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Alzheimer Hastalığı için Potansiyel Çok Hedefli Terapötikler Olarak Stilbenlerin Hesaplamalı Analizi

Year 2025, Volume: 8 Issue: 1, 145 - 166, 17.01.2025
https://doi.org/10.47495/okufbed.1466868

Abstract

Amaç: Bu çalışmanın amacı, 13 stilben ve Alzheimer hastalığı (AH)’nın tedavisinde kullanılan 5 Amerikan Gıda ve İlaç Dairesi onaylı ilacın ADME tahmini ve moleküler yerleştirme yöntemi ile karşılaştırılmasıdır. AD patolojisinde yer alan kolinerjik, amiloid, tau, oksidatif stres ve inflamasyon hipotezleri, moleküler yerleştirmede hedeflenmiştir. Gereç ve Yöntemler: SwissADME, stilbenlerin (resveratrol, pterostilben, oksiresveratrol, pikeatannol, pinosilvin, isorhapontigenin, isorhapontin, astringin, piceid (polidatin) ve mulberroside A) ve Amerikan Gıda ve İlaç Dairesi onaylı ilaçların (takrin, donepezil, rivastigmin, galantamin ve memantin) fizikokimyasal, lipofiliklik, suda çözünürlük, farmakokinetik, ilaca benzerlik ve tıbbi kimya özelliklerini belirlemek için kullanılmıştır. CBDOCK2, stilbenlerin ve Amerikan Gıda ve İlaç Dairesi onaylı ilaçların hedef proteinlere (AChE, BuChE, APP, BACE, GSK-3β, CDK5, SOD, CAT, GPx, Cox-2, iNOS, IL-1β ve TNF-α) bağlanma afinitesini belirlemek için kullanılmıştır. Bulgular: SWISS ADME sonuçları stilbenlerin AD tedavisinde doğal ürünler olarak kullanılabileceğini göstermiştir. Moleküler yerleştirme sonuçları, mulberroside A’nın en iyi vina skorunu (kcal/mol) gösterdiğini ve ardından astringin, piceid (polidatin), isorhapontin, donepezil, oxyresveratrol, piceatannol, galantamin, resveratrol, isorhapontigenin, takrin, pinosilvin, pterostilben, rivastigmin ve memantin’in geldiği gösterilmiştir. Sonuç: Çalışmamızda AH tedavisinde stilbenler ve Amerikan Gıda ve İlaç Dairesi onaylı ilaçlar hesaplamalı yaklaşımlar kullanılarak değerlendirilmiştir. Sonuçlar, AD patolojisinin çeşitli hipotezleri üzerindeki potansiyel terapötik etkilerini vurgulamıştır. Bu bulguların klinik uygulamalarda doğrulanması için daha fazla araştırmaya ihtiyaç vardır.

References

  • Akhoon BA., Tiwari H., Nargotra A. In silico drug design methods for drug repurposing. In: In Silico Drug Design. Cambridge, Academic Press 2019; 47-84.
  • Aleynova OA., Ogneva ZV., Suprun AR., Ananev AA., Nityagovsky NN., Beresh AA., Dubrovina AS., Kiselev KV. The effect of external treatment of arabidopsis thaliana with plant-derived stilbene compounds on plant resistance to abiotic stresses. Plants 2024; 13(2): 184.
  • Balakrishnan R., Jannat K., Choi DK. Development of dietary small molecules as multi-targeting treatment strategies for Alzheimer's disease. Redox Biol. 2024; 103105.
  • Boateng ST., Roy T., Agbo ME., Mahmud MA., Banang-Mbeumi S., Chamcheu RCN., Yadav RK., Pham LK., Dang DD., Jackson KE, Nagalo BM, Efimova T., Fotie J., Chamcheu JC. Multifaceted approach toward mapping out the anticancer properties of small molecules via in vitro evaluation on melanoma and nonmelanoma skin cancer cells, and in silico target fishing. Chem. Biol. Drug Des. 2024; 103(1).
  • Boobier S., Hose DRJ., Blacker A., Nguyen B. Machine learning with physicochemical relationships: solubility prediction in organic solvents and water. Nature Communications 2020; 11: 521.
  • Boyles F. Developing novel scoring functions for protein-ligand docking using machine learning. Doctoral Dissertation, University of Oxford 2020.
  • Buchwald P., Bodor N. Octanol-water partition: Searching for predictive models. Curr. Med. Chem. 1998; 5(5): 353-380.
  • Cao W., Zheng B., Zeng X., He H., Chen L. Stilbene, as phyto-oestrogens, can construct resistant starch through noncovalent interactions with starch: A structural correlation study. Food Hydrocoll. 2024; 148: 109438.
  • Chai TT., Wong CCC., Sabri MZ., Wong FC. Seafood paramyosins as sources of anti-angiotensin-converting-enzyme and anti-dipeptidyl-peptidase peptides after gastrointestinal digestion: A cheminformatic investigation. Molecules 2022; 27(12): 3864.
  • Ciorsac A., Filip M., Isvoran A. Predict of water solubility of the low molecular weigh oligomers of polyhydroxyalkanoates. New Front. Chem. 2021; 30(1): 25-34.
  • Daina A., Michielin O., Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Rep. 2017; 7(1): 42717.
  • Daina A., Zoete V. A boiled-egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem 2016; 11(11): 1117-1121.
  • Ertl P., Schuffenhauer A. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. J. Cheminform. 2009; 1: 1-11.
  • Ganz T., Ben-Hur T. The “hit and run” hypothesis for Alzheimer’s disease pathogenesis. Int. J. Mol. Sci. 2024; 25(6): 3245.
  • Goodnow Jr RA. Current practices in generation of small molecule new leads. J. Cell. Biochem. 2001; 84(S37): 13-21.
  • Gupta PP., Bastikar VA., Bastikar A., Chhajed SS., Pathade PA. Computational screening techniques for Lead design and development. CADD 2020; 187-222.
  • Hakkola J., Hukkanen J., Turpeinen M., Pelkonen O. Inhibition and induction of CYP enzymes in humans: an update. Arch. Toxicol. 2020; 94(11): 3671-3722.
  • Henning N., Kannigadu C., Aucamp J., van Rensburg HDJ., David DD. Probing benzothiadiazine-1, 1-dioxide ethylene glycol derivatives against Leishmania: synthesis and in vitro efficacy evaluation. Res Sq. 2023; PPR664243.
  • Ibrahim MT., Uzairu A., Uba S., Shallangwa GA. Computational modeling of novel quinazoline derivatives as potent epidermal growth factor receptor inhibitors. Heliyon 2020; 6(2).
  • Jia CY., Li JY., Hao GF., Yang GF. A drug-likeness toolbox facilitates ADMET study in drug discovery. Drug Discov. Today 2020; 25(1): 248-258.
  • Jose S., Devi SS., Sajeev A., Girisa S., Alqahtani MS., Abbas M., et al. Repurposing FDA-approved drugs as FXR agonists: a structure based in silico pharmacological study. Biosci. Rep. 2023; 43(3).
  • Kadri A., Aouadi K. In vitro antimicrobial and α-glucosidase inhibitory potential of enantiopure cycloalkylglycine derivatives: Insights into their in silico pharmacokinetic, druglikeness, and medicinal chemistry properties. Journal of Applied Pharmaceutical Science 2020; 10(6): 107-115.
  • Kamble SM., Patil KR., Upaganlawar AB. Etiology, pathogenesis of Alzheimer's disease and amyloid beta hypothesis. In: Alzheimer's Disease and Advanced Drug Delivery Strategies. Cambridge, Academic Press 2024; 1-11.
  • Liao M., Jaw-Tsai S., Beltman J., Simmons A., Harding T., 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: 1032-1042.
  • Liu N., Liang X., Chen Y., Xie L. Recent trends in treatment strategies for Alzheimer's disease and the challenges: A topical advancement. Ageing Res. Rev. 2024; 102199.
  • 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).
  • Meli R., Morris GM., Biggin PC. Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: A review. Front. Bioinform. 2022; 2: 885983.
  • Mishra S., Dahima R. In vitro ADME studies of TUG-891, a GPR-120 inhibitor using SWISS ADME predictor. JDDT 2019; 9(2-s): 366-369.
  • Moharana M., Pattanayak SK., Khan F. Molecular recognition of bio-active triterpenoids from Swertia chirayita towards hepatitis Delta antigen: a mechanism through docking, dynamics simulation, Gibbs free energy landscape. J. Biomol. Struct. Dyn. 2023; 41(24).
  • Nasb M., Tao W., Chen N. Alzheimer's disease puzzle: Delving into pathogenesis hypotheses. Aging Dis. 2024; 15(1): 43-73.
  • Ndombera F., Maiyoh G., Tuei V. Pharmacokinetic, physicochemical and medicinal properties of n-glycoside anti-cancer agent more potent than 2-deoxy-d-glucose in lung cancer cells. J. Pharm. Pharmacol. 2019; 7(4): 165-176.
  • Ozioko PC., Gaiya DD., Abdullahi I. Essential secondary metabolites of Azadirachta indica leaf in search of drug for COVID-19 treatment: In-silico ADMET and bioactivity predictions. Int. J. Adv. Res. Biol. Sci. 2023; 10(9): 79-93.
  • Perluigi M., Di Domenico F., Butterfield DA. Oxidative damage in neurodegeneration: Roles in the pathogenesis and progression of Alzheimer disease. Physiol. Rev. 2024; 104(1): 103-197.
  • Poltronieri P., Xu B., & Giovinazzo G. Resveratrol and other stilbenes: effects on dysregulated gene expression in cancers and novel delivery systems. Anti-Cancer Agents in Medicinal Chemistry 2020.
  • Ponzoni I., Sebastián-Pérez V., Requena-Triguero C., Roca C., Martínez MJ., Cravero F., Diaz MF., Paez JA., Arrayas RG., Adrio J., Campillo NE. Hybridizing feature selection and feature learning approaches in QSAR modeling for drug discovery. Sci. Rep. 2017; 7(1): 2403.
  • Rafeeq MM., Helmi N., Sain ZM., Iqbal J., Alzahrani A., Alkurbi MO., Shater AF., Al-ahmadi BM., Alam MZ., Alam Q. Target-based virtual screening and molecular dynamics approach to identify potential antileishmanial agents through targeting UvrD-like helicase ATP-binding domain. Adv. Life Sci 2024; 11(1): 237-245.
  • Ranjith D., Padhi PK., Dhaval JK., Karikalan M., Naveena M., Johnson BE., Telang AG. Insilco prediction and hematological alterations in male rats exposed to Ethion and its amelioration by nano-quercetin: A sub chronic study. J. Pharm. Innov. 2022; 11(11): 1116-1122.
  • Ranjith D., Ravikumar C. SwissADME predictions of pharmacokinetics and drug-likeness properties of small molecules present in Ipomoea mauritiana Jacq. J Pharmacogn Phytochem 2019; 8(5): 2063-2073.
  • Sardar H. Drug like potential of Daidzein using SwissADME prediction: In silico Approaches. PHYTONutrients 2023; 02-08.
  • Sert M., Işılar Ö., Yaglioglu AS., Bulut A. Gabriel-Cromwell aziridination of amino sugars; chiral ferrocenoyl-aziridinyl sugar synthesis and their biological evaluation. Carbohydr. Res. 2021; 509: 108430.
  • Shevelyova MP., Deryusheva EI., Nemashkalova EL., Machulin AV., Litus EA. Role of human serum albumin in the prevention and treatment of Alzheimer’s disease. Biol. Bull. Rev. 2024; 14(1): 29-42.
  • Soares A., Sousa G., Calil R., & Trossini G. Absorption matters: A closer look at popular oral bioavailability rules for drug approvals. Molecular Informatics 2023; 42.
  • Socała K., Żmudzka E., Lustyk K., Zagaja M., Brighenti V., Costa AM., Andres-Mach M., Pytka K., Martinelli I., Mandrioli J., Pellati F., Biagini G., Wlaz P. Therapeutic potential of stilbenes in neuropsychiatric and neurological disorders: A comprehensive review of preclinical and clinical evidence. Phytother. Res. 2024; 38(3): 1400-1461.
  • Udugade SB., Doijad RC., Udugade BV. In silico evaluation of pharmacokinetics, drug-likeness and medicinal chemistry friendliness of momordicin1: An active chemical constituent of momordica charantia. J. Adv. Sci. Res. 2019; 10(03 Suppl 1): 222-229.
  • Vejandla B., Savani S., Appalaneni R., Veeravalli RS., Gude SS. Alzheimer’s disease: The past, present, and future of a globally progressive disease. Cureus 2024; 16(1).
  • Wolfe MS. γ-Secretase: once and future drug target for Alzheimer’s disease. Expert Opin. Drug Discov. 2024; 19(1): 5-8.
  • Yadav AR., Mohite SK. ADME analysis of phytochemical constituents of Psidium guajava. Asian J. Sci. Res. 2020; 13(5): 373-375.
  • Yağlıoğlu AŞ., Gürbüz DG., Dölarslan M., Demirtaş İ. First determination of anticancer, cytotoxic, and in silico ADME evaluation of secondary metabolites of endemic Astragalus leucothrix Freyn & Bornm. Turk. J. Chem. 2022; 46(1); 169-183.
  • Yajing M., Sufang L., Qingfeng Z., Zhonghua L., Zhijian Z., Bin Y. Approved drugs and natural products at clinical stages for treating Alzheimer’s disease. Chin J Nat Med 2024; 22(0): 1-12.
  • Yan QW., Su BJ., He S., Liao HB., Wang HS., Liang D. Structurally diverse stilbenes from Gnetum parvifolium and their anti-neuroinflammatory activities. Bioorg. Chem. 2024; 143: 107060.
  • Yoshitomo A., Asano S., Hozuki S., Tamemoto Y., Shibata Y., Hashimoto N., Takahashi K., Sasaki Y., Ozawa N., Kageyama M., Iijima T., Kazuki Y., Sato H. Significance of basal membrane permeability of epithelial cells in predicting ıntestinal drug absorption. Drug Metabolism and Disposition 2022; 51: 318-328.

Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease

Year 2025, Volume: 8 Issue: 1, 145 - 166, 17.01.2025
https://doi.org/10.47495/okufbed.1466868

Abstract

Purpose: The aim of this study is to compare 13 stilbenes and 5 FDA-approved drugs used in the treatment of Alzheimer’s disease (AD) by ADME prediction and molecular docking method. Cholinergic, amyloid, tau, oxidative stress and inflammation hypotheses involved in AD pathology were targeted in molecular docking. Materials and Methods: SwissADME has been used to determine the physicochemical, lipophilicity, water solubility, pharmacokinetics, drug-likeness and medicinal chemistry properties of stilbenes (resveratrol, pterostilbene, oxyresveratrol, piceatannol, pinosylvin, isorhapontigenin, isorhapontin, astringin, piceid (polydatin), and mulberroside A) and FDA-approved drugs (tacrine, donepezil, rivastigmine, galantamine, and memantine). CBDOCK2 has been used to determine the binding affinity stilbenes and FDA-approved drugs to target proteins (AChE, BuChE, APP, BACE, GSK-3β, CDK5, SOD, CAT, GPx, Cox-2, iNOS, IL-1β, and TNF-α). Results: SWISS ADME results showed that stilbenes could be used as natural products in the treatment of AD. The molecular docking results indicated that mulberroside A showed the best vina score (kcal/mol) followed by astringin, piceid (polydatin), isorhapontin, donepezil, oxyresveratrol, piceatannol, galanthamine, resveratrol, isorhapontigenin, tacrine, pinosylvin, pterostilbene, rivastigmine, and memantine. Conclusion: Our study evaluated stilbenes and FDA-approved drugs for the treatment of AD using computational approaches. The results highlight its potential therapeutic effects on various hypotheses of AD pathology. More research is needed to validate these findings for clinical practice.

References

  • Akhoon BA., Tiwari H., Nargotra A. In silico drug design methods for drug repurposing. In: In Silico Drug Design. Cambridge, Academic Press 2019; 47-84.
  • Aleynova OA., Ogneva ZV., Suprun AR., Ananev AA., Nityagovsky NN., Beresh AA., Dubrovina AS., Kiselev KV. The effect of external treatment of arabidopsis thaliana with plant-derived stilbene compounds on plant resistance to abiotic stresses. Plants 2024; 13(2): 184.
  • Balakrishnan R., Jannat K., Choi DK. Development of dietary small molecules as multi-targeting treatment strategies for Alzheimer's disease. Redox Biol. 2024; 103105.
  • Boateng ST., Roy T., Agbo ME., Mahmud MA., Banang-Mbeumi S., Chamcheu RCN., Yadav RK., Pham LK., Dang DD., Jackson KE, Nagalo BM, Efimova T., Fotie J., Chamcheu JC. Multifaceted approach toward mapping out the anticancer properties of small molecules via in vitro evaluation on melanoma and nonmelanoma skin cancer cells, and in silico target fishing. Chem. Biol. Drug Des. 2024; 103(1).
  • Boobier S., Hose DRJ., Blacker A., Nguyen B. Machine learning with physicochemical relationships: solubility prediction in organic solvents and water. Nature Communications 2020; 11: 521.
  • Boyles F. Developing novel scoring functions for protein-ligand docking using machine learning. Doctoral Dissertation, University of Oxford 2020.
  • Buchwald P., Bodor N. Octanol-water partition: Searching for predictive models. Curr. Med. Chem. 1998; 5(5): 353-380.
  • Cao W., Zheng B., Zeng X., He H., Chen L. Stilbene, as phyto-oestrogens, can construct resistant starch through noncovalent interactions with starch: A structural correlation study. Food Hydrocoll. 2024; 148: 109438.
  • Chai TT., Wong CCC., Sabri MZ., Wong FC. Seafood paramyosins as sources of anti-angiotensin-converting-enzyme and anti-dipeptidyl-peptidase peptides after gastrointestinal digestion: A cheminformatic investigation. Molecules 2022; 27(12): 3864.
  • Ciorsac A., Filip M., Isvoran A. Predict of water solubility of the low molecular weigh oligomers of polyhydroxyalkanoates. New Front. Chem. 2021; 30(1): 25-34.
  • Daina A., Michielin O., Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Rep. 2017; 7(1): 42717.
  • Daina A., Zoete V. A boiled-egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem 2016; 11(11): 1117-1121.
  • Ertl P., Schuffenhauer A. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. J. Cheminform. 2009; 1: 1-11.
  • Ganz T., Ben-Hur T. The “hit and run” hypothesis for Alzheimer’s disease pathogenesis. Int. J. Mol. Sci. 2024; 25(6): 3245.
  • Goodnow Jr RA. Current practices in generation of small molecule new leads. J. Cell. Biochem. 2001; 84(S37): 13-21.
  • Gupta PP., Bastikar VA., Bastikar A., Chhajed SS., Pathade PA. Computational screening techniques for Lead design and development. CADD 2020; 187-222.
  • Hakkola J., Hukkanen J., Turpeinen M., Pelkonen O. Inhibition and induction of CYP enzymes in humans: an update. Arch. Toxicol. 2020; 94(11): 3671-3722.
  • Henning N., Kannigadu C., Aucamp J., van Rensburg HDJ., David DD. Probing benzothiadiazine-1, 1-dioxide ethylene glycol derivatives against Leishmania: synthesis and in vitro efficacy evaluation. Res Sq. 2023; PPR664243.
  • Ibrahim MT., Uzairu A., Uba S., Shallangwa GA. Computational modeling of novel quinazoline derivatives as potent epidermal growth factor receptor inhibitors. Heliyon 2020; 6(2).
  • Jia CY., Li JY., Hao GF., Yang GF. A drug-likeness toolbox facilitates ADMET study in drug discovery. Drug Discov. Today 2020; 25(1): 248-258.
  • Jose S., Devi SS., Sajeev A., Girisa S., Alqahtani MS., Abbas M., et al. Repurposing FDA-approved drugs as FXR agonists: a structure based in silico pharmacological study. Biosci. Rep. 2023; 43(3).
  • Kadri A., Aouadi K. In vitro antimicrobial and α-glucosidase inhibitory potential of enantiopure cycloalkylglycine derivatives: Insights into their in silico pharmacokinetic, druglikeness, and medicinal chemistry properties. Journal of Applied Pharmaceutical Science 2020; 10(6): 107-115.
  • Kamble SM., Patil KR., Upaganlawar AB. Etiology, pathogenesis of Alzheimer's disease and amyloid beta hypothesis. In: Alzheimer's Disease and Advanced Drug Delivery Strategies. Cambridge, Academic Press 2024; 1-11.
  • Liao M., Jaw-Tsai S., Beltman J., Simmons A., Harding T., 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: 1032-1042.
  • Liu N., Liang X., Chen Y., Xie L. Recent trends in treatment strategies for Alzheimer's disease and the challenges: A topical advancement. Ageing Res. Rev. 2024; 102199.
  • 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).
  • Meli R., Morris GM., Biggin PC. Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: A review. Front. Bioinform. 2022; 2: 885983.
  • Mishra S., Dahima R. In vitro ADME studies of TUG-891, a GPR-120 inhibitor using SWISS ADME predictor. JDDT 2019; 9(2-s): 366-369.
  • Moharana M., Pattanayak SK., Khan F. Molecular recognition of bio-active triterpenoids from Swertia chirayita towards hepatitis Delta antigen: a mechanism through docking, dynamics simulation, Gibbs free energy landscape. J. Biomol. Struct. Dyn. 2023; 41(24).
  • Nasb M., Tao W., Chen N. Alzheimer's disease puzzle: Delving into pathogenesis hypotheses. Aging Dis. 2024; 15(1): 43-73.
  • Ndombera F., Maiyoh G., Tuei V. Pharmacokinetic, physicochemical and medicinal properties of n-glycoside anti-cancer agent more potent than 2-deoxy-d-glucose in lung cancer cells. J. Pharm. Pharmacol. 2019; 7(4): 165-176.
  • Ozioko PC., Gaiya DD., Abdullahi I. Essential secondary metabolites of Azadirachta indica leaf in search of drug for COVID-19 treatment: In-silico ADMET and bioactivity predictions. Int. J. Adv. Res. Biol. Sci. 2023; 10(9): 79-93.
  • Perluigi M., Di Domenico F., Butterfield DA. Oxidative damage in neurodegeneration: Roles in the pathogenesis and progression of Alzheimer disease. Physiol. Rev. 2024; 104(1): 103-197.
  • Poltronieri P., Xu B., & Giovinazzo G. Resveratrol and other stilbenes: effects on dysregulated gene expression in cancers and novel delivery systems. Anti-Cancer Agents in Medicinal Chemistry 2020.
  • Ponzoni I., Sebastián-Pérez V., Requena-Triguero C., Roca C., Martínez MJ., Cravero F., Diaz MF., Paez JA., Arrayas RG., Adrio J., Campillo NE. Hybridizing feature selection and feature learning approaches in QSAR modeling for drug discovery. Sci. Rep. 2017; 7(1): 2403.
  • Rafeeq MM., Helmi N., Sain ZM., Iqbal J., Alzahrani A., Alkurbi MO., Shater AF., Al-ahmadi BM., Alam MZ., Alam Q. Target-based virtual screening and molecular dynamics approach to identify potential antileishmanial agents through targeting UvrD-like helicase ATP-binding domain. Adv. Life Sci 2024; 11(1): 237-245.
  • Ranjith D., Padhi PK., Dhaval JK., Karikalan M., Naveena M., Johnson BE., Telang AG. Insilco prediction and hematological alterations in male rats exposed to Ethion and its amelioration by nano-quercetin: A sub chronic study. J. Pharm. Innov. 2022; 11(11): 1116-1122.
  • Ranjith D., Ravikumar C. SwissADME predictions of pharmacokinetics and drug-likeness properties of small molecules present in Ipomoea mauritiana Jacq. J Pharmacogn Phytochem 2019; 8(5): 2063-2073.
  • Sardar H. Drug like potential of Daidzein using SwissADME prediction: In silico Approaches. PHYTONutrients 2023; 02-08.
  • Sert M., Işılar Ö., Yaglioglu AS., Bulut A. Gabriel-Cromwell aziridination of amino sugars; chiral ferrocenoyl-aziridinyl sugar synthesis and their biological evaluation. Carbohydr. Res. 2021; 509: 108430.
  • Shevelyova MP., Deryusheva EI., Nemashkalova EL., Machulin AV., Litus EA. Role of human serum albumin in the prevention and treatment of Alzheimer’s disease. Biol. Bull. Rev. 2024; 14(1): 29-42.
  • Soares A., Sousa G., Calil R., & Trossini G. Absorption matters: A closer look at popular oral bioavailability rules for drug approvals. Molecular Informatics 2023; 42.
  • Socała K., Żmudzka E., Lustyk K., Zagaja M., Brighenti V., Costa AM., Andres-Mach M., Pytka K., Martinelli I., Mandrioli J., Pellati F., Biagini G., Wlaz P. Therapeutic potential of stilbenes in neuropsychiatric and neurological disorders: A comprehensive review of preclinical and clinical evidence. Phytother. Res. 2024; 38(3): 1400-1461.
  • Udugade SB., Doijad RC., Udugade BV. In silico evaluation of pharmacokinetics, drug-likeness and medicinal chemistry friendliness of momordicin1: An active chemical constituent of momordica charantia. J. Adv. Sci. Res. 2019; 10(03 Suppl 1): 222-229.
  • Vejandla B., Savani S., Appalaneni R., Veeravalli RS., Gude SS. Alzheimer’s disease: The past, present, and future of a globally progressive disease. Cureus 2024; 16(1).
  • Wolfe MS. γ-Secretase: once and future drug target for Alzheimer’s disease. Expert Opin. Drug Discov. 2024; 19(1): 5-8.
  • Yadav AR., Mohite SK. ADME analysis of phytochemical constituents of Psidium guajava. Asian J. Sci. Res. 2020; 13(5): 373-375.
  • Yağlıoğlu AŞ., Gürbüz DG., Dölarslan M., Demirtaş İ. First determination of anticancer, cytotoxic, and in silico ADME evaluation of secondary metabolites of endemic Astragalus leucothrix Freyn & Bornm. Turk. J. Chem. 2022; 46(1); 169-183.
  • Yajing M., Sufang L., Qingfeng Z., Zhonghua L., Zhijian Z., Bin Y. Approved drugs and natural products at clinical stages for treating Alzheimer’s disease. Chin J Nat Med 2024; 22(0): 1-12.
  • Yan QW., Su BJ., He S., Liao HB., Wang HS., Liang D. Structurally diverse stilbenes from Gnetum parvifolium and their anti-neuroinflammatory activities. Bioorg. Chem. 2024; 143: 107060.
  • Yoshitomo A., Asano S., Hozuki S., Tamemoto Y., Shibata Y., Hashimoto N., Takahashi K., Sasaki Y., Ozawa N., Kageyama M., Iijima T., Kazuki Y., Sato H. Significance of basal membrane permeability of epithelial cells in predicting ıntestinal drug absorption. Drug Metabolism and Disposition 2022; 51: 318-328.
There are 51 citations in total.

Details

Primary Language English
Subjects Neurogenetics
Journal Section RESEARCH ARTICLES
Authors

Seda Şirin

Early Pub Date January 15, 2025
Publication Date January 17, 2025
Submission Date April 8, 2024
Acceptance Date August 21, 2024
Published in Issue Year 2025 Volume: 8 Issue: 1

Cite

APA Şirin, S. (2025). Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 8(1), 145-166. https://doi.org/10.47495/okufbed.1466868
AMA Şirin S. Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease. Osmaniye Korkut Ata University Journal of The Institute of Science and Techno. January 2025;8(1):145-166. doi:10.47495/okufbed.1466868
Chicago Şirin, Seda. “Computational Analysis of Stilbenes As Potential Multi-Targeted Therapeutics for Alzheimer’s Disease”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8, no. 1 (January 2025): 145-66. https://doi.org/10.47495/okufbed.1466868.
EndNote Şirin S (January 1, 2025) Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8 1 145–166.
IEEE S. Şirin, “Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease”, Osmaniye Korkut Ata University Journal of The Institute of Science and Techno, vol. 8, no. 1, pp. 145–166, 2025, doi: 10.47495/okufbed.1466868.
ISNAD Şirin, Seda. “Computational Analysis of Stilbenes As Potential Multi-Targeted Therapeutics for Alzheimer’s Disease”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8/1 (January 2025), 145-166. https://doi.org/10.47495/okufbed.1466868.
JAMA Şirin S. Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease. Osmaniye Korkut Ata University Journal of The Institute of Science and Techno. 2025;8:145–166.
MLA Şirin, Seda. “Computational Analysis of Stilbenes As Potential Multi-Targeted Therapeutics for Alzheimer’s Disease”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 8, no. 1, 2025, pp. 145-66, doi:10.47495/okufbed.1466868.
Vancouver Şirin S. Computational Analysis of Stilbenes as Potential Multi-Targeted Therapeutics for Alzheimer’s Disease. Osmaniye Korkut Ata University Journal of The Institute of Science and Techno. 2025;8(1):145-66.

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