saint - db:用于抗体建模和设计的综合结构抗体数据库。

IF 8.4 1区 医学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xiaoqiang Huang, Jun Zhou, Shuang Chen, Xiaofeng Xia, Y Eugene Chen, Jie Xu
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引用次数: 0

摘要

抗体(Ab)结构和抗体-抗原(Ag)相互作用(AAIs)对于理解免疫识别和设计抗体治疗方法至关重要。虽然现有的结构化Ab数据库提供了有价值的见解,但它们仍然面临数据准确性、完整性和/或更新频率方面的限制。在这里,我们提出了saint -parser,这是一种计算工作流程,用于从蛋白质数据库(PDB)中快速,准确和稳健地提取Ab和AAI信息。saint -parser具有精确检测Ab链,准确配对Ab链,可靠识别AAIs的特点。最后一次更新是在2025年5月1日,它包含了9757个PDB结构的19128个数据条目,提供了一个全面和最新的资源。详细的分析强调了saint - db在数据准确性和完整性方面优于广泛使用的SAbDab。此外,saint - db提供的非冗余的、人工管理的Ab-Ag结合亲和条目几乎是SAbDab的两倍。为了支持ab相关的研究并使更广泛的科学界受益,我们在https://github.com/tommyhuangthu/SAAINT上提供对saint -parser、saint - db摘要文件、未处理的PDB结构和saint -parser处理的结构模型的开放访问。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAAINT-DB: a comprehensive structural antibody database for antibody modeling and design.

Antibody (Ab) structures and antibody-antigen (Ag) interactions (AAIs) are essential for understanding immune recognition and designing Ab therapeutics. While existing structural Ab databases provide valuable insights, they still face limitations in data accuracy, completeness, and/or update frequency. Here, we present SAAINT-parser, a computational workflow for rapid, accurate, and robust extraction of Ab and AAI information from the Protein Data Bank (PDB). SAAINT-parser features precise detection of Ab chains, accurate pairing of Ab chains, and reliable identification of AAIs. The resulting SAAINT-DB, last updated on May 1, 2025, contains 19,128 data entries from 9757 PDB structures, offering a comprehensive and up-to-date resource. Detailed analyses highlight the advantages of SAAINT-DB over the widely used SAbDab in terms of data accuracy and completeness. Furthermore, SAAINT-DB provides nearly twice as many non-redundant, manually curated Ab-Ag binding affinity entries as SAbDab. To support Ab-related research and benefit the broader scientific community, we provide open access to SAAINT-parser, the SAAINT-DB summary file, unprocessed PDB structures, and SAAINT-parser-processed structure models at https://github.com/tommyhuangthu/SAAINT .

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来源期刊
Acta Pharmacologica Sinica
Acta Pharmacologica Sinica 医学-化学综合
CiteScore
15.10
自引率
2.40%
发文量
4365
审稿时长
2 months
期刊介绍: APS (Acta Pharmacologica Sinica) welcomes submissions from diverse areas of pharmacology and the life sciences. While we encourage contributions across a broad spectrum, topics of particular interest include, but are not limited to: anticancer pharmacology, cardiovascular and pulmonary pharmacology, clinical pharmacology, drug discovery, gastrointestinal and hepatic pharmacology, genitourinary, renal, and endocrine pharmacology, immunopharmacology and inflammation, molecular and cellular pharmacology, neuropharmacology, pharmaceutics, and pharmacokinetics. Join us in sharing your research and insights in pharmacology and the life sciences.
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