In silico prediction of parkinsonian motor deficits-related neurotoxicants based on the adverse outcome pathway concept.

Exposure to neurotoxicants has been associated with Parkinson's disease (PD). Limited by the clinical variation in the signs and symptoms as well as the slow disease progression, the identification of parkinsonian neurotoxicants relies on animal models. Here, we propose an innovative in silico model for the prediction of parkinsonian neurotoxicants. The model was designed based on a validated adverse outcome pathway (AOP) for parkinsonian motor deficits initiated from the inhibition of mitochondrial complex I. The model consists of a molecular docking model for mitochondrial complex I protein to predict the molecular initiating event and a neuronal cytotoxicity Quantitative Structure-Activity Relationships (QSAR) model to predict the cellular outcome of the AOP. Four known PD-related complex I inhibitors and four non-neurotoxic chemicals were utilized to develop the threshold of the models and to validate the model, respectively. The integrated model showed 100% specificity in ruling out the non-neurotoxic chemicals. The screening of 41 neurotoxicants and complex I inhibitors with the model resulted in 16 chemicals predicted to induce parkinsonian disorder through the molecular initiating event of mitochondrial complex I inhibition. Five of them, namely cyhalothrin, deguelin, deltamethrin, diazepam, and permethrin, are cases with direct evidence linking them to parkinsonian motor deficit-related signs and symptoms. The neurotoxicant prediction model for parkinsonian motor deficits based on the AOP concept may be useful in prioritizing chemicals for further evaluations on PD potential.

Discovery of M Protease Inhibitors Encoded by SARS-CoV-2.

The coronavirus (CoV) disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome CoV-2 (SARS-CoV-2) is a health threat worldwide. Viral main protease (Mpro, also called 3C-like protease [3CLpro]) is a therapeutic target for drug discovery. Herein, we report that GC376, a broad-spectrum inhibitor targeting Mpro in the picornavirus-like supercluster, is a potent inhibitor for the Mpro encoded by SARS-CoV-2, with a half-maximum inhibitory concentration (IC50) of 26.4 ± 1.1 nM. In this study, we also show that GC376 inhibits SARS-CoV-2 replication with a half-maximum effective concentration (EC50) of 0.91 ± 0.03 µM. Only a small portion of SARS-CoV-2 Mpro was covalently modified in the excess of GC376 as evaluated by mass spectrometry analysis, indicating that improved inhibitors are needed. Subsequently, molecular docking analysis revealed that the recognition and binding groups of GC376 within the active site of SARS-CoV-2 Mpro provide important new information for the optimization of GC376. Given that sufficient safety and efficacy data are available for GC376 as an investigational veterinary drug, expedited development of GC376, or its optimized analogues, for treatment of SARS-CoV-2 infection in human is recommended.

Artificial intelligence approach fighting COVID-19 with repurposing drugs.

Background: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the disease will be a therapeutic medicine that has prior use experiences in patients in order to resolve the current pandemic situation before it could become worsening. Artificial intelligence (AI) technology is hereby applied to identify the marketed drugs with potential for treating COVID-19. Methods: An AI platform was established to identify potential old drugs with anti-coronavirus activities by using two different learning databases; one consisted of the compounds reported or proven active against SARS-CoV, SARS-CoV-2, human immunodeficiency virus, influenza virus, and the other one containing the known 3C-like protease inhibitors. All AI predicted drugs were then tested for activities against a feline coronavirus in in vitro cell-based assay. These assay results were feedbacks to the AI system for relearning and thus to generate a modified AI model to search for old drugs again. Results: After a few runs of AI learning and prediction processes, the AI system identified 80 marketed drugs with potential. Among them, 8 drugs (bedaquiline, brequinar, celecoxib, clofazimine, conivaptan, gemcitabine, tolcapone, and vismodegib) showed in vitro activities against the proliferation of a feline infectious peritonitis (FIP) virus in Fcwf-4 cells. In addition, 5 other drugs (boceprevir, chloroquine, homoharringtonine, tilorone, and salinomycin) were also found active during the exercises of AI approaches. Conclusion: Having taken advantages of AI, we identified old drugs with activities against FIP coronavirus. Further studies are underway to demonstrate their activities against SARS-CoV-2 in vitro and in vivo at clinically achievable concentrations and doses. With prior use experiences in patients, these old drugs if proven active against SARS-CoV-2 can readily be applied for fighting COVID-19 pandemic.

Fluorophore Absorption Size Exclusion Chromatography (FA-SEC): An Alternative Method for High-Throughput Detergent Screening of Membrane Proteins.

Membrane proteins play key roles in many fundamental functions in cells including ATP synthesis, ion and molecule transporter, cell signalling and enzymatic reactions, accounting for ~30% genes of whole genomes. However, the hydrophobic nature of membrane proteins frequently hampers the progress of structure determination. Detergent screening is the critical step in obtaining stable detergent-solubilized membrane proteins and well-diffracting protein crystals. Fluorescence Detection Size Exclusion Chromatography (FSEC) has been developed to monitor the extraction efficiency and monodispersity of membrane proteins in detergent micelles. By tracing the FSEC profiles of GFP-fused membrane proteins, this method significantly enhances the throughput of detergent screening. However, current methods to acquire FSEC profiles require either an in-line fluorescence detector with the SEC equipment or an off-line spectrofluorometer microplate reader. Here, we introduce an alternative method detecting the absorption of GFP (FA-SEC) at 485 nm, thus making this methodology possible on conventional SEC equipment through the in-line absorbance spectrometer. The results demonstrate that absorption is in great correlation with fluorescence of GFP. The comparably weaker absorption signal can be improved by using a longer path-length flow cell. The FA-SEC profiles were congruent with the ones plotted by FSEC, suggesting FA-SEC could be a comparable and economical setup for detergent screening of membrane proteins.

Evaluation of the antiangiogenic effect of Kringle 1-5 in a rat glioma model.

BACKGROUND: Kringle 1-5 (K1-5) is a potent antiangiogenesis factor for treating breast cancer and hepatocellular carcinoma. However, its use in treating brain tumors has not been studied. OBJECTIVE: To evaluate whether K1-5 is effective at treating gliomas. METHODS: The effects of K1-5 on cell morphology and cytotoxicity with or without lipopolysaccharide were tested in primary mixed neuronal-glial cultures. The antiglioma activity of K1-5 was evaluated by intra-arterial administration of K1-5 at 4 days after implantation of C6 glioma cells into the rat hippocampus. In 1 group of animals, tumor size, tumor vasculature, and tumor histology were evaluated on day 12. Animal survival was assessed in the other group. RESULTS: In vitro studies showed that K1-5 did not induce cytotoxicity in neurons and glia. In vivo studies demonstrated that K1-5 reduced vessel length and vessel density and inhibited perivascular tumor invasion. In addition, K1-5 normalized vessel morphology, decreased expression of hypoxia-inducible factor-1α and vascular endothelial growth factor, decreased tumor hypoxia, and decreased pseudopalisading necrosis. The average tumor volume was smaller in the treated than in the untreated group. Furthermore, animals treated with K1-5 survived significantly longer. CONCLUSION: Kringle 1-5 effectively reduces the growth of malignant gliomas in the rat. Although still far from translation in humans, K1-5 might be a possible future alternative treatment option for patients with gliomas.

Functional recovery after the repair of transected cervical roots in the chronic stage of injury.

The treatment of root injury is typically performed at the more chronic stages post injury, by which time a substantial number of neurons have died. Therefore, before being applied in the clinical setting, a treatment strategy for these lesions should prove to be as effective in the chronic stages of injury as it is in the acute stage. In this study, we simulated the most severe clinical scenarios to establish an optimal time window for repair at a chronic stage. The sixth to eighth cervical roots on the left side of female SD rats were cut at their junction with the spinal cord. One or three weeks later, the wound was reopened and these roots were repaired with intercostal nerve grafts, with subsequent application of aFGF and fibrin glue. In the control group, the wound was closed after re-exploration without further repair procedures. Sensory and motor functions were measured after the surgery. Spinal cord morphology, neuron survival, and nerve fiber regeneration were traced by CTB-HRP. Results showed that both the sensory and motor functions had significant recovery in the 1-week repair group, but not in the 3-week repair group. By CTB-HRP tracing, we found that the architecture of the spinal cords was relatively preserved in the 1-week repair group, while those of the control group showed significant atrophic change. There were regenerating nerve fibers in the dorsal horn and more motor neuron survival in the 1-week repair group compared to that of the 3-week group. It was concluded that treating transected cervical roots at a chronic stage with microsurgical nerve grafting and application of aFGF and fibrin glue can lead to significant functional recovery, as long as the repair is done before too many neurons die.