ArticleFrontiers in microbiology2026
A metal-aware library-expansion and virtual-screening workflow for
Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Methods: We built an explicit protein-ligand-metal model of MRAY_PSEAE and extracted pocket constraints from point-cloud geometry and polar/charged features. Candidates were generated through similarity-guided library expansion, combining PubChem 2D similarity retrieval with local rule-based BRICS enumeration. After canonicalization and 2D/property filtering, compounds were clustered by fingerprint similarity and prioritized through chemical-state plausibility, docking, Prime/MM-GBSA rescoring, and ligand strain filtering, followed by interaction analysis, 1-μs MD, and Results: Three hits (6675, 2733768, 5311309) were prioritized. In microsecond MD, compound 5311309 showed the most stable pose and key hotspot retention. ADMET indicated a permeability/efflux bottleneck along with liver-kidney and irritation/sensitization alerts, whereas hERG and AMES signals were favorable. In growth assays, compound 5311309 showed an IC50 of approximately 15.1 μM and an MIC of 64 μM. Conclusion: Metal-aware pocket modeling plus multi-level screening improved plausibility and ranking for this metal-dependent target, identifying compound 5311309 as a practical lead optimization starting point.
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