ArticleBMC bioinformatics2026
DL3D: visual representation of conformational ensembles of domain-linker-domain proteins.
Article in BMC bioinformatics, 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
backgroundThe domain-linker-domain (DLD) architecture is commonly found in proteins, where flexible linkers connect consecutive domains and regulate their relative spatial positioning. Often, these linkers present partially structured elements that modulate inter-domain dynamics, directly influencing their function. From a protein design perspective, tuning the relative position and orientation of domains via the linker offers opportunities to modulate biological activity. Despite their relevance, analyzing conformational ensembles of DLD proteins remains a challenge, thereby limiting the structural insights that can be extracted.
resultsWe present DL3D, a robotics-inspired visualization tool that enables intuitive analysis of the conformational space sampled by DLD proteins. DL3D discretizes the relative positions of the two domains at the linker ends and projects each conformation onto a 3D voxel map, where density is represented in grayscale to highlight the most probable configurations. In addition, quaternion-based operations allow the analysis of relative domain orientations.
conclusionDL3D facilitates the structural investigation of highly flexible proteins composed of well-folded domains connected by flexible linkers. Beyond visualization, the tool supports downstream analyses such as low-dimensional conformational clustering. DL3D is implemented as a Python package and is available at: https://gitlab.laas.fr/moma/methods/analysis/dl3d/ . A Jupyter notebook with usage examples is also provided.
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