Glycosylation profiling to evaluate glycoprotein immunogens against HIV-1.
Glycosylation profiling to evaluate glycoprotein immunogens against HIV-1.
复制标题
DOI：
10.1080/14789450.2017.1376658
复制
发表时间：
2017-10
影响因子：
3.4
通讯作者：
Crispin M
中科院分区：
文献类型：
--
作者：
Behrens AJ;Struwe WB;Crispin M
开发人类免疫缺陷病毒（HIV）疫苗的大部分努力都集中在病毒附着糖蛋白（Env）的重组模拟物的设计上。主要的免疫原表现出类似于天然抗原的特性，目前正在研究它们诱导广泛中和抗体（bNAbs）的能力。了解这些免疫原上特定糖基化位点聚糖的相对丰度是很重要的，因为大多数bnab已经进化到能够识别或逃避覆盖在蛋白质表面的密集聚糖外壳。了解候选免疫原上的聚糖结构可以在天然构象和缺乏关键结构特征的免疫原之间进行筛选，因为空间约束限制了聚糖的加工。特定聚糖的加工状态对其结构环境的敏感性导致需要定量的聚糖分析和位点特异性分析来探测免疫原的结构完整性。我们回顾了HIV免疫原评估的分析方法，并讨论了这些研究如何导致对控制HIV附着和融合尖峰的糖基化状态的结构约束的更好理解。总组成和位点特异性糖基化分析正在成为评估基于env的候选免疫原的标准方法。
Much of the efforts to develop a vaccine against the human immunodeficiency virus (HIV) have focused on the design of recombinant mimics of the viral attachment glycoprotein (Env). The leading immunogens exhibit native-like antigenic properties and are being investigated for their ability to induce broadly neutralizing antibodies (bNAbs). Understanding the relative abundance of glycans at particular glycosylation sites on these immunogens is important as most bNAbs have evolved to recognize or evade the dense coat of glycans that masks much of the protein surface. Understanding the glycan structures on candidate immunogens enables triaging between native-like conformations and immunogens lacking key structural features as steric constraints limit glycan processing. The sensitivity of the processing state of a particular glycan to its structural environment has led to the need for quantitative glycan profiling and site-specific analysis to probe the structural integrity of immunogens. We review analytical methodologies for HIV immunogen evaluation and discuss how these studies have led to a greater understanding of the structural constraints that control the glycosylation state of the HIV attachment and fusion spike. Total composition and site-specific glycosylation profiling are emerging as standard methods in the evaluation of Env-based immunogen candidates.
登录
查看更多内容
影响因子：
2.9
作者：
Cao L;Tolić N;Qu Y;Meng D;Zhao R;Zhang Q;Moore RJ;Zink EM;Lipton MS;Paša-Tolić L;Wu S
通讯作者：
Wu S
影响因子：
8.8
作者：
Torrents de la Peña A;Julien JP;de Taeye SW;Garces F;Guttman M;Ozorowski G;Pritchard LK;Behrens AJ;Go EP;Burger JA;Schermer EE;Sliepen K;Ketas TJ;Pugach P;Yasmeen A;Cottrell CA;Torres JL;Vavourakis CD;van Gils MJ;LaBranche C;Montefiori DC;Desaire H;Crispin M;Klasse PJ;Lee KK;Moore JP;Ward AB;Wilson IA;Sanders RW
通讯作者：
Sanders RW
影响因子：
32.4
作者：
Falkowska, Emilia;Le, Khoa M.;Ramos, Alejandra;Doores, Katie J.;Lee, Jeong Hyun;Blattner, Claudia;Ramirez, Alejandro;Derking, Ronald;van Gils, Marit J.;Liang, Chi-Hui;Mcbride, Ryan;von Bredow, Benjamin;Shivatare, Sachin S.;Wu, Chung-Yi;Chan-Hui, Po-Ying;Liu, Yan;Feizi, Ten;Zwick, Michael B.;Koff, Wayne C.;Seaman, Michael S.;Swiderek, Kristine;Moore, John P.;Evans, David;Paulson, James C.;Wong, Chi-Huey;Ward, Andrew B.;Wilson, Ian A.;Sanders, Rogier W.;Poignard, Pascal;Burton, Dennis R.
通讯作者：
Burton, Dennis R.
影响因子：
4.4
作者：
Go, Eden P.;Hua, David;Desaire, Heather
通讯作者：
Desaire, Heather
影响因子：
3.8
作者：
Cassol, Edana;Cassetta, Luca;Poli, Guido
通讯作者：
Poli, Guido