Multi-target approach for Alzheimer’s disease treatment: computational biomolecular modeling of cholinesterase enzymes with a novel 4-N-phenylaminoquinoline derivative reveal promising potentials

Abstract

The identification of dual inhibitors targeting the active sites of the cholinesterase enzymes, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), have lately surfaced as a multi-approach towards Alzheimer treatment. More recently, a novel series of 4-N-phenylaminoquinolines was synthesized and evaluated against AChE and BuChE in which one of the compounds displayed appreciable inhibition compared to the standard compound, galantamine. To provide a clearer picture of the inhibition mechanism of this potent compound at the molecular level, computational biomolecular modeling was carried out. The investigation was initiated with the exploration of the chemical properties of the identified compound 11 b and reference drug, galantamine. Density functional theory (DFT) calculations reveal some conceptual parameters that provide information on the stability and reactivity of the compounds as potential inhibitors. To unveil the binding mechanism, energetics and enzyme-ligand interactions, molecular dynamics (MD) simulations of six different systems were executed over a period. Calculated binding free energy values are in the same order with experimental IC₅₀ data. Identification of the main residues driving optimum binding of the active compound 11 b to the binding region of both AChE and BuChE showed Trp81 and Trp110 as the most important, respectively. It was proposed that the studied compound could serve as a dual inhibitor for AChE and BuChE, therefore, would potentially be a promising moiety in a multi-target approach for the treatment of Alzheimer’s disorder.

Communicated by Ramaswamy H. Sarma

Keywords:

• Alzheimer’s disease
• acetylcholinesterase (AChE)
• butyrylcholinesterase (BuChE)
• dual inhibition
• density functional theory (DFT)
• molecular dynamics (MD)

Acknowledgements

The Centre for High-Performance Computing, South Africa (www.chpc.ac.za) is also appreciated for the computational resource.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

We acknowledge the College of Health Sciences, University of KwaZulu Natal, Durban, South Africa, and South African National Research Foundation for financial support.