MNHN-Tree-Tools: A toolbox for tree inference using multi-scale clustering of a set of sequences

Innovative tree-based method for sampling molecular conformations: exploring the ATP-binding cassette subfamily D member 1 (ABCD1) transporter as a case study

We introduce a novel tree-based method for visualizing molecular conformation sampling. Our method offers enhanced precision in highlighting conformational differences and facilitates the observation of local minimas within proteins fold space. The projection of empirical laboratory data on the tree allows us to create a link between protein conformations and disease relevant data. To demonstrate the efficacy of our approach, we applied it to the ATP-binding cassette subfamily D member 1 (ABCD1) transporter responsible for very long-chain fatty acids (VLCFAs) import into peroxisomes. The genetic disorder called X-linked adrenoleukodystrophy (XALD) is characterized by the accumulation of VLCFA due to pathogenic variants in the ABCD1 gene. Using in silico molecular simulation, we examined the behavior of 16 prevalent mutations alongside the wild-type protein, exploring both inward and outward open forms of the transporter through molecular simulations. We evaluated from resulting trajectories the energy potential related to the ABCD1 interactions with ATP molecules. We categorized XALD patients based on the severity and progression of their disease, providing a unique clinical perspective. By integrating this data into our numerical framework, our study aimed to uncover the molecular underpinnings of XALD, offering new insights into disease progression. As we explored molecular trajectories and conformations resulting from our study, the tree-based method not only contributes valuable insights into XALD but also lays a solid foundation for forthcoming drug design studies. We advocate for the broader adoption of our innovative approach, proposing it as a valuable tool for researchers engaged in molecular simulation studies.