Automated Author Profile

Kumar, Vijay

Laboratory of Organic and Medicinal Chemistry, Department of Chemistry, Central University of Punjab, Ghudda, Bathinda (Punjab)- 151401

Current S-Index

2.8

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.9

Average Dataset Index per dataset

Total Datasets

3

Total datasets for this author

Average FAIR Score

42.9%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Identification of Potential Multi-Target Directed Ligands Through Virtual Screening and Molecular Dynamics Simulation Approach for the Treatment of Alzheimer's Disease

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.

Authors

  • , Kailash ;
  • Devi, Bharti ;
  • Ashrulochan Sahoo ;
  • Kumar, Vijay ;
  • Dwivedi, Ashish Ranjan ;
  • Thareja, Suresh ;
  • Rajnish Kumar ;
  • Kumar, Vinod
0 Citations0 Mentions58% FAIR1.3 Dataset Index
10.5281/zenodo.7511381January 2023

Identification of Potential Multi-Target Directed Ligands Through Virtual Screening and Molecular Dynamics Simulation Approach for the Treatment of Alzheimer's Disease

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.

Authors

  • , Kailash ;
  • Devi, Bharti ;
  • Ashrulochan Sahoo ;
  • Kumar, Vijay ;
  • Dwivedi, Ashish Ranjan ;
  • Thareja, Suresh ;
  • Rajnish Kumar ;
  • Kumar, Vinod
0 Citations0 Mentions58% FAIR1.3 Dataset Index
10.5281/zenodo.7511380January 2023

Identification of Potential Multi-Target Directed Ligands Through Virtual Screening and Molecular Dynamics Simulation Approach for the Treatment of Alzheimer's Disease

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.

Authors

  • , Kailash ;
  • Devi, Bharti ;
  • Ashrulochan Sahoo ;
  • Kumar, Vijay ;
  • Dwivedi, Ashish Ranjan ;
  • Thareja, Suresh ;
  • Rajnish Kumar ;
  • Kumar, Vinod
0 Citations0 Mentions13% FAIR0.3 Dataset Index
10.5281/zenodo.7512041January 2023