Corpus overview


MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

ProteinS (2072)

ProteinN (547)

NSP5 (412)

ComplexRdRp (249)

ProteinE (144)


SARS-CoV-2 Proteins
    displaying 26101 - 26110 records in total 26277
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    Structural genomics and interactomics of 2019 Wuhan novel coronavirus, 2019-nCoV, indicate evolutionary conserved functional regions of viral proteins

    Authors: Hongzhu Cui; Ziyang Gao; Ming Liu; Senbao Lu; Winnie Mkandawire; Sun Mo; Oleksandr Narykov; Suhas Srinivasan; Dmitry Korkin

    doi:10.1101/2020.02.10.942136 Date: 2020-02-14 Source: bioRxiv

    During its first month, the recently emerged 2019 Wuhan novel coronavirus (2019-nCoV) has already infected many thousands of people in mainland China and worldwide and took hundreds of lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection MESHD and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge we leverage the data about the related coronaviruses that is readily available in public databases, and integrate these data into a single computational pipeline. As a result, we provide a comprehensive structural genomics and interactomics road-maps of 2019-nCoV and use these information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community at

    Trend and forecasting of the COVID-19 MESHD outbreak in China

    Authors: Qiang Li; Wei Feng

    id:2002.05866v1 Date: 2020-02-14 Source: arXiv

    By using the public data from Jan. 20 to Feb. 11 HGNC, 2020, we perform data-driven analysis and forecasting on the COVID-19 MESHD epidemic in mainland China, especially Hubei province. Our results show that the turning points of the daily infections are predicted to be Feb. 6 and Feb. 1, 2020, for Hubei and China other than Hubei, respectively. The epidemic in China is predicted to end up after Mar. 10, 2020, and the number of the total infections are predicted to be 51600. The data trends reveal that quick and active strategies taken by China to reduce human exposure have already had a good impact on the control of the epidemic.

    A spatial model of CoVID-19 MESHD transmission in England and Wales: early spread and peak timing

    Authors: Leon Danon; Ellen Brooks-Pollock; Mick Bailey; Matt J Keeling

    doi:10.1101/2020.02.12.20022566 Date: 2020-02-14 Source: medRxiv

    Background: An outbreak of a novel coronavirus, named CoVID-19 MESHD, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England. Methods: We adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 MESHD in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China. Results: We predict that a CoVID-19 MESHD outbreak will peak 126 to 147 days (~4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate. Discussion: We provide initial estimates of the potential course of CoVID-19 MESHD in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for healthcare capacity planning.

    Understanding the present status and forecasting of COVID-19 MESHD in Wuhan

    Authors: Toshihisa Tomie

    doi:10.1101/2020.02.13.20022251 Date: 2020-02-14 Source: medRxiv

    The present status of COVID[-]19 is analyzed and the end of the disease is forecasted. The peak of the epidemic is different in three regions, Wuhan, Hubei province except Wuhan, and mainland China except Hubei. In two regions except Wuhan, the peak of the epidemic passed ten days ago. If the trend until February 11 does not change, the disease may end by the end of February. In Wuhan, the epidemic reached a peak but the reported number of newly infected MESHD patients fluctuates largely. We need to know the reason for the big fluctuation to forecast the end of the disease.

    Visual Data Analysis and Simulation Prediction for COVID-19 MESHD

    Authors: Baoquan Chen; Mingyi Shi; Xingyu Ni; Liangwang Ruan; Hongda Jiang; Heyuan Yao; Mengdi Wang; Zhenhua Song; Qiang Zhou; Tong Ge

    id:2002.07096v3 Date: 2020-02-14 Source: arXiv

    The COVID-19 MESHD (formerly, 2019-nCoV) epidemic has become a global health emergency, as such, WHO declared PHEIC. China has taken the most hit since the outbreak of the virus, which could be dated as far back as late November by some experts. It was not until January 23rd that the Wuhan government finally recognized the severity of the epidemic and took a drastic measure to curtain the virus spread by closing down all transportation connecting the outside world. In this study, we seek to answer a few questions: How did the virus get spread from the epicenter Wuhan city to the rest of the country? To what extent did the measures, such as, city closure and community quarantine, help controlling the situation? More importantly, can we forecast any significant future development of the event had some of the conditions changed? By collecting and visualizing publicly available data, we first show patterns and characteristics of the epidemic development; we then employ a mathematical model of disease transmission dynamics to evaluate the effectiveness of some epidemic control measures, and more importantly, to offer a few tips on preventive measures.

    Structural modeling of 2019-novel coronavirus (nCoV) spike protein PROTEIN reveals a proteolytically-sensitive activation loop as a distinguishing feature compared to SARS-CoV and related SARS-like coronaviruses

    Authors: Javier A. Jaimes; Nicole M. Andre; Jean K. Millet; Gary R. Whittaker

    id:2002.06196v1 Date: 2020-02-14 Source: arXiv

    The 2019 novel coronavirus (2019-nCoV) is currently causing a widespread outbreak centered on Hubei province, China and is a major public health concern. Taxonomically 2019-nCoV is closely related to SARS-CoV MESHD and SARS-related bat coronaviruses, and it appears to share a common receptor with SARS-CoV MESHD (ACE-2). Here, we perform structural modeling of the 2019-nCoV spike glycoprotein PROTEIN. Our data provide support for the similar receptor utilization between 2019-nCoV and SARS-CoV MESHD, despite a relatively low amino acid similarity in the receptor binding module. Compared to SARS-CoV MESHD, we identify an extended structural loop containing basic amino acids at the interface of the receptor binding (S1) and fusion (S2) domains, which we predict to be proteolytically-sensitive. We suggest this loop confers fusion activation and entry properties more in line with MERS-CoV MESHD and other coronaviruses, and that the presence of this structural loop in 2019-nCoV may affect virus stability and transmission.

    Identification of a pangolin niche for a 2019-nCoV-like coronavirus through an extensive meta-metagenomic search

    Authors: Lamia Wahba; Nimit Jain; Andrew Z Fire; Massa J Shoura; Karen L Artiles; Matthew J McCoy; Dae Eun Jeong

    doi:10.1101/2020.02.08.939660 Date: 2020-02-14 Source: bioRxiv

    In numerous instances, tracking the biological significance of a nucleic acid sequence can be augmented through the identification of environmental niches in which the sequence of interest is present. Many metagenomic datasets are now available, with deep sequencing of samples from diverse biological niches. While any individual metagenomic dataset can be readily queried using web-based tools, meta-searches through all such datasets are less accessible. In this brief communication, we demonstrate such a meta-meta-genomic approach, examining close matches to the Wuhan coronavirus 2019-nCoV in all high-throughput sequencing datasets in the NCBI Sequence Read Archive accessible with the keyword "virome". In addition to the homology to bat coronaviruses observed in descriptions of the 2019-nCoV sequence (F. Wu et al. 2020, Nature,; P. Zhou et al. 2020, Nature,, we note a strong homology to numerous sequence reads in a metavirome dataset generated from the lungs of deceased Pangolins reported by Liu et al. (Viruses 11:11, 2019, Our observations are relevant to discussions of the derivation of 2019-nCoV and illustrate the utility and limitations of meta-metagenomic search tools in effective and rapid characterization of potentially significant nucleic acid sequences. ImportanceMeta-metagenomic searches allow for high-speed, low-cost identification of potentially significant biological niches for sequences of interest.

    Single-cell RNA expression profiling of ACE2 HGNC, the putative receptor of Wuhan 2019-nCoV, in the nasal tissue

    Authors: CHAO WU; Shufa Zheng; Yu Chen; Min Zheng

    doi:10.1101/2020.02.11.20022228 Date: 2020-02-13 Source: medRxiv

    A novel coronavirus (2019-nCoV) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. WHO decides to determine a Public Health Emergency of International Concern (PHEIC) of 2019-nCoV. 2019-nCov was reported to share the same receptor, Angiotensin-converting enzyme 2 HGNC ( ACE2 HGNC), with SARS-Cov. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 HGNC RNA expression profile in the tissues at different locations of the respiratory tract. The result indicates that the ACE2 HGNC expression appears in nasal epithelial cells. We found that the size of this population of ACE2 HGNC-expressing nasal epithelial cells is comparable with the size of the population of ACE2 HGNC-expression type II alveolar MESHD cells (AT2) in the Asian sample reported by Yu Zhao et al. We further detected 2019-nCoV by polymerase chain reaction (PCR) from the nasal-swab and throat-swab of seven suspected cases. We found that 2019-nCoV tends to have a higher concentration in the nasal-swab comparing to the throat-swab, which could attribute to the ACE2 HGNC-expressing nasal epithelial cells. We hope this study could be informative for virus-prevention strategy development, especially the treatment of nasal mucus.

    ACE2 HGNC Expression in Kidney and Testis May Cause Kidney and Testis Damage After 2019-nCoV Infection MESHD

    Authors: Caibin Fan; Kai Li; Yanhong Ding; Wei Lu Lu; Jianqing Wang

    doi:10.1101/2020.02.12.20022418 Date: 2020-02-13 Source: medRxiv

    In December 2019 and January 2020, novel coronavirus (2019-nCoV) - infected pneumonia MESHD (NCIP) occurred in Wuhan, and has already posed a serious threat to public health. ACE2 HGNC ( Angiotensin Converting Enzyme 2 HGNC) has been shown to be one of the major receptors that mediate the entry of 2019-nCoV into human cells, which also happens in severe acute respiratory syndrome coronavirus MESHD (SARS). Several researches have indicated that some patients have abnormal renal function MESHD or even kidney damage MESHD in addition to injury in respiratory system, and the related mechanism is unknown. This arouses our interest in whether coronavirus infection MESHD will affect the urinary and male reproductive systems. Here in this study, we used the online datasets to analyze ACE2 HGNC expression in different human organs. The results indicate that ACE2 HGNC highly expresses in renal tubular cells, Leydig cells and cells in seminiferous ducts in testis. Therefore, virus might directly bind to such ACE2 HGNC positive cells and damage the kidney and testicular tissue of patients. Our results indicate that renal function evaluation and special care should be performed in 2019-nCoV patients during clinical work, because of the kidney damage MESHD caused by virus and antiviral drugs with certain renal toxicity MESHD. In addition, due to the potential pathogenicity of the virus to testicular tissues, clinicians should pay attention to the risk of testicular lesions MESHD in patients during hospitalization and later clinical follow-up, especially the assessment and appropriate intervention in young patients' fertility.

    Serial interval of novel coronavirus (2019-nCoV) infections

    Authors: Hiroshi Nishiura; Natalie M Linton; Andrei R. Akhmetzhanov

    doi:10.1101/2020.02.03.20019497 Date: 2020-02-13 Source: medRxiv

    Objective: To estimate the serial interval of novel coronavirus ( COVID-19 MESHD) from information on 28 infector-infectee pairs. Methods: We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n=28) and a subset of pairs with highest certainty in reporting (n=18). In addition, we adjusting for right truncation of the data as the epidemic is still in its growth phase. Results: Accounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9). Conclusions: The serial interval of COVID-19 MESHD is shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 MESHD serial interval is also shorter than the serial interval of severe acute respiratory syndrome MESHD (SARS), indicating that calculations made using the SARS serial interval may introduce bias.

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

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