2D QSAR, design, docking study and ADMET of some N-aryl derivatives concerning inhibitory activity against Alzheimer disease

Future Journal of Pharmaceutical Sciences - Tập 8 - Trang 1-14 - 2022
Abduljelil Ajala1, Adamu Uzairu1, Gideon A. Shallangwa1, Stephen E. Abechi1
1Department of Chemistry, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria

Tóm tắt

Alzheimer disease (AD) is an ailment that disturbs mainly people of old age. The fundamental remedial way to deal with AD depends on the utilization of AChEI. The design of new intense and particular AChEI is critical in drug discovery. In silico technique will be used to solve the above problem. A new method was established to discover novel agents with better biological activity against Alzheimer disease. A validated model was established in this research to predict the biological activities of some anti-Alzheimer compounds and to design new hypothetical drugs influenced with molecular properties in the derived model; ATS4i, MATS2e, SpMax7_BhS, Energy(HOMO) and Molecular Weight and showed good correlation R2 = 0.936, R2adj = 0.907, Q2cv = 0.88, LOF = 0.0154 and R2ext = 0.881. All the descriptors in the model were in good agreement with the 15 test set predicted values. Five compounds were designed using D35rm as a template with improved activity. The compounds have higher and better binding scores (− 10.1, − 9.4, − 9.3, − 9.1 and − 8.1 all in kcal/mol) than the approved drugs (Donepezil =  − 7.4 kcal/mol). As the outcome, every one of the selected and the designed compounds is created and improved as potential anti-Alzheimer agents. Despite this, the further test examines and in vivo investigations are recommended to assess the method of the activities and other pharmacological impacts on these compounds.

Tài liệu tham khảo

Verma N, Beretvas SN, Pascual B, Masdeu JC, Markey MK (2015) New scoring methodology improves the sensitivity of the Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-Cog) in clinical trials. Alzheimer’s Res Ther 7(1):1–17

Mehta D, Jackson R, Paul G, Shi J, Sabbagh M (2017) Why do trials for Alzheimer’s disease drugs keep failing? A discontinued drug perspective for 2010–2015. Expert Opin Investig Drugs 26(6):735–739. https://doi.org/10.1080/13543784.2017.1323868

Adedirin O, Uzairu A, Shallangwa GA, Abechi SE (2018) Computational studies on α-aminoacetamide derivatives with anticonvulsant activities. Beni-Suef Univ J Basic Appl Sci. 3:1–10. https://doi.org/10.1016/j.bjbas.2018.08.005

Arthur DE, Uzairu A, Mamza P, Abechi SE, Shallangwa G (2018) Insilico modelling of quantitative structure–activity relationship of pGI50 anticancer compounds on K-562 cell line. Cogent Chem 4(1):1–23. https://doi.org/10.1080/23312009.2018.1432520

Golbraikh A, Tropsha A (2002) Beware of q 2 ! J Mol Graph Modell 20:269–276

Abdulfatai U, Uzairu A, Uba S, Shallangwa GA (2019) Molecular modelling and design of lubricant additives and their molecular dynamic simulations studies of diamond-like-carbon (DLC) and steel surface coating. Egypt J Pet 28(1):111–115. https://doi.org/10.1016/j.ejpe.2018.12.004

Brooijmans N (2009) Chapter: Docking methods, ligand design, and validating data sets in the structural genomics era. In: Gu J, Bourne PE (eds) Structural bioinformatics. Wiley, New York, pp 635–663

Lipinski CA (2016) Rule of five in 2015 and beyond: target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Adv Drug Deliv Rev 101:34–41. https://doi.org/10.1016/j.addr.2016.04.029

Hassan SSU, Zhang WD, Jin HZ, Basha SH, Priya SS (2022) In silico anti-inflammatory potential of guaiane dimers from Xylopia vielana targeting COX-2. J Biomol Struct Dyn 40(1):484–498. https://doi.org/10.1080/07391102.2020.1815579