Barcelona Supercomputing Center (BSC), Barcelona, Spain.
CELLEX Research Laboratories, CibeRes (Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Front Immunol. 2023 Dec 6;14:1278534. doi: 10.3389/fimmu.2023.1278534. eCollection 2023.
The application of B-cell epitope identification to develop therapeutic antibodies and vaccine candidates is well established. However, the validation of epitopes is time-consuming and resource-intensive. To alleviate this, in recent years, multiple computational predictors have been developed in the immunoinformatics community. Brewpitopes is a pipeline that curates bioinformatic B-cell epitope predictions obtained by integrating different state-of-the-art tools. We used additional computational predictors to account for subcellular location, glycosylation status, and surface accessibility of the predicted epitopes. The implementation of these sets of rational filters optimizes antibody recognition properties of the candidate epitopes. To validate Brewpitopes, we performed a proteome-wide analysis of SARS-CoV-2 with a particular focus on S protein and its variants of concern. In the S protein, we obtained a fivefold enrichment in terms of predicted neutralization versus the epitopes identified by individual tools. We analyzed epitope landscape changes caused by mutations in the S protein of new viral variants that were linked to observed immune escape evidence in specific strains. In addition, we identified a set of epitopes with neutralizing potential in four SARS-CoV-2 proteins (R1AB, R1A, AP3A, and ORF9C). These epitopes and antigenic proteins are conserved targets for viral neutralization studies. In summary, Brewpitopes is a powerful pipeline that refines B-cell epitope bioinformatic predictions during public health emergencies in a high-throughput capacity to facilitate the optimization of experimental validation of therapeutic antibodies and candidate vaccines.
B 细胞表位鉴定在开发治疗性抗体和疫苗候选物方面的应用已经得到了很好的证实。然而，表位的验证既耗时又耗资源。为了解决这个问题，近年来，免疫信息学领域已经开发出了多种计算预测器。Brewpitopes 是一个管道，它通过整合不同的最先进的工具来管理生物信息学 B 细胞表位预测。我们使用了额外的计算预测器来考虑预测表位的亚细胞位置、糖基化状态和表面可及性。这些合理的过滤器的实现优化了候选表位的抗体识别特性。为了验证 Brewpitopes，我们对 SARS-CoV-2 进行了全蛋白质组分析，特别关注 S 蛋白及其关注的变体。在 S 蛋白中，与单个工具识别的表位相比，预测的中和作用增加了五倍。我们分析了 S 蛋白突变引起的表位景观变化，这些突变与特定菌株中观察到的免疫逃逸证据有关。此外，我们还鉴定了一组在四种 SARS-CoV-2 蛋白（R1AB、R1A、AP3A 和 ORF9C）中具有中和潜力的表位。这些表位和抗原蛋白是病毒中和研究的保守靶标。总之，Brewpitopes 是一个强大的管道，它可以在公共卫生紧急情况下以高通量的方式对 B 细胞表位生物信息学预测进行优化，从而促进治疗性抗体和候选疫苗的实验验证的优化。
