Identification of imidazole-based small molecules to combat cognitive disability caused by Alzheimer’s disease: A molecular docking and MD simulations based approach
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引用次数: 0
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disorder that is the primary cause of dementia. It is characterised by the gradual loss of brain cells, which results in memory loss and cognitive dysfunction. One of the hallmarks of AD is an abnormally upregulated glutaminyl-peptide cyclotransferase (QPCT or QC) enzyme. Not only AD, but QC has also been implicated with pathological conditions like Huntington's disease (HD), melanomas, carcinomas, atherosclerosis, and septic arthritis. Therefore, the inhibition of QC emerged as a potential strategy for preventing multiple pathological conditions. Considering this, we screened a library of 153,536 imidazole-based compounds against a doubly mutant (Y115E-Y117E) QC target. Molecular docking based virtual screening and absorption, distribution, metabolism, excretion/toxicity (ADME/T) predictions identified five compounds, namely 118981836, 136459842, 139388116, 139388226, and 139958725. Furthermore, molecular dynamics (MD) simulations of 500 ns were conducted to investigate the behaviour of the identified compounds with the target receptor. The results were compared to the co-ligand by analysing RMSD, RMSF, and SASA parameters. To our knowledge, this is the first computational study that employed a protein with double mutation to identify new imidazole-based QC-inhibitors.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.