Department of Biomedical Engineering, Chung-Ang University, Seoul 06974, South Korea.
Department of Bio-integrated Science and Technology, College of Life Sciences, Sejong University, Seoul 05006, Republic of Korea.
Database (Oxford). 2024 Aug 28;2024. doi: 10.1093/database/baae085.
Autoinhibition, a crucial allosteric self-regulation mechanism in cell signaling, ensures signal propagation exclusively in the presence of specific molecular inputs. The heightened focus on autoinhibited proteins stems from their implication in human diseases, positioning them as potential causal factors or therapeutic targets. However, the absence of a comprehensive knowledgebase impedes a thorough understanding of their roles and applications in drug discovery. Addressing this gap, we introduce Autoinhibited Protein Database (AiPD), a curated database standardizing information on autoinhibited proteins. AiPD encompasses details on autoinhibitory domains (AIDs), their targets, regulatory mechanisms, experimental validation methods, and implications in diseases, including associated mutations and post-translational modifications. AiPD comprises 698 AIDs from 532 experimentally characterized autoinhibited proteins and 2695 AIDs from their 2096 homologs, which were retrieved from 864 published articles. AiPD also includes 42 520 AIDs of computationally predicted autoinhibited proteins. In addition, AiPD facilitates users in investigating potential AIDs within a query sequence through comparisons with documented autoinhibited proteins. As the inaugural autoinhibited protein repository, AiPD significantly aids researchers studying autoinhibition mechanisms and their alterations in human diseases. It is equally valuable for developing computational models, analyzing allosteric protein regulation, predicting new drug targets, and understanding intervention mechanisms AiPD serves as a valuable resource for diverse researchers, contributing to the understanding and manipulation of autoinhibition in cellular processes. Database URL: http://ssbio.cau.ac.kr/databases/AiPD.
自动抑制是细胞信号传导中一种至关重要的变构自我调节机制,它确保信号仅在存在特定分子输入的情况下传播。对自动抑制蛋白的高度关注源于它们在人类疾病中的作用,将它们定位为潜在的因果因素或治疗靶点。然而,由于缺乏全面的知识库,阻碍了我们对它们在药物发现中的作用和应用的深入理解。为了解决这一差距,我们引入了自动抑制蛋白数据库(Autoinhibited Protein Database,AiPD),这是一个标准化自动抑制蛋白信息的精心策划的数据库。AiPD 包含自动抑制结构域(Autoinhibitory Domains,AIDs)、它们的靶标、调节机制、实验验证方法以及在疾病中的作用的详细信息,包括相关的突变和翻译后修饰。AiPD 包含 532 个经实验表征的自动抑制蛋白的 698 个 AIDs 和它们 2096 个同源物的 2695 个 AIDs,这些数据是从 864 篇已发表的文章中检索到的。AiPD 还包含 42520 个经计算预测的自动抑制蛋白的 AIDs。此外,AiPD 通过与已记录的自动抑制蛋白进行比较,使用户能够在查询序列中研究潜在的 AIDs。作为首个自动抑制蛋白数据库,AiPD 极大地帮助了研究自动抑制机制及其在人类疾病中的改变的研究人员。它对于开发计算模型、分析变构蛋白调节、预测新的药物靶点以及理解干预机制同样具有价值。AiPD 是各种研究人员的宝贵资源,有助于理解和操纵细胞过程中的自动抑制。数据库网址:http://ssbio.cau.ac.kr/databases/AiPD。