ABSTRACT
The newly identified 2019 novel coronavirus (2019-nCoV) has caused more than 81,400 laboratory-confirmed human infections, including 3261 deaths, posing a serious threat to human health. Currently, however, there is no specific antiviral treatment or vaccine. To identify immunodominant peptides for designing global peptide vaccine for combating the infections caused by 2019-nCoV, the structure and immunogenicity of 2019-nCoV structural protein were analyzed by bioinformatics tools. 33 B-cell epitopes and 39 T-cell epitopes were determined in four structural proteins via different immunoinformatic tools in which include spike protein (22 B-cell epitopes, 25 T-cell epitopes ), nucleocapsid protein (7 B-cell epitopes, 6 T-cell epitopes), membrane protein (2 B-cell epitopes, 7 T-cell epitopes), and envelope protein (2 B-cell epitopes, 1T-cell epitopes), respectively. The proportion of epitope residues in primary sequence was used to determine the antigenicity and immunogenicity of proteins. The envelope protein has the largest antigenicity in which residue coverage of B-cell epitopes is 24%. The membrane protein possesses the largest immunogenicity in which residue coverage of T-cell epitopes is 55.86%. The reason that immune storm was caused by 2019-nCoV maybe that the membrane and envelope protein expressed plentifully in cell infected. Further, studies involving experimental validation of these predicted epitopes is warranted to ensure the potential of B-cells and T-cells stimulation for their effective use as vaccine candidates. These findings provide the basis for starting further studies on the pathogenesis, and optimizing the design of diagnostic, antiviral and vaccination strategies for this emerging infection.
Subject(s)
Emergencies , DeathABSTRACT
OBJECTIVE Clinical characteristics of novel coronavirus pneumonia (COVID-19) have been described in numerous studies but yielded varying results. We aimed to conduct a systematic review on scientific literatures and to synthesize critical data on clinical traits of COVID-19 from its initial outbreak to pandemic. METHODS Systematic searches were conducted to identify retrospective observational study that contained clinical characteristics on COVID-19 through multiple databases. Two reviewers independently evaluated eligible publications. Data on clinical characteristics of COVID-19 were extracted and analyzed. RESULTS Seventy-two retrospective studies demonstrating the clinical characteristics of COVID-19 were included. A total of 3470 COVID-19 patients were synthesized to the final analysis in an unbiased manner. The most common symptom was fever (2878 [83.0%]), and 63.4% of the patients presented fever as onset symptom. There were 2528 [88.2%] of 2866 cases had abnormal lung findings on chest CT scan. Laboratory findings showed that 1498 [62.8%] of 2387 cases had lymphopenia, and 1354 [64.8%] of 2091 cases had an increased level of C-reactive protein (CRP). A total of 185 [11.5%] patients were admitted to intensive care unit (ICU) while the overall case fatality rate (CFR) was 3.7%. Compared to patients admitted outside of Hubei, China, those from Hubei had a significant higher ICU admission rate (21.9% vs. 2.5%, p<0.001). Also, CFR attributed to COVID-19 was significantly higher in Hubei than that of non-Hubei admissions (10.4% vs. 0.6%, p<0.001). INTERPRETATION This large patient-based systematic review presents a more precise profiling of the COVID-19 from its outbreak to current pandemic. Dynamic evolvements of COVID-19 are needed to be characterized in future studies.