal transduction by cytokines can be mitigated by using the flavonoid class of drugs like flavonols. Methodology: A molecular docking study of flavonol compounds with proteins linked with inflammation was carried out using the AutodockVina program. SwissADME and pkCSM modules were used to assess the pharmacokinetic features of plant products. Compared to commercially available NSAIDs, flavonols had more excellent molecular docking scores. Results: Calculation of ADME features of flavonols with no carcinogenicity and low oral acute toxicity level. Compared to anti-inflammatory medicines, the Rutin docking score against COX-I (-8.7 kcal/mol) and the Galangin docking score against COX-II enzymes (-9.4 kcal/mol) had higher values. Discussion: Molecular docking studies exhibited the highest docking score for COX-I is Rutin -8.7 Kcal/mol and hydrogen bond with THR-89, PRO-84, LS-468, GLY-471, PHE-470. The highest docking for COX-II is Galangin -9.4 Kcal/mol and hydrogen bonding with VAL-349 and TYR-385. ADME/T studies were performed for all the flavonols. Rutin has the highest violations in drug-likeliness studies. Conclusion: Flavonols may be more effective anti-inflammatory medicines than commercial medications. By modifying the pharmacokinetic features of plant products through diverse formulation strategies, we can get these phytochemicals to their target sites with fewer adverse effects.

Downloads

Download data is not yet available.

References

Deng Z, Liu S. Inflammation-responsive delivery systems for the treatment of chronic inflammatory diseases. Drug Deliv Transl Res, 11, 1475–97 (2021) https://doi.org/10.1007/s13346-021-00977-8.

Stupin V, Manturova N, Silina E, Litvitskiy P, Vasin V, Artyushkova E, Ivanov A, Gladchenko M, Aliev S. The effect of inflammation on the healing process of acute skin wounds under the treatment of wounds with injections in rats. J Exp Pharmacol, 12, 409–22 (2020) https://doi.org/10.2147/JEP.S275791.

de Groot DJA, de Vries EGE, Groen HJM, de Jong S. Non-steroidal anti-inflammatory drugs to potentiate chemotherapy effects: From lab to clinic, Critical reviews in oncology/hematology, 52-69, (2007). https://doi.org/10.1016/j.critrevonc.2006.07.001.

Sohail R, Mathew M, Patel KK, Reddy SA, Haider Z, Naria M, Habib A, Abdin ZU, Razzaq Chaudhry W, Akbar A. Effects of Non-steroidal Anti-inflammatory Drugs (NSAIDs) and Gastroprotective NSAIDs on the Gastrointestinal Tract: A Narrative Review. Cureus, (2023) https://doi.org/10.7759/cureus.37080.

Ferrfindiz ML, Alcaraz MJ. Anti-inflammatory activity and inhibition of arachidonic acid metabolism by flavonoids, Agents and Actions 32, 283–288 (1991), https://doi.org/10.1007/BF01980887

Lee SY, Cho SS, Li YC, Bae CS, Park KM, Park DH. Anti-inflammatory Effect of Curcuma longa and Allium hookeri Co-treatment via NF-κB and COX-2 Pathways. Sci Rep, 10, (2020) https://doi.org/10.1038/s41598-020-62749-7.

Ju Z, Li M, Xu J, Howell DC, Li Z, Chen F-E. Recent development on COX-2 inhibitors as promising anti-inflammatory agents: The past 10 years. Acta Pharm Sin B, 12, 2790–807 (2022) https://doi.org/10.1016/j.apsb.2022.01.002.

Murkovic M. Phenolic Compounds: Occurrence, Classes, and Analysis. Encyclopedia of Food and Health. Elsevier Inc., pp. 346–51 (2015), https://doi.org/10.1016/B978-0-12-384947-2.00539-0.

Ververidis F, Trantas E, Douglas C, Vollmer G, Kretzschmar G, Panopoulos N. Biotechnology of flavonoids and other phenylpropanoid‐derived natural products. Part I: Chemical diversity, impacts on plant biology and human health. Biotechnology Journal: Healthcare Nutrition Technology, 2(10):1214-34, (2007), https://doi.org/10.1002/biot.200700084.

Woodman OL, Chan EC. Vascular and anti‐oxidant actions of flavonols and flavones. Clinical and Experimental Pharmacology and Physiology. 31(11):786-90, (2004), https://doi.org/10.1111/j.1440-1681.2004.04072.x.

Di Majo D, La Guardia M, Leto G, Crescimanno M, Flandina C, Giammanco M. Flavonols and flavan-3-ols as modulators of xanthine oxidase and manganese superoxide dismutase activity. Int J Food Sci Nutr, 65, 886–92 (2014) https://doi.org/10.3109/09637486.2014.931362.

Ahmad F, Misra L, Tewari R, Gupta P, Mishra P, Shukla R. Anti-inflammatory flavanol glycosides from Saraca asoca bark. Nat Prod Res, 30, 489–92 (2016) https://doi.org/10.1080/14786419.2015.1023728.

Kopustinskiene DM, Jakstas V, Savickas A, Bernatoniene J. Flavonoids as anticancer agents. Nutrients.12(2):457, (2010), https://doi.org/10.3390/nu12020457.

Liu HL, Jiang WB, Xie MX. Flavonoids: recent advances as anticancer drugs. Recent patents on anti-cancer drug discovery. 5(2):152-64, (2010), https://doi.org/10.2174/157489210790936261.

Bisol Â, de Campos PS, Lamers ML. Flavonoids as anticancer therapies: A systematic review of clinical trials. phytotherapy Research, 34(3):568-82, (2020), https://doi.org/10.1002/ptr.6551.

Kim HH, Kim DH, Kim MH, Oh MH, Kim SR, Park KJ, Lee MW. Flavonoid constituents in the leaves of Myrica rubra sieb. et zucc. with anti-inflammatory activity. Arch Pharm Res, 36, 1533–40 (2013) https://doi.org/10.1007/s12272-013-0147-x.

Trott O, Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem, NA-NA (2009) https://doi.org/10.1002/jcc.21334.

Du X, Li Y, Xia Y-L, Ai S-M, Liang J, Sang P, Ji X-L, Liu S-Q. Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods. Int J Mol Sci, 17, 144 (2016) https://doi.org/10.3390/ijms17020144.

Hasan MM, Khan Z, Chowdhury MS, Khan MA, Moni MA, Rahman MH. In silico molecular docking and ADME/T analysis of Quercetin compound with its evaluation of broad-spectrum therapeutic potential against particular diseases. Inform Med Unlocked, 29, 100894 (2022) https://doi.org/10.1016/j.imu.2022.100894.

Divyashri G, Murthy TPK, Sundareshan S, Kamath P, Murahari M, Saraswathy GR, Sadanandan B. In silico approach towards the identification of potential inhibitors from Curcuma amada Roxb against H. pylori: ADMET screening and molecular docking studies. BioImpacts, 11, 119–27 (2021) https://doi.org/10.34172/BI.2021.19.

Wu T, He M, Zang X, Zhou Y, Qiu T, Pan S, Xu X. A structure-activity relationship study of flavonoids as inhibitors of E. coli by membrane interaction effect. Biochim Biophys Acta Biomembr, 1828, 2751–6 (2013) https://doi.org/10.1016/j.bbamem.2013.07.029.

Pentu N, Rishitha P, Nikhil G, Rao TR. Therapeutic potential of flavonoids in the management of psoriasis. Asian J Pharm Pharmacol, 10, 35–45 (2024) https://doi.org/10.31024/ajpp.2024.10.1.2.

Khare S, Chatterjee T, Gupta S, Ashish P. Bioavailability predictions, pharmacokinetics and drug-likeness of bioactive compounds from Andrographis paniculata using Swiss ADME. MGM Journal of Medical Sciences, 10, 651–9 (2023) https://doi.org/10.4103/mgmj.mgmj_245_23.

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, 7, (2017) https://doi.org/10.1038/srep42717.

Ayar A, Aksahin M, Mesci S, Yazgan B, Gül M, Yıldırım T. Antioxidant, Cytotoxic Activity and Pharmacokinetic Studies by Swiss Adme, Molinspiration, Osiris and DFT of PhTAD-substituted Dihydropyrrole Derivatives. Curr Comput Aided Drug Des, 18, 52–63 (2022) https://doi.org/10.2174/1573409917666210223105722.

Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced drug delivery reviews, 23(1-3):3-25, (1997), https://doi.org/10.1016/S0169-409X(96)00423-1.

Azzam K AL. SwissADME and pkCSM Webservers Predictors: an integrated Online Platform for Accurate and Comprehensive Predictions for In Silico ADME/T Properties of Artemisinin and its Derivatives. Kompleksnoe Ispolʹzovanie Mineralʹnogo syrʹâ/Complex Use of Mineral Resources/Mineraldik Shikisattardy Keshendi Paidalanu, 325, 14–21 (2023) https://doi.org/10.31643/2023/6445.13.

Pires DEV, Blundell TL, Ascher DB. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J Med Chem, 58, 4066–72 (2015) https://doi.org/10.1021/acs.jmedchem.5b00104.

Yeni Y, Rachmania RA. The Prediction of Pharmacokinetic Properties of Compounds in Hemigraphis alternata (Burm.F.) T. Ander Leaves Using pkCSM. Indonesian Journal of Chemistry, 22, 1081–9 (2022) https://doi.org/10.22146/ijc.73117.

Di Muzio E, Toti D, Polticelli F. DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina. J Comput Aided Mol Des, 31, 213–8 (2017) https://doi.org/10.1007/s10822-016-0006-1.

Trott O, Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem, 31, 455–61 (2010) https://doi.org/10.1002/jcc.21334.

Seeliger D, De Groot BL. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des, 24, 417–22 (2010) https://doi.org/10.1007/s10822-010-9352-6.

Shaikh GM, Murahari M, Thakur S, Kumar MS, YC M. Studies on ligand-based pharmacophore modeling approach in identifying potent future EGFR inhibitors. J Mol Graph Model, 112, (2022) https://doi.org/10.1016/j.jmgm.2021.108114.

Sakyi PO, Broni E, Amewu RK, Miller WA, Wilson MD, Kwofie SK. Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase. Front Cell Infect Microbiol, 12, (2022) https://doi.org/10.3389/fcimb.2022.859981.

Hasan MM, Khan Z, Chowdhury MS, Khan MA, Moni MA, Rahman MH. In silico molecular docking and ADME/T analysis of Quercetin compound with its evaluation of broad-spectrum therapeutic potential against particular diseases. Inform Med Unlocked, 29, (2022) https://doi.org/10.1016/j.imu.2022.100894.

Singh SP, Konwar BK. Molecular docking studies of quercetin and its analogues against human inducible nitric oxide synthase. SpringerPlus. 1:1-0, (2021), https://doi.org/10.1186/2193-1801-1-69.

Al Azzam KM. SwissADME and pkCSM Webservers Predictors: an integrated Online Platform for Accurate and Comprehensive Predictions for In Silico ADME/T Properties of Artemisinin and its Derivatives. Complex Use of Mineral Resources, 325, 14–21 (2023) https://doi.org/10.31643/2023/6445.13.

Khare S, Chatterjee T, Gupta S, Ashish P. Bioavailability predictions, pharmacokinetics and drug-likeness of bioactive compounds from Andrographis paniculata using Swiss ADME. MGM Journal of Medical Sciences, 10, 651–9 (2023) https://doi.org/10.4103/mgmj.mgmj_245_23.

Pires DEV, Kaminskas LM, Ascher DB. Prediction and optimization of pharmacokinetic and toxicity properties of the ligand. Methods in Molecular Biology. Vol. 1762, Humana Press Inc., pp. 271–84 (2018), https://doi.org/10.1007/978-1-4939-7756-7_14.

Raschi E, Ceccarini L, De Ponti F, Recanatini M. hERG-related drug toxicity and models for predicting hERG liability and QT prolongation. Expert Opin Drug Metab Toxicol, 5, 1005–21 (2009) https://doi.org/10.1517/17425250903055070.

Ha H, Lee S, Kim D-H, Seo C-S, Shin H. hERG Channel-Related Cardiotoxicity Assessment of 13 Herbal Medicines. Journal of Korean Medicine, 42, 44–55 (2021) https://doi.org/10.13048/jkm.21024.