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Published January 7, 2023 | Version v1
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Identification of Potential Multi-Target Directed Ligands Through Virtual Screening and Molecular Dynamics Simulation Approach for the Treatment of Alzheimer's Disease

  • 1. Laboratory of Organic and Medicinal Chemistry, Department of Chemistry, Central University of Punjab, Ghudda, Bathinda (Punjab)- 151401
  • 2. Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology, BHU, Varanasi (UP)- 221005
  • 3. Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Bathinda (Punjab)-151401
  • 4. Gitam School of Pharmacy Hyderabad, Rudraram Patancheru Mandal, Hyderabad, Telengana-502329

Description

Alzheimer’s disease (AD) is a multifactorial neurological disorder characterized by memory loss and cognitive impairment. The currently available single-targeting drugs have miserably failed in the treatment of AD and multi-target directed ligands (MTDLs) are being explored as an alternative strategy. Cholinesterase and monoamine oxidase enzymes are reported to play crucial role in the pathology of AD and multipotent ligands targeting these two enzymes simultaneously, are under various phases of design and development. Recent studies have revealed that computational approaches are robust and trusted tools for the identification of novel therapeutics. The current research work is focused on the development of potential multitarget directed ligands that simultaneously inhibit acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B) enzymes employing structure-based virtual screening (SBDD) approach. The ASINEX database was screened after applying pan assay interference and drug likeness filter to identify novel molecules using three docking precision criteria Highthroughput virtual screening (HTVS), Standard Precision (SP), and extra precision (XP). Additionally, binding free energy calculations, ADME and molecular dynamic simulations were also employed to get structural insights into mechanism of protein-ligand binding and pharmacokinetic properties. Three lead molecules viz. AOP19078710, BAS00314308 and BDD26909696 were successfully identified which displayed binding score of -10.565, -10.543 & -8.066 kcal/mol against AChE and -11.019, -12.357 & -10.068 kcal/mol against MAO-B, better score as compared to the standard inhibitors. In near future, these molecules will be synthesized and evaluated through in vitro and in vivo assays for their inhibition potential against AChE and MAO-B enzymes.

Notes

In this study, we have used various softwares for the computational studies like: Schrodinger, GROMACS, KNIME extension, SWISS bioavailability prediction.

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