International journal of molecular sciences
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Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are combined with atomistic molecular simulations and comparative binding free energy analysis of the SARS-CoV and SARS-CoV-2 spike protein receptor binding domains with the ACE2 host receptor. ⋯ Through coevolutionary network analysis and dynamics-based alanine scanning, we established linkages between the binding energy hotspots and potential regulators and carriers of signal communication in the virus-host receptor complexes. The results of this study detailed a binding mechanism in which the energetics of the SARS-CoV-2 association with ACE2 may be determined by cumulative changes of a number of residues distributed across the entire binding interface. The central findings of this study are consistent with structural and biochemical data and highlight drug discovery challenges of inhibiting large and adaptive protein-protein interfaces responsible for virus entry and infection transmission.
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New psychoactive substances are being used as drugs and appear to be quite popular nowadays. Thanks to their specific properties, these drugs create inimitable experiences for intoxicated people. Synthetic cathinones are the most common compounds in these new drugs. ⋯ An increasing number of people are being admitted to emergency wards due to the consequences of their use. This work mainly summarizes the history, synthesis, pharmacology, toxicology, structure-activity relationship, metabolism, clinical process and health risks, poisoning and death, forensic toxicology, and legal status of α-PVP. We hope this review will help bring more attention to the exploration of this substance in order to raise awareness of its negative impacts on humans.
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The 1918 influenza killed approximately 50 million people in a few short years, and now, the world is facing another pandemic. In December 2019, a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused an international outbreak of a respiratory illness termed coronavirus disease 2019 (COVID-19) and rapidly spread to cause the worst pandemic since 1918. Recent clinical reports highlight an atypical presentation of acute respiratory distress syndrome (ARDS) in COVID-19 patients characterized by severe hypoxemia, an imbalance of the renin-angiotensin system, an increase in thrombogenic processes, and a cytokine release storm. ⋯ PH is a complication of ARDS that has received little attention; thus, we hypothesize that PH in COVID-19-induced ARDS represents an important target for disease amelioration. The mechanisms that can promote PH following SARS-CoV-2 infection are described. In this review article, we outline emerging mechanisms of pulmonary vascular dysfunction and outline potential treatment options that have been clinically tested.
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Acute respiratory distress syndrome (ARDS) is characterized by massive inflammation, increased vascular permeability and pulmonary edema. Mortality due to ARDS remains very high and even in the case of survival, acute lung injury can lead to pulmonary fibrosis. The renin-angiotensin system (RAS) plays a significant role in these processes. ⋯ In addition, the impact of established RAS-inhibiting drugs on the pulmonary RAS is to be elucidated. The unfavorable prognosis of ARDS and the lack of effective treatment urge the search for novel therapeutic strategies. In the context of the ongoing SARS-CoV-2 pandemic and considering the involvement of humoral disbalance in the pathogenesis of ARDS, targeting the renin-angiotensin system and reducing the pathogen's cell entry could be a promising therapeutic strategy in the struggle against COVID-19.
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Patients with gliomas, isocitrate dehydrogenase 1 (IDH1) mutation status have been studied as a prognostic indicator. Recent advances in machine learning (ML) have demonstrated promise in utilizing radiomic features to study disease processes in the brain. We investigate whether ML analysis of multiparametric radiomic features from preoperative Magnetic Resonance Imaging (MRI) can predict IDH1 mutation status in patients with glioma. ⋯ The FLAIR-trained XGBoost model achieved ROC with AUC of 0.95, accuracy of 0.90, f1-score of 0.75 on the test set. A model that was trained on combined FLAIR-DWI radiomic features did not provide incremental accuracy. The results show that a XGBoost classifier using multiparametric radiomic features derived from preoperative MRI can predict IDH1 mutation status with > 90% accuracy.