艾滋病疫苗
抗体
病毒学
免疫
人类免疫缺陷病毒(HIV)
艾滋病疫苗
生物
免疫系统
选择(遗传算法)
中和抗体
免疫学
计算生物学
计算机科学
疫苗试验
人工智能
作者
Kevin O. Saunders,Kevin Wiehe,Ming Tian,Priyamvada Acharya,Todd Bradley,S. Munir Alam,Eden P. Go,Richard M. Scearce,Laura L. Sutherland,Rory Henderson,Allen L. Hsu,Mario J. Borgnia,Haiyan Chen,Xiaozhi Lu,Nelson R. Wu,Brian Watts,Chuancang Jiang,David Easterhoff,Hwei-Ling Cheng,Kelly McGovern
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2019-12-05
卷期号:366 (6470)
被引量:170
标识
DOI:10.1126/science.aay7199
摘要
Engineering better bnAbs A highly effective HIV vaccine has been the goal of vaccinologists for nearly 35 years. A successful vaccine would need to induce broadly neutralizing antibodies (bnAbs) that are capable of neutralizing multiple HIV strains (see the Perspective by Agazio and Torres). Steichen et al. report a strategy in which the first vaccine shot can lead to immune responses that generate desired bnAbs. By combining knowledge of human antibody repertoires and structure to guide design, they validated candidate immunogens through functional preclinical testing. Saunders et al. designed immunogens with differences in binding strength for bnAb precursors, which enabled selection of rare mutations after immunization. The immunogens promoted bnAb precursor maturation in humanized mice and macaques. Science , this issue p. eaax4380 , p. eaay7199 ; see also p. 1197
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