Literature DB >> 31543038

Reappraisal of FDA approved drugs against Alzheimer's disease based on differential gene expression and protein interaction network analysis: an in silico approach.

Hema Sree G N S1, Saraswathy Ganesan Rajalekshmi1,2, Manikanta Murahari1,3, Raghunadha R Burri4.   

Abstract

Alzheimer's disease (AD), a most prevailing neurodegenerative disorder with turbulence in cognitive and behavioural abilities, epitomizes one of the highest unmet medical requirements. The current AD treatment focuses merely on symptomatic relief, this explains a dearth in drug research oriented towards unwinding of disease specific druggable targets. On the other hand, toxicity and poor bioavailability hamper the evolution of novel chemical entities (NCE) in clinical trials. Drug repurposing offers a gateway to rejuvenate new therapeutic applications for existing approved drugs. This study concentrates on the identification of potential druggable AD targets and screening of FDA approved drugs with a concept of drug repurposing. differentially expressed genes (DEGs) were identified in frontal cortex, temporal cortex and hippocampus in AD patients from Gene Expression Omnibus (GEO) dataset GSE36980. Protein-protein interaction (PPI) analysis revealed SERPINA3 and BDNF to possess high node degree interaction with literature derived candidate genes (LDGs) in AD males and females, respectively, thus were selected as potential AD targets. Subsequently, FDA approved drugs were screened through the above shortlisted targets and were ranked based on molecular docking and MM-GBSA energy calculations using Glide and Prime tools, respectively. Drugs possessing best docking score and maximum binding energy were further evaluated through molecular dynamics simulation studies, which revealed the affinity of Tiludronic acid and Olsalazine towards SERPINA3 and BDNF, respectively.

Entities:  

Keywords:  Alzheimer’s disease; BDNF; Drug repurposing; SERPINA3; olsalazine; tiludronic acid

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Year:  2019        PMID: 31543038     DOI: 10.1080/07391102.2019.1671231

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102


  3 in total

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Journal:  Molecules       Date:  2022-07-08       Impact factor: 4.927

2.  Hub Genes, Diagnostic Model, and Predicted Drugs Related to Iron Metabolism in Alzheimer's Disease.

Authors:  Xuefeng Gu; Donglin Lai; Shuang Liu; Kaijie Chen; Peng Zhang; Bing Chen; Gang Huang; Xiaoqin Cheng; Changlian Lu
Journal:  Front Aging Neurosci       Date:  2022-07-07       Impact factor: 5.702

3.  High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3.

Authors:  Chandrabose Selvaraj; Dhurvas Chandrasekaran Dinesh; Umesh Panwar; Evzen Boura; Sanjeev Kumar Singh
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2021-08-06       Impact factor: 3.702

  3 in total

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