Prediction of Protein Structure of -LactamaseEnzymes in Mycobacterium Tuberculosis and Drug Prediction Based on AlphaFold3

This study focuses on Rv2068c blaC -lactamase, a core drug-resistant protein in Mycobacterium tuberculosis (MTB), which compromises the efficacy of -lactam antibiotics. After investigation of comprehensive analysis of resistance mechanism of Rv2068c blac -lactamase using the UniProt database, its three-dimentional structure was predicted using AlphaFold 3. The structural model revealed conserved catalytic motifs, including a serine-active site critical for -lactam ring hydrolysis. Later on, Rv2068c blaC -lactamase was compared with other TB drug resistance-related -lactamase proteins (e.g., GES-5, A0A1X1YXR3), which provided data on the nature and classification of -lactamases which correlate with substrate specificity and enzymatic stability and along with their structural and functional differences. Additionally, docking studies provide ligand-receptor binding modes and affinities. Docking studies identified ligand-receptor binding modes, with DELAMANID and JSF-3285 exhibiting consistent high-affinity interactions across clusters. These findings underscore BlaCs role in multidrug resistance and provide a structural framework for designing inhibitors against -lactamase-mediated antibiotic inactivation.

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Publication Details

Journal
Theoretical and Natural Science
Published
2025-06-27
DOI
https://doi.org/10.54254/2753-8818/2025.au24433
Primary Topic
Machine Learning in Bioinformatics
Type
article
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article

Prediction of Protein Structure of -LactamaseEnzymes in Mycobacterium Tuberculosis and Drug Prediction Based on AlphaFold3

Lingxuan Gong
Theoretical and Natural Science
Machine Learning in Bioinformatics
article

Prediction of Protein Structure of -LactamaseEnzymes in Mycobacterium Tuberculosis and Drug Prediction Based on AlphaFold3

Lingxuan Gong
article en

Abstract

This study focuses on Rv2068c blaC -lactamase, a core drug-resistant protein in Mycobacterium tuberculosis (MTB), which compromises the efficacy of -lactam antibiotics. After investigation of comprehensive analysis of resistance mechanism of Rv2068c blac -lactamase using the UniProt database, its three-dimentional structure was predicted using AlphaFold 3. The structural model revealed conserved catalytic motifs, including a serine-active site critical for -lactam ring hydrolysis. Later on, Rv2068c blaC -lactamase was compared with other TB drug resistance-related -lactamase proteins (e.g., GES-5, A0A1X1YXR3), which provided data on the nature and classification of -lactamases which correlate with substrate specificity and enzymatic stability and along with their structural and functional differences. Additionally, docking studies provide ligand-receptor binding modes and affinities. Docking studies identified ligand-receptor binding modes, with DELAMANID and JSF-3285 exhibiting consistent high-affinity interactions across clusters. These findings underscore BlaCs role in multidrug resistance and provide a structural framework for designing inhibitors against -lactamase-mediated antibiotic inactivation.

Theoretical and Natural ScienceVol. 119(1)
Shenzhen Baoan High School Group (CN)
Openalex Percentile: Top 86%
Machine Learning in Bioinformatics
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Prediction of Protein Structure of -LactamaseEnzymes in Mycobacterium Tuberculosis and Drug Prediction Based on AlphaFold3 — Lingxuan Gong · Theoretical and Natural Science (2025) | TGRS Research Map | TGRS