Di Silvestre Dario, Brambilla Francesca, Merlini Giampaolo, Mauri Pierluigi
Institute for Biomedical Technologies - National Research Council (ITB-CNR), Segrate, Milan, Italy.
Amyloidosis Research and Treatment Centre, Fondazione IRCCS Policlinico San Matteo and University of Pavia, Pavia, Italy.
Methods Mol Biol. 2025;2884:369-387. doi: 10.1007/978-1-0716-4298-6_22.
Amyloidosis diseases are characterized by protein misfolding, which forms insoluble beta-sheet fibrils progressively deposited in tissues. Deposition in the form of amyloid aggregates can occur in various organs, damaging their structure and function. The hallmark of amyloidosis is aberrant interactions leading to protein aggregation and proteotoxicity. Accordingly, amyloidosis-related samples represent a valuable source of information to generate new knowledge useful for diagnostic, prognostic, and therapeutic purposes. In this scenario, we outline the path to apply computational methods and strategies based on the combination of proteomics and systems biology approaches. In addition to algorithms useful for subtyping amyloid deposits or assessing proteome recovery after drug treatment, our chapter provides workflows based on protein-protein interaction and protein co-expression network models. In particular, the main steps to reconstruct and analyze them at both functional and topological levels are described. Our chapter aims to provide tools and instructions to identify and monitor prognostic, diagnostic, and therapeutic markers and to shed light on the processes, pathways, and functions affected by amyloidogenic proteins.
淀粉样变性疾病的特征是蛋白质错误折叠，形成不溶性β-折叠原纤维并逐渐沉积在组织中。淀粉样聚集体形式的沉积可发生在各种器官中，损害其结构和功能。淀粉样变性的标志是异常相互作用导致蛋白质聚集和蛋白毒性。因此，与淀粉样变性相关的样本是产生有助于诊断、预后和治疗目的新知识的宝贵信息来源。在这种情况下，我们概述了应用基于蛋白质组学和系统生物学方法相结合的计算方法和策略的途径。除了可用于淀粉样沉积物亚型分类或评估药物治疗后蛋白质组恢复情况的算法外，我们的章节还提供了基于蛋白质-蛋白质相互作用和蛋白质共表达网络模型的工作流程。特别是，描述了在功能和拓扑层面重建和分析它们的主要步骤。我们的章节旨在提供工具和指导，以识别和监测预后、诊断和治疗标志物，并阐明受淀粉样蛋白影响的过程、途径和功能。
