Enhancement of the HIV Antibody Database tool for Open Science

项目摘要 我们P01 HIVRAD项目的目标是推动我们针对HIV-1的生殖系靶向方法 通过在转基因小鼠和猕猴中进行免疫原设计和测试的循环来设计疫苗。 这项P01拨款中建议的实验将产生候选免疫原，用于在 由合作者马尔科姆·马丁博士和人类进行疫苗试验的猕猴。一项创新 该项目的一个方面是其结构确定和免疫原的综合方法 设计、选择和评估--解决结构问题的人员也参与其中 免疫基因设计和筛选，允许快速和知情的迭代周期 免疫原的改进。 作为这种综合方法的一部分，比约克曼实验室开发了该软件包 HIV抗体数据库，旨在无障碍地访问、比较 以及广谱中和抗HIV抗体序列、结构和中和分析 数据。该计划包括一个数据分析工具，用于识别HIV-1环境序列特征 负责中和/结合效力在不同菌株之间的变化。这一创新工具具有 允许我们使用结构组合来确定抗体/环境界面上的关键相互作用 和生物信息学分析。我们建议通过以下方式加强艾滋病毒抗体数据库工具 通过整合公开可用的数据流来提高其稳健性和可持续性， 采用结构化数据输入输出的标准格式，优化性能， 集成比约克曼实验室开发的另一个程序Variant数据库，该程序可以 质疑一种病毒式突变的格局。变异数据库可快速搜索SARS-CoV-2基因组 拥有超过一百万个序列的数据集。因此，它可以用来检测新出现的突变 在传统的系统发育分析中可能被忽视的模式。我们建议 通用化变异数据库以分析不同的病毒分类群，包括HIV-1。变体数据库 将增强为更强大和可持续，该版本将与艾滋病毒整合 抗体数据库。

Project Summary The goal of our P01 HIVRAD Project is to advance our germline-targeting approach to HIV-1 vaccine design by cycles of immunogen design and testing in transgenic mice and macaques. The experiments proposed in this P01 grant will produce candidate immunogens for testing in macaques by collaborator Dr. Malcolm Martin and for vaccine trials in humans. One innovative aspect of the project is its integrated approach to structure determination and immunogen design, selection, and evaluation - the same people solving structures are also involved with immunogen design and screening, allowing a rapid and informed cycle of iterative improvements of immunogens. As part of this integrated approach, the Bjorkman lab has developed the software package HIV Antibody Database, which was designed to enable frictionless access to, comparisons of, and analyses of broadly neutralizing anti-HIV antibody sequences, structures, and neutralization data. This program includes a data analysis tool to identify HIV-1 Env sequence features responsible for neutralization/binding potency variability across strains. This innovative tool has allowed us to determine key interactions at Ab/Env interfaces using a combination of structural and bioinformatics analyses. We propose to enhance the HIV Antibody Database tool by improving its robustness and sustainability by integrating publicly available data streams, adopting standard formats for input and output of structural data, optimizing performance, and integrating another program developed by the Bjorkman lab, Variant Database, which can query a viral mutational landscape. Variant Database can quickly search SARS-CoV-2 genome datasets with over a million sequences. Thus, it can be used to detect emerging mutation patterns that might be overlooked in conventional phylogenetic analyses. We propose to generalize Variant Database to analyze different virus taxa, including HIV-1. Variant Database will be enhanced to be more robust and sustainable, and this version will be integrated with HIV Antibody Database.