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Linear epitopes of SARS-CoV-2 spike protein elicit neutralizing antibodies in COVID-19 patients
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作者 Yang Li Dan-yun Lai +14 位作者 Hai-nan Zhang He-wei Jiang Xiaolong Tian Ming-liang Ma Huan Qi Qing-feng Meng Shu-juan Guo Yanling Wu Wei Wang Xiao Yang Da-wei Shi Jun-biao Dai Tianlei Ying Jie Zhou Sheng-ce Tao 《Cellular & Molecular Immunology》 CSCD 2020年第10期1095-1097,共3页
COVID-19 is caused by SARS-CoV-2.1,2 By July 25,2020,globally,15,672,841 diagnosed cases and 638,352 deaths were reported(https://coronavirus.jhu.edu/map.html).3 High titers of Spike protein(S protein)-specific antibo... COVID-19 is caused by SARS-CoV-2.1,2 By July 25,2020,globally,15,672,841 diagnosed cases and 638,352 deaths were reported(https://coronavirus.jhu.edu/map.html).3 High titers of Spike protein(S protein)-specific antibodies are found in the blood of COVID-19 patients,especially IgG for both SARS-CoV4 and SARS-CoV-2.5,6 Because of the central role that S protein plays in the entry of the virus into the host cell,S1 and,more specifically,the RBD(receptorbinding domain)is the most targeted region for the development of COVID-19 therapeutic antibodies7,8 and vaccines.9 It is known that in addition to the RBD,other areas/epitopes of S protein may also elicit neutralizing antibodies.10 However,antibody responses to full-length S protein have not been investigated at epitope resolution,and the capability of linear epitopes to elicit neutralizing antibodies has still not been explored. 展开更多
关键词 SARS CoV IGG Neutralizing antibodies linear epitopes S protein RBD COVID s protein
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Identification of the Epitopes of Monoclonal Antibodies against P74 of Helicoverpa armigera Nucleopolyhedrovirus
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作者 Limin Liao Dianhai Hou +5 位作者 Huachao Huang Manli Wang Fei Deng Hualin Wang Zhihong Hu Tao Zhang 《Virologica Sinica》 SCIE CAS CSCD 2013年第6期360-367,共8页
P74 is a per os infectivity factor of baculovirus.Here,we report the production of three monoclonal antibodies (mAbs),denoted as 20D9,20F9 and 21E1,raised against P74 of Helicoverpa armigera nucleopolyhedrovirus (Hear... P74 is a per os infectivity factor of baculovirus.Here,we report the production of three monoclonal antibodies (mAbs),denoted as 20D9,20F9 and 21E1,raised against P74 of Helicoverpa armigera nucleopolyhedrovirus (HearNPV),and the identification of their recognition epitopes.The full-length P74,without the transmembrane domains at the C-terminus,was first divided into three segments (N,M and C,respectively),based on the proposed cleavage model for the protein,which were then expressed individually.Western blot analyses revealed specific cross-reactions with the N fragment,for both 20D9 and 21E1.Extensive truncation,followed by prokaryotic expression,of the P74 N fragment was then performed in order to screen for linear epitopes of P74.The recognition regions of 20D9 and 21E1 were revealed to be localized at R144-T153 and T199-C219,respectively.In addition,immunofluorescence microscopy indicated that 20D9 and 20F9 could recognize native P74 in HearNPV-infected cells.These findings will facilitate further investigations of the proteolytic processing of HearNPV P74,and of its involvement in virus-host interactions. 展开更多
关键词 HEARNPV P74 linear epitope Monoclonal antibody
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iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features
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作者 Md.Mehedi Hasan Mst.Shamima Khatun Hiroyuki Kurata 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2020年第5期593-600,共8页
Linear B-cell epitopes are critically important for immunological applications,such as vaccine design,immunodiagnostic test,and antibody production,as well as disease diagnosis and therapy.The accurate identification ... Linear B-cell epitopes are critically important for immunological applications,such as vaccine design,immunodiagnostic test,and antibody production,as well as disease diagnosis and therapy.The accurate identification of linear B-cell epitopes remains challenging despite several decades of research.In this work,we have developed a novel predictor,Identification of Linear B-cell Epitope(i LBE),by integrating evolutionary and sequence-based features.The successive feature vectors were optimized by a Wilcoxon-rank sum test.Then the random forest(RF)algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell epitopes.We combined the RF scores by the logistic regression to enhance the prediction accuracy.iLBE yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent dataset.iLBE is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests.A web application with curated datasets for iLBE is freely accessible at http://kurata14.bio.kyutech.ac.jp/iLBE/. 展开更多
关键词 linear B-cell epitope BLAST Feature encoding Feature selection Random forest
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