Numerous studies have reported that amyloid-beta 42 (Aβ-42) protein is a high-profile risk factor associated with the onset and progression of Alzheimer’s disease (AD). Accumulation of extracellular senile plaques, synaptic degeneration, and intracellular neurofibrillary tangles were recorded as essential features that facilitate the onset of Aβ-42, resulting in AD. Hence, we attempted a new screening technique to discover potential inhibitors against Aβ-42 using an in silico deep neural network approach. We screened PubChem compounds library and found wgx-50 as a potential inhibitor of Aβ-42. Also, synergistic effects of wgx-50–gold nanoparticles (AuNPs) complex induced significant inhibition of Aβ-42, compared with those of wgx-50 alone. Further, molecular docking analysis, systems biology approach, and time course simulation confirmed that synergistic effects of wgx-50–AuNPs complex have potential application in the treatment for AD. Additionally, we proposed the biological circuit for AD induced by Aβ-42 that can be used to monitor the effect of drugs on AD.
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The simulations in this work were supported by the Center for High Performance Computing, Shanghai Jiao Tong University.
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Kaushik, A.C., Kumar, A., Peng, Z. et al. Evaluation and validation of synergistic effects of amyloid-beta inhibitor–gold nanoparticles complex on Alzheimer’s disease using deep neural network approach. Journal of Materials Research 34, 1845–1853 (2019). https://doi.org/10.1557/jmr.2018.452