Deciphering the Interactions of Bioactive Compounds in Selected Traditional Medicinal Plants against Alzheimer’s Diseases via Pharmacophore Modeling, Auto-QSAR, and Molecular Docking Approaches

Molecules

OdunayoAnthonia Taiwo¹  AbayomiEmmanuel Adegboyega²  AdebolaBusola Ojo³  KhalafF. Alsharif⁴  IkponmwosaOwen Evbuomwan⁵  Charles Okolie⁵  GaberEl-Saber Batiha⁶   OluwafemiAdeleke Ojo⁷  Mary-AnnChinyere Nwakama⁷  CharlesObiora Nwonuma⁷  Matthew Iyobhebhe⁷  RotdelmwaFilibus Maimako⁷ 

[1] Department of Biochemistry, Chrisland University, Abeokuta PMB 2131, Nigeria;Department of Biochemistry, Faculty of Basic Medical Science, University of Jos, Jos PMB 2084, Nigeria;Department of Biochemistry, Faculty of Sciences, Ekiti State University, Ado-Ekiti PMB 5363, Nigeria;Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;Department of Microbiology, Landmark University, Omu-Aran PMB 1001, Nigeria;Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, AlBeheira 22511, Egypt;Medicinal Biochemistry and Biochemical Toxicology Group, Department of Biochemistry, Landmark University, Omu-Aran PMB 1001, Nigeria;

关键词: Alzheimer’s;    pharmacophore modeling;    QSAR;    molecular docking;    bioactive compounds;    neurodegenerative diseases;   

DOI  :  10.3390/molecules26071996

来源: DOAJ

【 摘 要 】

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC₅₀ values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R² = 0.86 and Q² = 0.73), pls_38 (R² = 0.77 and Q² = 0.72), kpls_desc_44 (R² = 0.81 and Q² = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.

【 授权许可】

Unknown