Stabilization of the Metastable Prefusion Conformation of SARS-CoV-2 Spike Glycoprotein through N-linked Glycosylation on S2 Subunit (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents a serious threat to public health. The spike (S) glycoprotein of SARS-CoV-2 mediates viral entry into host cells and is heavily glycosylated. In this study, we systemically analyzed the roles of 22 putative N-linked glycans in SARS-CoV-2 S protein expression, membrane fusion, viral entry, and stability. Using α-glycosidase inhibitors, castanospermine and NB-DNJ, we confirmed that disrupting the N-linked glycosylation process blocked the maturation of the S protein, leading to impairment of S protein-mediated membrane fusion. Single substitution of each of the 22 N-linked glycosylation sites with glutamine revealed that 9 out of the 22 N-linked glycosylation sites were critical for S protein folding and maturation, resulting in reduced S protein-mediated cell-cell fusion and viral entry. Of note, N1074Q mutation markedly affected S protein stability and induced significant receptor-independent syncytium (RIS) formation in HEK293T/hACE2-KO cells, and removal of the furin-cleavage site partially compensated instability of N1074Q mutation. Although the corresponding mutation in the SARS-CoV S protein (N1056Q) did not induce RIS in HEK293T cells, the mutants N669Q and N1080Q exhibited increased fusogenic activity and induced syncytia formation in HEK293T cells. Therefore, N-glycans on the SARS-CoV and SARS-CoV-2 S2 subunits are of great importance in maintaining the prefusion state of the S protein. The study revealed the critical roles of N-glycans in S protein maturation and stability, which have implications for the design of vaccines and anti-viral strategies.

Risk of autoimmune diseases in patients with COVID-19: A retrospective cohort study.

Background: There are a growing number of case reports of various autoimmune diseases occurring after COVID-19, yet there is no large-scale population-based evidence to support this potential association. This study provides a closer insight into the association between COVID-19 and autoimmune diseases and reveals discrepancies across sex, age, and race of participants. Methods: This is a retrospective cohort study based on the TriNetX U.S. Collaborative Network. In the test-negative design, cases were participants with positive polymerase chain reaction (PCR) test results for SARS-CoV-2, while controls were participants who tested negative and were not diagnosed with COVID-19 throughout the follow-up period. Patients with COVID-19 and controls were propensity score-matched (1: 1) for age, sex, race, adverse socioeconomic status, lifestyle-related variables, and comorbidities. The primary endpoint is the incidence of newly recorded autoimmune diseases. Adjusted hazard ratios (aHRs) and 95% confident intervals (CIs) of autoimmune diseases were calculated between propensity score-matched groups with the use of Cox proportional-hazards regression models. Findings: Between January 1st, 2020 and December 31st, 2021, 3,814,479 participants were included in the study (888,463 cases and 2,926,016 controls). After matching, the COVID-19 cohort exhibited significantly higher risks of rheumatoid arthritis (aHR:2.98, 95% CI:2.78-3.20), ankylosing spondylitis (aHR:3.21, 95% CI:2.50-4.13), systemic lupus erythematosus (aHR:2.99, 95% CI:2.68-3.34), dermatopolymyositis (aHR:1.96, 95% CI:1.47-2.61), systemic sclerosis (aHR:2.58, 95% CI:2.02-3.28), Sjögren's syndrome (aHR:2.62, 95% CI:2.29-3.00), mixed connective tissue disease (aHR:3.14, 95% CI:2.26-4.36), Behçet's disease (aHR:2.32, 95% CI:1.38-3.89), polymyalgia rheumatica (aHR:2.90, 95% CI:2.36-3.57), vasculitis (aHR:1.96, 95% CI:1.74-2.20), psoriasis (aHR:2.91, 95% CI:2.67-3.17), inflammatory bowel disease (aHR:1.78, 95%CI:1.72-1.84), celiac disease (aHR:2.68, 95% CI:2.51-2.85), type 1 diabetes mellitus (aHR:2.68, 95%CI:2.51-2.85) and mortality (aHR:1.20, 95% CI:1.16-1.24). Interpretation: COVID-19 is associated with a different degree of risk for various autoimmune diseases. Given the large sample size and relatively modest effects these findings should be replicated in an independent dataset. Further research is needed to better understand the underlying mechanisms. Funding: Kaohsiung Veterans General Hospital (KSVGH111-113).

In silico prediction of immune-escaping hot spots for future COVID-19 vaccine design (preprint)

The COVID-19 pandemic has had a widespread impact on a global scale, and the evolution of considerable dominants has already taken place. Some variants contained certain key mutations located on the receptor binding domain (RBD) of spike protein, such as E484K and N501Y. It is increasingly worrying that these variants could impair the efficacy of current vaccines or therapies. Therefore, how to design future vaccines to prevent the different variants remains urgent. In this work, we proposed an in silico approach, in which we combined binding free energy measured by computational mutagenesis of spike-antibody complexes and mutation frequency calculated from viral genome sequencing data, to estimate an immune-escaping score (IES) and predict immune-escaping hot spots. We identified 23 immune-escaping mutations on the RBD, nine of which occurred in omicron variants (R346K, K417N, N440K, L452Q, L452R, S477N, T478K, F490S, and N501Y), despite our dataset being curated before the omicron first appeared. The highest immune-escaping score (IES=1) was found for E484K, which agrees with recent studies stating that the mutation significantly reduced the efficacy of neutralization antibodies. Furthermore, our predicted binding free energy and IES show a high correlation with high-throughput deep mutational scanning (Pearson’s r = 0.70) and experimentally measured neutralization titers data (mean Pearson’s r = -0.80). In summary, our work provides valuable insights and will help design future COVID-19 vaccines.

Alexithymia and post-traumatic stress disorder symptoms in Chinese undergraduate students during the COVID-19 national lockdown: The mediating role of sleep problems and the moderating role of self-esteem

Objective This study examined whether sleep disturbance was a mediator between alexithymic traits and post-traumatic stress disorder (PTSD) COVID-19 pandemic-related stress symptoms, and explored whether self-esteem moderated the alexithymic contribution to poor sleep and PTSD symptoms. Method A representative sample of young adults (N = 2,485) from six universities in Southwest China completed online self-report surveys on alexithymia, sleep, PTSD, self-esteem, sociodemographic information, and health-related behaviors. Results High alexithymic young adults were found to be more likely to have higher sleep problems and higher PTSD symptoms. The moderated mediation model showed that sleep problems mediated the associations between alexithymia and PTSD symptoms. Alexithymic people with lower self-esteem were more likely to have elevated PTSD symptoms and sleep problems than those with higher self-esteem. Conclusion Targeted psychological interventions for young people who have difficulty expressing and identifying emotions are recommended as these could assist in reducing their post-traumatic psychophysical and psychological problems. Improving self-esteem could also offer some protection for trauma-exposed individuals.

An automated approach to extracting positive and negative clinical research results (preprint)

Failure is common in clinical trials since the successful failures presented in negative results always indicate the ways that should not be taken. In this paper, we proposed an automated approach to extracting positive and negative clinical research results by introducing a PICOE (Population, Intervention, Comparation, Outcome, and Effect) framework to represent randomized controlled trials (RCT) reports, where E indicates the effect between a specific I and O. We developed a pipeline to extract and assign the corresponding statistical effect to a specific I-O pair from natural language RCT reports. The extraction models achieved a high degree of accuracy for ICO and E descriptive words extraction through two rounds of training. By defining a threshold of p-value, we find in all Covid-19 related intervention-outcomes pairs with statistical tests, negative results account for nearly 40%. We believe that this observation is noteworthy since they are extracted from the published literature, in which there is an inherent risk of reporting bias, preferring to report positive results rather than negative results. We provided a tool to systematically understand the current level of clinical evidence by distinguishing negative results from the positive results.

Impact of government interventions on the stock market during COVID-19: a case study in Indonesia

This paper aims to examine the short-term impact of government interventions on 11 industrial sectors in the Indonesian Stock Exchange (IDX) during the COVID-19 pandemic. Whereas earlier studies have widely investigated the impact of government interventions on the financial markets during the pandemic, there is lack of research on analysing the financial impacts of various interventions in different industrial sectors, particularly in Indonesia. In this research, five key types of government interventions are selected amid the pandemic from March 2020 to July 2021, including economic stimulus packages, jobs creation law, Jakarta lockdowns, Ramadan travel restrictions, and free vaccination campaign. Based on an event study methodology, the research reveals that the first economic stimulus package was critical in reviving most sectors following the announcement of the first COVID-19 case in Indonesia. Jakarta lockdowns impacted stock returns negatively in most sectors, but the impacts were relatively insignificant in comparison to other countries in the region. The recurrence of lockdowns in Jakarta had a minor detrimental impact, showing that the market had acclimated to the new normal caused by the COVID-19 pandemic. Additionally, Ramadan travel restrictions caused minor negative impacts on the stock market. Furthermore, the second Ramadan travel restrictions generated a significant reaction from the technology sector. Finally, while free vaccination campaign and job creation law did not significantly boost the stock market, both are believed to result in a positive long-term effect on the country’s economy if appropriately executed. The findings are critical for investors, private companies, and governments to build on recovery action plans for major industrial sectors, allowing the stock market to bounce back quickly and efficiently. As this study limits its analysis to the short-term impact of individual interventions, future studies can examine long-term and combined effects of interventions which could also help policy makers to form effective portfolios of interventions in the event of a pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s43546-022-00312-4.

Automated Multi-View Multi-Modal Assessment of COVID-19 Patients Using Reciprocal Attention and Biomedical Transform

Automated severity assessment of coronavirus disease 2019 (COVID-19) patients can help rationally allocate medical resources and improve patients' survival rates. The existing methods conduct severity assessment tasks mainly on a unitary modal and single view, which is appropriate to exclude potential interactive information. To tackle the problem, in this paper, we propose a multi-view multi-modal model to automatically assess the severity of COVID-19 patients based on deep learning. The proposed model receives multi-view ultrasound images and biomedical indices of patients and generates comprehensive features for assessment tasks. Also, we propose a reciprocal attention module to acquire the underlying interactions between multi-view ultrasound data. Moreover, we propose biomedical transform module to integrate biomedical data with ultrasound data to produce multi-modal features. The proposed model is trained and tested on compound datasets, and it yields 92.75% for accuracy and 80.95% for recall, which is the best performance compared to other state-of-the-art methods. Further ablation experiments and discussions conformably indicate the feasibility and advancement of the proposed model.

scPheno: A deep generative model to integrate scRNA-seq with disease phenotypes and its application on prediction of COVID-19 pneumonia and severe assessment (preprint)

Cell-to-cell variability is orchestrated by transcriptional variations participating in different biological processes. However, the dissection of transcriptional variability in specific biological process at single-cell level remains unavailable. Here, we present a deep generative model scPheno to integrate scRNA-seq with disease phenotypes to unravel the invisible phenotype-related transcriptional variations. We applied scPheno on COVID-19 blood scRNA-seq to separate transcriptional variations in regulating COVID-19 host immunity and transcriptional variations in maintaining cell-type identity. In silico, we found CLU+IFI27+S100A9+ monocyte as the efficient cellular marker for the prediction of COVID-19 diagnosis. Inspiringly, using only 4 genes upregulated in CLU+IFI27+S100A9+ monocytes can predict the COVID-19 diagnosis of individuals from different country with an accuracy up to 81.3%. We also found C1+CD163+ monocyte and 8 C1+CD163+ monocyte-upregulated genes as the efficient biomarkers for the prediction of severity assessment. Overall, scPheno is an effective method in dissecting the transcriptional basis of phenotype variations at single-cell level.

Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of Tropical Andean South America: a spatiotemporally disaggregated time series analysis. (preprint)

Background: The COVID-19 pandemic has caused societal disruption globally and South America has been hit harder than other lower-income regions. This study modeled effects of 6 weather variables on district-level SARS-CoV-2 reproduction numbers (Rt) in three contiguous countries of Tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors. Methods: Daily time-series data on SARS-CoV-2 infections were sourced from health authorities of the three countries at the smallest available administrative level. Rt values were calculated and merged by date and unit ID with variables from a Unified COVID-19 dataset and other publicly available sources for May - December 2020. Generalized additive mixed effects models were fitted. Findings: Relative humidity and solar radiation were inversely associated with SARS-CoV-2 Rt. Days with radiation above 1,000 KJ/m2 saw a 1.3%, and those with humidity above 50%, a 1.0% reduction in Rt. Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with least population mobility. Temperature, region, aggregate government policy response and population age structure had little impact. The fully adjusted model explained 3.9% of Rt variance. Interpretation: Dry atmospheric conditions of low humidity increase, and higher solar radiation decrease district-level SARS-CoV-2 reproduction numbers, effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures.

Health equity approach to statewide outreach to under-resourced communities during COVID

OBJECTIVES/GOALS: Despite a disproportionate impact of COVID-19 on minority and under-resourced communities, nearly all COVID-19 resources have only been online in English. A statewide coalition of community and academic partners used community-engaged strategies to provide tailored outreach to diverse populations. METHODS/STUDY POPULATION: The STOP COVID-19 CA statewide team had a workgroup focused on communications. Members of this group represented different sectors, racial/ethnic groups, disciplines, and regions across the state. They had regular meetings to discuss and strategize how to overcome the impact of historic and structural racism on access to COVID-19 resources, including testing, vaccines, and protective equipment. The team also shared regular updates about changes in community concerns and needs as well as new, tailored resources. RESULTS/ANTICIPATED RESULTS: Together, the team has been able to reach diverse populations across the state, including providing information about COVID-19 in multiple languages and formats, from radio to virtual town halls to local health fairs. The multiple sites also increased access to vaccines and testing through trusted community leaders and locations, including church-based locations to bringing vaccines and testing directly to workplaces. These community pop-up vaccination sites have helped to vaccinate large numbers of diverse populations, some of whom were initially unsure about getting the vaccine, which has helped to reduce the gaps in community vaccination rates by race/ethnicity. DISCUSSION/SIGNIFICANCE: This network of community-engaged strategies utilized for rapid COVID-19 response could also be used to for responses to future public health emergencies, addressing chronic diseases (e.g., diabetes, hypertension), or even other complex issues that affect society and health (e.g., climate change).

COVID-19 policies in practice and their direct and indirect impacts in Northern California jails (preprint)

Context: Although the increased risk of COVID-19 in carceral facilities is well documented, little is known about the practical barriers to infection control and indirect impacts of pandemic policies in these settings. Evidence in jails is especially scarce. Methods: Between July 8, 2020 and April 30, 2021 we performed SARS-CoV-2 serology testing and administered a questionnaire among residents and staff in four Northern California jails. We analyzed seroprevalence in conjunction with demographic factors and survey responses of self-perceived COVID-19 risk, recent illness, COVID-19 test results, and symptom reporting behaviors. We additionally assessed COVID-19 policies in practice and evaluated their impacts on court dates, mental health, and routine health care. We engaged stakeholder representatives, including incarcerated individuals and their advocates, to guide study design, conduct, and interpretation. Findings: We enrolled 788 incarcerated individuals and 380 staff across four county jails. Most seropositive individuals had not previously tested positive for COVID-19, despite many suspecting prior infection. Among incarcerated participants, we identified deficient access to face masks and prevalent symptom underreporting associated with fears of isolation and perceptions of medical neglect in jail. Incarcerated participants also reported substantial hindrances to court cases and reductions in routine health care due to COVID-19. Incarcerated individuals and staff both cited worsened mental health due to COVID-19, which for incarcerated individuals was largely attributable to further isolation from loved ones and other pandemic restrictions on recreation and programming. Conclusions: Perceptions of inadequate protection from COVID-19 were pervasive among incarcerated individuals. Simultaneously, restrictive measures compounded poor mental health and fostered fears of isolation that undermined effective infection control. Custody officials should work to systematically improve provision of masks, understand and mitigate fears and mistrust, and take proactive steps to minimize the detrimental impacts of restrictive policies on residents' mental health and well-being.

Milk Small Extracellular Vesicles-derived miRNAs Restrict Porcine Epidemic Diarrhea Virus Infectivity (preprint)

Background: Virus-caused diseases are a huge challenge to both animals and human beings, especially coronaviruses. Porcine epidemic diarrhea virus (PEDV), a coronavirus, causes acute diarrhea and up to 100% mortality in piglets less than three weeks of age. Maternal immunity provides protection for piglets in resisting PEDV infection. Small extracellular vesicles (sEV) contain bioactive molecules such as miRNAs to exchange genetic and epigenetic information between cells. Our previous study suggested that milk sEV facilitated intestinal tract development and prevented LPS-induced intestine damage. However, the effects of milk sEV on the inhibition of viral infections remain unclear. Results: In this study, through in vivo experiments, we found that porcine milk sEV protected piglets from PEDV-induced diarrhea and death. In vitro, we clarified that this protective effect was partly generated through the inhibition of the PEDV-N protein and HMGB1 by sEV miR-let-7e and miR-27b, respectively. Conclusions: In conclusion, we report that porcine milk sEVs protected piglets from PEDV-induced diarrhea and death by inhibiting virus replication, and this protective effect was partly generated through the inhibition of the PEDV-N and HMGB1 pathways by exosomal miR-let-7e and miR-27b. This study reveals a new antiviral function of milk sEVs, and the results suggest that milk sEVs may act as a mother-offspring transmission pathway for protecting newborns against PEDV infection.

Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic (preprint)

An impressive number of COVID-19 data catalogs exist. None, however, are optimized for data science applications, e.g ., inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 case data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, and key demographic characteristics.

Synergistic Inhibition of SARS-CoV-2 Replication using Disulfiram/Ebselen and Remdesivir (preprint)

The SARS-CoV-2 replication and transcription complex (RTC) comprising nonstructural protein (nsp) 2-16 plays crucial roles in viral replication, reducing the efficacy of broad-spectrum nucleoside analog drugs such as remdesivir and in evading innate immune responses. Most studies target a specific viral component of the RTC such as the main protease or the RNA-dependent RNA polymerase. In contrast, our strategy is to target multiple conserved domains of the RTC to prevent SARS-CoV-2 genome replication and to create a high barrier to viral resistance and/or evasion of antiviral drugs. We show that clinically-safe Zn-ejector drugs, disulfiram/ebselen, can target conserved Zn2+-sites in SARS-CoV-2 nsp13 and nsp14 and inhibit nsp13 ATPase and nsp14 exoribonuclease activities. As the SARS-CoV-2 nsp14 domain targeted by disulfiram/ebselen is involved in RNA fidelity control, our strategy allows coupling of the Zn-ejector drug with a broad-spectrum nucleoside analog that would otherwise be excised by the nsp14 proofreading domain. As proof-of-concept, we show that disulfiram/ebselen, when combined with remdesivir, can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells. We present a mechanism of action and the advantages of our multi-targeting strategy, which can be applied to any type of coronavirus with conserved Zn2+-sites.

Incidence and Clinical Impacts of COVID-19 Infection in Patients with Hemodialysis: Systematic Review and Meta-Analysis of 396,062 Hemodialysis Patients (preprint)

Background: Better understanding of incidence and clinical outcomes of COVID-19 infection in hemodialysis (HD) patients could assist healthcare providers to develop proper preventive strategies and optimal management. However, no published systematic review summarizes current epidemiological evidence regarding COVID-19 infection in HD patients.Methods: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We systematically searched PUBMED and EMBASE for articles published on incidence or mortality of COVID-19 infection in maintenance HD patients until September 2020, and conducted meta-analysis of proportions for incidence and mortality rate. Heterogeneity was measured by Cochran’s Q and I2 statistic. Publication bias was evaluated by Egger’s test. The study protocol was registered in the PROSPERO database (CRD42020209134).Results: In total, 29 articles with 3,261 confirmed COVID-19 cases from pooled 396,062 HD patients were identified. Overall COVID-19 incidence in these HD patients was 7.7% (95% CI: 5.0-10.9%), with significant heterogeneity among the studies (I2 = 99.7%, p<0.001) and risk of publication bias (Egger’s test, p<0.001). Overall mortality rate was 22.4% (95% CI: 17.9-27.1%) in HD patients with COVID-19, with significant heterogeneity among the studies (I2 = 87.1%, p<0.001). Reported incidence and mortality varied by geographic area, being higher in non-Asian- than Asian countries.Conclusions: Both incidence and mortality of COVID-19 infection were higher in HD patients. Available data may underestimate the real incidence of infection because screening and diagnosis differ between countries. International collaboration and standardized reporting of future epidemiologic studies is encouraged to improve clinical outcomes of COVID-19 infection in HD patients.

Implications of the COVID-19 San Francisco Bay Area Shelter-in-Place Announcement: A Cross-Sectional Social Media Survey (preprint)

Background: The U.S. has experienced an unprecedented number of shelter-in-place orders throughout the COVID-19 pandemic. There is limited empirical research that examines the impact of these orders. We aimed to rapidly ascertain whether social distancing; difficulty with daily activities (obtaining food, essential medications and childcare); and levels of concern regarding COVID-19 changed after the March 16, 2020 announcement of shelter-in-place orders for seven counties in the San Francisco Bay Area. Methods: We conducted an online, cross-sectional social media survey from March 14 - April 1, 2020. We measured changes in social distancing behavior; experienced difficulties with daily activities (i.e., access to healthcare, childcare, obtaining essential food and medications); and level of concern regarding COVID-19 after the March 16 shelter-in-place announcement in the San Francisco Bay Area and elsewhere in the U.S. Results: The percentage of respondents social distancing all of the time increased following the shelter-in-place announcement in the Bay Area (9.2%, 95% CI: 6.6, 11.9) and elsewhere in the U.S. (3.4%, 95% CI: 2.0, 5.0). Respondents also reported increased difficulty with obtaining food, hand sanitizer, and medications, particularly with obtaining food for both respondents from the Bay Area (13.3%, 95% CI: 10.4, 16.3) and elsewhere (8.2%, 95% CI: 6.6, 9.7). We found limited evidence that level of concern regarding the COVID-19 crisis changed following the shelter-in-place announcement. Conclusion: These results capture early changes in attitudes, behaviors, and difficulties. Further research that specifically examines social, economic, and health impacts of COVID-19, especially among vulnerable populations, is urgently needed. =

The impact of goggle-associated harms to health and working status of nurses during management of COVID-19 (preprint)

Background To investigate the impact of goggles on their health and clinical practice during management of patients with COVID-19. Methods 231 nurse practitioners were enrolled who worked in isolation region in designated hospitals to admit patients with COVID-19 in China. Demographic data, goggle-associated symptoms and underlying reasons, incidence of medical errors or exposures, the effects of fog in goggles on practice were all collected. Data were stratified and analyzed by age or working experience. Risk factors of goggle-associated medical errors were analyzed by multivariable logistical regression analysis. Findings Goggle-associated symptoms and foggy goggles widely presented in nurses. The most common symptoms were headache, skin pressure injury and dizziness. Headache, vomit and nausea were significantly fewer reported in nurses with longer working experience while rash occurred higher in this group. The underlying reasons included tightness of goggles, unsuitable design and uncomfortable materials. The working status of nurses with more working experience was less impacted by goggles. 11.3% nurses occurred medical exposures in clinical practice while 19.5% nurses made medical errors on patients. The risk factors for medical errors were time interval before adapting to goggle-associated discomforts, adjusting goggles and headache. Interpretation Goggle-associated symptoms and fog can highly impact the working status and contribute to medical errors during management of COVID-19. Increased the experience with working in PPE through adequate training and psychological education may benefit for relieving some symptoms and improving working status. Improvement of goggle design during productive process was strongly suggested to reduce incidence of discomforts and medical errors.

Multi-Targeting of Functional Cysteines in Multiple Conserved SARS-CoV-2 Domains by Clinically Safe Zn-ejectors (preprint)

We present a near-term treatment strategy to tackle pandemic outbreaks of coronaviruses with no specific drugs/vaccines by combining evolutionary and physical principles to identify conserved viral domains containing druggable Zn-sites that can be targeted by clinically safe Zn-ejecting compounds. By applying this strategy to SARS-CoV-2 polyprotein-1ab, we predicted multiple labile Zn-sites in papain-like cysteine protease (PLpro), nsp10 transcription factor, and nsp13 helicase. These are attractive drug targets because they are highly conserved among coronaviruses and play vital structural/catalytic roles in viral proteins indispensable for viral replication. We show that five Zn-ejectors can release Zn2+ from PLpro and nsp10, and clinically-safe disulfiram and ebselen can not only covalently bind to the Zn-bound/catalytic cysteines in both proteins, but also inhibit PLpro protease activity. We propose combining disulfiram/ebselen with broad-spectrum antivirals/drugs to target different conserved domains acting at various stages of the virus life cycle to synergistically inhibit SARS-CoV-2 replication and reduce the emergence of drug resistance.