Network-based identification of miRNAs and transcription factors and in silico drug screening targeting δ-secretase involved in Alzheimer's disease
Saleem Iqbal, Md. Zubbair Malik, Debnath Pal
Abstract
BACKGROUND: System medicine approaches have played a pivotal role in identifying novel disease networks especially in miRNA research. It is no wonder that miRNAs are implicated in multiple clinical conditions, allowing us to establish the hubs and nodes for network models of Alzheimer's Disease (AD). AD is an age-related, progressive, irreversible, and multifactorial neurodegenerative disorder characterized by cognitive and memory impairment and is the most common cause of dementia in older adults. Worldwide, around 50 million people have dementia, and there are nearly 10 million new cases every year. δ-secretase, also known as asparagine endopeptidase (AEP) or legumain (LGMN), is a lysosomal cysteine protease that cleaves peptide bonds C-terminally to asparagine residues in both amyloid precursor protein (APP) and tau, mediating the amyloid-β and tau pathology in AD. The patient's miRNA expression was found to be deregulated in the brain, extracellular fluid, blood plasma, and serum. METHODS: drug designing of the novel inhibitor scaffold of δ-secretase as powerful therapeutic targets by using the concept of scaffolds and frameworks. In this context, this study also aimed at identifying effective small molecule inhibitors targeting δ-secretase. RESULTS: Among the 16 experimentally verified miRNAs, Network analysis of the LGMN and its associated miRNA identify novel hsa-miRNA-106a-5p and hsa-miRNA-34a-5p being more expressed in the brain. Our in silico high throughput screening, followed by XP docking revealed Oprea1 as the lead. Molecular dynamic simulations of the δ-secretase-docked complex have been carried out for a time period of 200 ns and revealed that Root Mean Square Deviation (RMSD) of the protein Cα-backbone with respect to its starting position increased to 1.20 Å for the first 25 ns of the trajectory and then became stable around 0.6 Å in the last 170 ns course of the simulation. The radius of gyration (RGYR) reveals that compactness was maintained till the end of simulations. CONCLUSION: drug analysis led us to the identification of Oprea1 which could be taken for further investigation to explore its potential for AD therapy.