SUSPECT-BDQ

SUSPECT-BDQ predicts structural susceptibility and potential resistance of Mycobacterium tuberculosis AtpE variants to bedaquiline, enabling assessment of variant impacts on drug binding.

Key Features:

• Target: Assesses mutations in AtpE, the primary target of bedaquiline in Mycobacterium tuberculosis.
• Variant dataset: Analyzed 9 previously identified resistance-associated variants and 54 non-resistance-associated mutations across 23 mycobacterial species.
• Structural and functional analysis: Analyzes structural and functional consequences of AtpE variants to identify disruptions to bedaquiline binding.
• Binding-site localization: Identifies that resistance-associated mutations predominantly occur at the bedaquiline binding site and disrupt critical interactions, reducing binding affinity.
• Predictive model: Implements a supervised predictive algorithm with a reported accuracy of 93.3% for identifying likely resistance mutations.
• Regional assessment: Applied the predictive model to circulating variants in the Asia-Pacific region to evaluate susceptibility trends.

Scientific Applications:

• Resistance prediction: Predicts whether specific AtpE variants are likely to confer resistance to bedaquiline.
• Variant characterization: Characterizes structural and functional impacts of clinical AtpE variants.
• Genomic surveillance: Supports interpretation of circulating variants for surveillance of bedaquiline susceptibility, including Asia-Pacific datasets.
• Clinical and research interpretation: Informs interpretation of genomic determinants of bedaquiline resistance for clinical and research decision-making.

Methodology:

Computational framework analyzing structural and functional consequences of AtpE variants using a comparative dataset of 9 resistance-associated and 54 non-resistance-associated mutations across 23 mycobacterial species, and a supervised predictive algorithm reported to achieve 93.3% accuracy.