Toward Robust Characterization of Dynamic Binding Pockets: Lessons from the HBV Capsid Assembly Modulator Site
Protein function often depends on ligand binding pockets that fluctuate among conformational states, altering their size, shape, topology, and accessibility, yet quantitative comparison of these dynamic cavities remains challenging because their boundaries are often inherently ambiguous. The measure volinterior algorithm uses fuzzy-boundary detection to characterize enclosed molecular spaces;…
The fluctuating nature of protein function is largely dictated by ligand binding pockets, which exhibit variations in size, shape, topology, and accessibility. Traditional methods struggle to quantitatively compare these dynamic cavities due to the inherent ambiguity in defining their boundaries. To address this challenge, researchers employed the fuzzy-boundary detection algorithm, known as volinterior, to characterize the HBV capsid assembly modulator (CAM) binding site.
This study serves as a model system to develop and validate a practical workflow for applying the volinterior method to dynamic protein binding pockets.
The methodology provides valuable guidance for selecting appropriate parameters and evaluating the results. It establishes a standardized protocol for quantitatively characterizing the HBV CAM pocket, demonstrating robust and reproducible performance across various conformational ensembles derived from molecular dynamics (MD) simulations.
The findings emphasize the significance of a reproducible strategy for adapting the volinterior algorithm to other dynamic binding pockets, allowing for consistent comparison of pocket geometry among independent structural studies.
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