DL3D: visual representation of conformational ensembles of domain-linker-domain proteins
Abstract
Background The 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. Results We 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. Conclusion DL3D 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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BibTeX
@article{carriere2026dl3d,
title = {{DL3D: visual representation of conformational ensembles of domain-linker-domain proteins}},
author = {Laure Carrière and Simon Bartels and Christophe Zanon and Pau Bernadó and Juan Cortés},
journal = {BMC Bioinformatics},
year = {2026},
month = may,
doi = {10.1186/s12859-026-06474-4},
url = {https://laas.hal.science/hal-05749377v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - DL3D: visual representation of conformational ensembles of domain-linker-domain proteins
AU - Laure Carrière
AU - Simon Bartels
AU - Christophe Zanon
AU - Pau Bernadó
AU - Juan Cortés
PY - 2026
DA - 2026/05/29
JO - BMC Bioinformatics
DO - 10.1186/s12859-026-06474-4
UR - https://laas.hal.science/hal-05749377v1
AB - Background The 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. Results We 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. Conclusion DL3D 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.
SN - 1471-2105
ER -