Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fuzhou 350004, China.
Brief Bioinform. 2024 Sep 23;25(6). doi: 10.1093/bib/bbae519.
Protein degradation through the ubiquitin proteasome system at the spatial and temporal regulation is essential for many cellular processes. E3 ligases and degradation signals (degrons), the sequences they recognize in the target proteins, are key parts of the ubiquitin-mediated proteolysis, and their interactions determine the degradation specificity and maintain cellular homeostasis. To date, only a limited number of targeted degron instances have been identified, and their properties are not yet fully characterized. To tackle on this challenge, here we develop a novel deep-learning framework, namely MetaDegron, for predicting E3 ligase targeted degron by integrating the protein language model and comprehensive featurization strategies. Through extensive evaluations using benchmark datasets and comparison with existing method, such as Degpred, we demonstrate the superior performance of MetaDegron. Among functional features, MetaDegron allows batch prediction of targeted degrons of 21 E3 ligases, and provides functional annotations and visualization of multiple degron-related structural and physicochemical features. MetaDegron is freely available at http://modinfor.com/MetaDegron/. We anticipate that MetaDegron will serve as a useful tool for the clinical and translational community to elucidate the mechanisms of regulation of protein homeostasis, cancer research, and drug development.
蛋白质通过泛素蛋白酶体系统在时空上的降解调控对于许多细胞过程是必不可少的。E3 连接酶和降解信号（degrons），即它们在靶蛋白中识别的序列，是泛素介导的蛋白水解的关键部分，它们的相互作用决定了降解的特异性并维持细胞内的稳态。迄今为止，只有有限数量的靶向 degron 实例被识别，它们的特性尚未完全表征。为了应对这一挑战，我们在这里开发了一种新的深度学习框架，即 MetaDegron，通过整合蛋白质语言模型和全面的特征化策略来预测 E3 连接酶靶向的 degron。通过使用基准数据集进行广泛评估，并与现有的方法（如 Degpred）进行比较，我们证明了 MetaDegron 的优越性能。在功能特征方面，MetaDegron 允许对 21 种 E3 连接酶的靶向 degron 进行批量预测，并提供多个 degron 相关结构和物理化学特征的功能注释和可视化。MetaDegron 可在 http://modinfor.com/MetaDegron/ 上免费获取。我们预计 MetaDegron 将成为临床和转化社区阐明蛋白质动态平衡调节机制、癌症研究和药物开发的有用工具。
