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SAND:使用基于结构比对编号对D类β-内酰胺酶进行全面注释。

SAND: a comprehensive annotation of class D β-lactamases using structural alignment-based numbering.

作者信息

Attana Fedaa, Kim Soobin, Spencer James, Iorga Bogdan I, Docquier Jean-Denis, Rossolini Gian Maria, Perilli Mariagrazia, Amicosante Gianfranco, Vila Alejandro J, Vakulenko Sergei B, Mobashery Shahriar, Bradford Patricia, Bush Karen, Partridge Sally R, Hujer Andrea M, Hujer Kristine M, Bonomo Robert A, Haider Shozeb

机构信息

UCL School of Pharmacy, University College London, London, United Kingdom.

School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom.

出版信息

Antimicrob Agents Chemother. 2025 Jul 2;69(7):e0015025. doi: 10.1128/aac.00150-25. Epub 2025 May 27.

Abstract

Class D β-lactamases are a diverse group of enzymes that contribute to antibiotic resistance by inactivating β-lactam antibiotics. Examination of class D β-lactamases has evolved significantly over the years, with advancements in molecular biology and structural analysis providing deeper insights into their mechanisms of action and variation in specificity. However, one of the challenges in the field is the inconsistent residue numbering and secondary structure annotation across different studies, which complicates the comparison and interpretation of data. To address this, we propose SAND-a standardized naming system for both residues and secondary structure elements, based on a comprehensive structural alignment of all documented sequences and experimentally obtained crystal structures of class D β-lactamases. This unified framework will streamline cross-study comparisons and enhance data interpretation. Moreover, the standardized framework will enable AI-driven natural language processing (NLP) techniques to efficiently mine and compile relevant data from scientific literature, speeding up the discovery process and contributing to more rapid advancements in β-lactamase research.

摘要

D类β-内酰胺酶是一类多样的酶,通过使β-内酰胺抗生素失活而导致抗生素耐药性。多年来,对D类β-内酰胺酶的研究有了显著进展,分子生物学和结构分析的进步使人们对其作用机制和特异性差异有了更深入的了解。然而,该领域的挑战之一是不同研究中残基编号和二级结构注释不一致,这使得数据的比较和解释变得复杂。为了解决这个问题,我们提出了SAND——一种针对残基和二级结构元件的标准化命名系统,它基于对所有已记录序列和通过实验获得的D类β-内酰胺酶晶体结构进行的全面结构比对。这个统一的框架将简化跨研究比较并增强数据解释。此外,标准化框架将使人工智能驱动的自然语言处理(NLP)技术能够有效地从科学文献中挖掘和整理相关数据,加快发现过程,并推动β-内酰胺酶研究更快取得进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1fbc/12217458/a6dc78bc5878/aac.00150-25.f001.jpg

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