Correction: Complementary recognition of the receptor-binding site of highly pathogenic H5N1 influenza viruses by two human neutralizing antibodies.

Journal of Biological Chemistry(2019)

引用 2|浏览36
暂无评分
摘要
The highly pathogenic avian influenza virus H5N1 is a major threat to global public health and therefore a high-priority target of current vaccine development. The receptor-binding site (RBS) on the globular head of hemagglutinin (HA) in the viral envelope is one of the major target sites for antibody recognition against H5N1 and other influenza viruses. Here, we report the identification and characterization of a pair of human RBS-specific antibodies, designated FLD21.140 and AVFluIgG03, that are mutually complementary in their neutralizing activities against a diverse panel of H5N1 viruses. Crystallographic analysis and site-directed mutagenesis revealed that the two antibodies share a similar RBS-binding mode, and their individual specificities are governed by residues at positions 133a, 144, and 145. Specifically, FLD21.140 preferred Leu-133a/Lys-144/Ser-145, whereas AVFluIgG03 favored Ser-133a/Thr-144/Pro-145 residue triplets, both of which perfectly matched the most prevalent residues in viruses from epidemic-originating regions. Of note, according to an analysis of 3758 H5 HA sequences available in the Influenza Virus Database at the National Center for Biotechnology Information, the residues Leu-133a/Ser-133a and Ser-145/Pro-145 constituted more than 87.6 and 99.3% of all residues at these two positions, respectively. Taken together, our results provide a structural understanding for the neutralizing complementarity of these two antibodies and improve our understanding of the RBS-specific antibody response against H5N1 infection in humans.
更多
查看译文
关键词
influenza,influenza virus,monoclonal antibody,structural biology,X-ray crystallography,vaccine development,virology,mutagenesis,infectious disease,antigenic variation,escape mutants,H5N1,HPAI,neutralizing antibodies,receptor-binding site,antiviral vaccine
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要