Memantine for COVID-19

Abstract The prediction of virus–drug associations (VDAs) is crucial for drug repositioning, contributing to the identification of latent antiviral drugs. In this study, we developed a graph-based integrated Gaussian kernel similarity (GiGs) method for predicting potential VDAs in drug repositioning. The GiGs model comprises three components: (i) collection of experimentally validated VDA information and calculation virus sequence, drug chemical structure, and drug side effect similarity; (ii) integration of viruses and drugs similarity based on the above information and Gaussian interaction profile kernel (GIPK); and (iii) utilization of similarity-constrained weight graph normalization matrix factorization to predict antiviral drugs. The GiGs model enhances correlation matrix quality through the integration of multiple biological data, improves performance via similarity constraints, and prevents overfitting and predicts missing data more accurately through graph regularization. Extensive experimental results indicated that the GiGs model outperforms five other advanced association prediction methods. A case study identified broad-spectrum drugs for treating highly pathogenic human coronavirus infections, with molecular docking experiments confirming the model’s accuracy.

Alpha-synuclein (α-syn) is a 140-amino-acid, intrinsically disordered, soluble protein that is abundantly present in the brain. It plays a crucial role in maintaining cellular structures and organelle functions, particularly in supporting synaptic plasticity and regulating neurotransmitter turnover. However, for reasons not yet fully understood, α-syn can lose its physiological role and begin to aggregate. This altered α-syn disrupts dopaminergic transmission and causes both presynaptic and postsynaptic dysfunction, ultimately leading to cell death. A group of neurodegenerative diseases known as α-synucleinopathies is characterized by the intracellular accumulation of α-syn deposits in specific neuronal and glial cells within certain brain regions. In addition to Parkinson’s disease (PD), these conditions include dementia with Lewy bodies (DLBs), multiple system atrophy (MSA), pure autonomic failure (PAF), and REM sleep behavior disorder (RBD). Given that these disorders are associated with α-syn-related neuroinflammation—and considering that SARS-CoV-2 infection has been shown to affect the nervous system, with COVID-19 patients experiencing neurological symptoms—it has been proposed that COVID-19 may contribute to neurodegeneration in PD and other α-synucleinopathies by promoting α-syn misfolding and aggregation. In this review, we focus on whether SARS-CoV-2 could act as an environmental trigger that facilitates the onset or progression of α-synucleinopathies. Specifically, we present new evidence on the potential role of SARS-CoV-2 in modulating α-syn function and discuss the causal relationship between SARS-CoV-2 infection and the development of parkinsonism-like symptoms.