Applications and prospects of cryo-EM in drug discovery.

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time- and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy (cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence (AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of medium-resolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

TRIM18 is a critical regulator of viral myocarditis and organ inflammation.

BACKGROUND: Infections by viruses including severe acute respiratory syndrome coronavirus 2 could cause organ inflammations such as myocarditis, pneumonia and encephalitis. Innate immunity to viral nucleic acids mediates antiviral immunity as well as inflammatory organ injury. However, the innate immune mechanisms that control viral induced organ inflammations are unclear. METHODS: To understand the role of the E3 ligase TRIM18 in controlling viral myocarditis and organ inflammation, wild-type and Trim18 knockout mice were infected with coxsackievirus B3 for inducing viral myocarditis, influenza A virus PR8 strain and human adenovirus for inducing viral pneumonia, and herpes simplex virus type I for inducing herpes simplex encephalitis. Mice survivals were monitored, and heart, lung and brain were harvested for histology and immunohistochemistry analysis. Real-time PCR, co-immunoprecipitation, immunoblot, enzyme-linked immunosorbent assay, luciferase assay, flow cytometry, over-expression and knockdown techniques were used to understand the molecular mechanisms of TRIM18 in regulating type I interferon (IFN) production after virus infection in this study. RESULTS: We find that knockdown or deletion of TRIM18 in human or mouse macrophages enhances production of type I IFN in response to double strand (ds) RNA and dsDNA or RNA and DNA virus infection. Importantly, deletion of TRIM18 protects mice from viral myocarditis, viral pneumonia, and herpes simplex encephalitis due to enhanced type I IFN production in vivo. Mechanistically, we show that TRIM18 recruits protein phosphatase 1A (PPM1A) to dephosphorylate TANK binding kinase 1 (TBK1), which inactivates TBK1 to block TBK1 from interacting with its upstream adaptors, mitochondrial antiviral signaling (MAVS) and stimulator of interferon genes (STING), thereby dampening antiviral signaling during viral infections. Moreover, TRIM18 stabilizes PPM1A by inducing K63-linked ubiquitination of PPM1A. CONCLUSIONS: Our results indicate that TRIM18 serves as a negative regulator of viral myocarditis, lung inflammation and brain damage by downregulating innate immune activation induced by both RNA and DNA viruses. Our data reveal that TRIM18 is a critical regulator of innate immunity in viral induced diseases, thereby identifying a potential therapeutic target for treatment.

Increased circulating microparticles contribute to severe infection and adverse outcomes of COVID-19 in patients with diabetes.

Patients with diabetes infected with COVID-19 have greater mortality than those without comorbidities, but the underlying mechanisms remain unknown. This study aims to identify the mechanistic interactions between diabetes and severe COVID-19. Microparticles (MPs), the cell membrane-derived vesicles released on cell activation, are largely increased in patients with diabetes. To date, many mechanisms have been postulated for increased severity of COVID-19 in patients with underlying conditions, but the contributions of excessive MPs in patients with diabetes have been overlooked. This study characterizes plasma MPs from normal human subjects and patients with type 2 diabetes in terms of amount, cell origins, surface adhesive properties, ACE2 expression, spike protein binding capacity, and their roles in SARS-CoV-2 infection. Results showed that over 90% of plasma MPs express ACE2 that binds the spike protein of SARS-CoV-2. MPs in patients with diabetes increase 13-fold in quantity and 11-fold in adhesiveness when compared with normal subjects. Perfusion of human plasma with pseudo-typed SARS-CoV-2 virus or spike protein-bound MPs into human endothelial cell-formed microvessels-on-a chip demonstrated that MPs from patients with diabetes, not normal subjects, interact with endothelium and carry SARS-CoV-2 into cells through endocytosis, providing additional virus entry pathways and enhanced infection. Results also showed a large percentage of platelet-derived tissue factor-bearing MPs in diabetic plasma, which could contribute to thrombotic complications with SARS-CoV-2 infection. This study reveals a dual role of diabetic MPs in promoting SARS-CoV-2 entry and propagating vascular inflammation. These findings provide novel mechanistic insight into the high prevalence of COVID-19 in patients with diabetes and their propensity to develop severe vascular complications.NEW & NOTEWORTHY This study provides the first evidence that over 90% of human plasma microparticles express ACE2 that binds SARS-CoV-2 S protein with high affinity. Thus, the highly elevated adhesive circulating microparticles identified in patients with diabetes not only have greater SARS-CoV-2 binding capacity but also enable additional viral entry through virus-bound microparticle-endothelium interactions and enhanced infection. These findings reveal a novel mechanistic insight into the adverse outcomes of COVID-19 in patients with diabetes.

Utilisation of outpatient medical services by people with diagnosed diabetes during the COVID-19 pandemic in Germany.

People with diabetes regularly need outpatient medical care due to their disease and possible concomitant and secondary illnesses. Using data from the nationwide GEDA 2019/2020-EHIS survey conducted from April 2019 to September 2020, the present study examines developments in outpatient utilisation behaviour during the measures put in place to contain the SARS-CoV-2 pandemic. During the observation period, people with diabetes had a significantly higher rate of utilisation of medical services provided by general practitioners (GPs) and specialists than the population as a whole. In the spring of 2020, when the restrictions were put in place, utilisation of specialist medical services by people with diabetes decreased temporarily by 46% compared to the 2019 reference period. In contrast, no relevant decline in the utilisation of medical services provided by GPs was observed, but this could be related to adaptations of care provision through telephone consultations for people with regularly requiring GP office visits. The issue examined here requires further observations in view of the renewed containment measures.

Hematological characteristics of patients with novel coronavirus pneumonia in intensive care unit.

BACKGROUND: Toward the end of December 2019, a novel type of coronavirus (2019-nCoV) broke out in Wuhan, China. Here, the hematological characteristics of patients with severe and critical 2019-nCoV pneumonia in intensive care unit (ICU) were investigated, which may provide the necessary basis for its diagnosis and treatment. METHODS: We collected data on patients with confirmed 2019-nCoV pneumonia in the ICU of Leishenshan Hospital in Wuhan from February 25 to April 2, 2020. Real-time reverse-transcription polymerase chain reaction was used to confirm the presence of 2019-nCoV, and various hematological characteristics were analyzed. RESULTS: All patients tested positive for 2019-nCoV using nasopharyngeal swabs or sputum after admission, and interstitial pneumonia findings were noted on chest computed tomography. Sex, age and comorbidities were not significantly different between the severe and critical groups. In terms of prognosis, the survival rate of patients in the severe group reached 100%, whereas that of patients in the critical group was only 13.33% after positive treatment. Furthermore, lymphocyte percentage, blood urea nitrogen, calcium, D-dimer, myohemoglobin, procalcitonin, and IL-6 levels were high-risk factors for disease progression in critical patients. Finally, lymphocyte percentage and blood urea nitrogen, calcium, myohemoglobin, and IL-6 levels were closely associated with patient prognosis. CONCLUSIONS: 2019-nCoV pneumonia should be considered a systemic disease. Patients with more complications were more likely to develop critical disease. Lymphocyte percentage and blood urea nitrogen, calcium, myohemoglobin, and IL-6 levels can be monitored to prevent progression critical disease.

Atrial Arrhythmias in Patients with Severe COVID-19.

The number of confirmed COVID-19 cases has increased drastically; however, information regarding the impact of this disease on the occurrence of arrhythmias is scarce. The aim of this study was to determine the impact of COVID-19 on arrhythmia occurrence. This prospective study included patients with COVID-19 treated at the Leishenshan Temporary Hospital of Wuhan City, China, from February 24 to April 5, 2020. Demographic, comorbidity, and arrhythmias data were collected from patients with COVID-19 (n = 84) and compared with control data from patients with bacterial pneumonia (n = 84) infection. Furthermore, comparisons were made between patients with severe and nonsevere COVID-19 and between older and younger patients. Compared with patients with bacterial pneumonia, those with COVID-19 had higher total, mean, and minimum heart rates (all P < 0.01). Patients with severe COVID-19 (severe and critical type diseases) developed more atrial arrhythmias compared with those with nonsevere symptoms. Plasma creatine kinase isoenzyme (CKMB) levels (P=0.01) were higher in the severe group than in the nonsevere group, and there were more deaths in the severe group than in the nonsevere group (6 (15%) vs. 3 (2.30%); P=0.05). Premature atrial contractions (PAC) and nonsustained atrial tachycardia (NSAT) were significantly positively correlated with plasma CKMB levels but not with high-sensitive cardiac troponin I or myoglobin levels. Our data demonstrate that COVID-19 patients have higher total, mean, and minimum heart rates compared with those with bacterial pneumonia. Patients with severe or critical disease had more frequent atrial arrhythmias (including PAC and AF) and higher CKMB levels and mortality than those with nonsevere symptoms.

Rhabdomyolysis is Associated with In-Hospital Mortality in Patients with COVID-19.

PURPOSE: Rhabdomyolysis (RM) has been associated with many viral infectious diseases, and associated with poor outcomes. We aim to evaluate the clinical features and outcomes of RM in patients with coronavirus disease 2019 (COVID-19). METHOD: This was a single-center, retrospective, cohort study of 1,014 consecutive hospitalized patients with confirmed COVID-19 at the Huoshenshan Hospital in Wuhan, China, between February 17 and April 12, 2020. RESULTS: The overall incidence of RM was 2.2%. Compared with patients without RM, those with RM tended to have a higher risk of deterioration. Patients with RM also constituted a greater percentage of patients admitted to the intensive care unit (90.9% vs. 5.3%, P < 0.001) and a greater percentage of patients undergoing mechanical ventilation (86.4% vs. 2.7% P < 0.001). Moreover, patients with RM had laboratory test abnormalities, including the presence of markers of inflammation, activation of coagulation, and kidney injury. Patients with RM also had a higher risk of in-hospital death (P < 0.001). Cox's proportional hazard regression model analysis confirmed that RM indicators, including peak creatine kinase levels > 1,000 IU/L (HR = 6.46, 95% CI: 3.02-13.86) and peak serum myoglobin concentrations > 1,000 ng/mL (HR = 9.85, 95% CI: 5.04-19.28), were independent risk factors for in-hospital death. Additionally, patients with COVID-19 that developed RM tended to have delayed viral clearance. CONCLUSION: RM might be an important contributing factor to adverse outcomes in COVID-19 patients. The early detection and effective intervention of RM may help reduce mortality among COVID-19 patients.

High resolution computed tomography for the diagnosis of 2019 novel coronavirus (2019-nCoV) pneumonia: a study from multiple medical centers in western China.

BACKGROUND: To evaluate the role of high-resolution computed tomography (HRCT) in the diagnosis of 2019 novel coronavirus (2019-nCoV) pneumonia and to provide experience in the early detection and diagnosis of 2019-nCoV pneumonia. METHODS: Seventy-two patients confirmed to be infected with 2019-nCoV from multiple medical centers in western China were retrospectively analyzed, including epidemiologic characteristics, clinical manifestations, laboratory findings and HRCT chest features. RESULTS: All patients had lung parenchymal abnormalities on HRCT scans, which were mostly multifocal in both lungs and asymmetric in all patients, and were mostly in the peripheral or subpleural lung regions in 52 patients (72.22%), in the central lung regions in 16 patients (22.22%), and in both lungs with "white lung" manifestations in 4 patients (5.56%). Subpleural multifocal consolidation was a predominant abnormality in 38 patients (52.78%). Ground-glass opacity was seen in 34 patients (47.22%). Interlobular septal thickening was found in 18 patients, 8 of whom had only generally mild thickening with no zonal predominance. Reticulation was seen in 8 patients (11.11%), and was mild and randomly distributed. In addition, both lungs of 28 patients had 2 or 3 CT imaging features. Out of these 72 patients, 36 were diagnosed as early stage, 32 patients as progressive stage, and 4 patient as severe stage pneumonia. Moreover, the diagnostic accuracy of HRCT features combined with epidemiological history was not significantly different from the detection of viral nucleic acid (all P >0.05). CONCLUSIONS: The HRCT features of 2019-nCoV pneumonia are characteristic to a certain degree, which when combined with epidemiological history yield high clinical value in the early detection and diagnosis of 2019-nCoV pneumonia.

Compare the epidemiological and clinical features of imported and local COVID-19 cases in Hainan, China.

BACKGROUND: Effective management of imported cases is an important part of epidemic prevention and control. Hainan Province, China reported 168 coronavirus disease 2019 (COVID-19), including 112 imported cases on February 19, 2020, but successfully contained the epidemic within 1 month. We described the epidemiological and clinical characteristics of COVID-19 in Hainan and compared these features between imported and local cases to provide information for other international epidemic areas. METHODS: We included 91 patients (56 imported and 35 local cases) from two designated hospitals for COVID-19 in Haikou, China, from January 20 to February 19, 2020. Data on the demographic, epidemiological, clinical and laboratory characteristics were extracted from medical records. Patients were followed until April 21, 2020, and the levels of antibodies at the follow-ups were also analysed by the Wilcoxon matched-pairs signed ranks test. RESULTS: Of the 91 patients, 78 (85.7%) patients were diagnosed within the first three weeks after the first case was identified (Day 1: Jan 22, 2020), while the number of local cases started to increase during the third week. No new cases occurred after Day 29. Fever and cough were two main clinical manifestations. In total, 15 (16.5%) patients were severe, 14 (15.4%) had complicated infections, nine (9.9%) were admitted to the intensive care unit, and three died. The median duration of viral shedding in feces was longer than that in nasopharyngeal swabs (19 days vs 16 days, P = 0.007). Compared with local cases, imported cases were older and had a higher incidence of fever and concurrent infections. There was no difference in outcomes between the two groups. IgG was positive in 92.8% patients (77/83) in the follow-up at week 2 after discharge, while 88.4% patients (38/43) had a reduction in IgG levels in the follow-up at week 4 after discharge, and the median level was lower than that in the follow-up at week 2 (10.95 S/Cut Off (S/CO) vs 15.02 S/CO, P <  0.001). CONCLUSION: Imported cases were more severe than local cases but had similar prognoses. The level of IgG antibodies declined from week 6 to week 8 after onset. The short epidemic period in Hainan suggests that the epidemic could be quickly brought under control if proper timely measures were taken.

Introducing the GEV Activation Function for Highly Unbalanced Data to Develop COVID-19 Diagnostic Models.

Fast and accurate diagnosis is essential for the efficient and effective control of the COVID-19 pandemic that is currently disrupting the whole world. Despite the prevalence of the COVID-19 outbreak, relatively few diagnostic images are openly available to develop automatic diagnosis algorithms. Traditional deep learning methods often struggle when data is highly unbalanced with many cases in one class and only a few cases in another; new methods must be developed to overcome this challenge. We propose a novel activation function based on the generalized extreme value (GEV) distribution from extreme value theory, which improves performance over the traditional sigmoid activation function when one class significantly outweighs the other. We demonstrate the proposed activation function on a publicly available dataset and externally validate on a dataset consisting of 1,909 healthy chest X-rays and 84 COVID-19 X-rays. The proposed method achieves an improved area under the receiver operating characteristic (DeLong's p-value < 0.05) compared to the sigmoid activation. Our method is also demonstrated on a dataset of healthy and pneumonia vs. COVID-19 X-rays and a set of computerized tomography images, achieving improved sensitivity. The proposed GEV activation function significantly improves upon the previously used sigmoid activation for binary classification. This new paradigm is expected to play a significant role in the fight against COVID-19 and other diseases, with relatively few training cases available.