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

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.

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Publication Details

Journal
Antimicrobial Agents and Chemotherapy
Published
2025-05-27
DOI
https://doi.org/10.1128/aac.00150-25
Citations
6
Primary Topic
Antibiotic Resistance in Bacteria
Type
article
Field-Weighted Citation Impact
3.55
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article

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

Robert A. Bonomo, Mariagrazia Perilli, Shahriar Mobashery, Gianfranco Amicosante et al.
6 citations
Antimicrobial Agents and Chemotherapy
Antibiotic Resistance in Bacteria
3.55
article

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

Robert A. Bonomo, Mariagrazia Perilli, Shahriar Mobashery, Gianfranco Amicosante, Gian María Rossolini, Karen Bush, Soobin Kim, Bogdan Iuliu Iorga, Jean‐Denis Docquier, Andrea M. Hujer, Shozeb M Haider, JAMES M. SPENCER, Sergei B. Vakulenko, Fedaa Attana, Alejandro J. Vila, Patricia A. Bradford, Sally R. Partridge, Kristine M. Hujer
article en
6 citations

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.

Antimicrobial Agents and ChemotherapyVol. 69(7)
University of Siena (IT), University of Notre Dame (US), The University of Sydney (AU), Institut de Chimie des Substances Naturelles (FR), Consejo Nacional de Investigaciones Científicas y Técnicas (AR), University of L'Aquila (IT), Université Paris-Saclay (FR), University of Bristol (GB), Louis Stokes Cleveland VA Medical Center (US), Indiana University Bloomington (US), UCL Biomedical Research Centre (GB), Instituto de Biología Molecular y Celular de Rosario (AR), University School (US), Dermatology Specialists (US), University of Florence (IT), University College London (GB), Case Western Reserve University (US), Indiana University (US), University of Tabuk (SA)
Quality Education
Openalex Percentile: Top 7%
Antibiotic Resistance in Bacteria
3.55
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