Abstract
The conformational-driven allosteric protein diatom Phaeodactylum tricornutum aureochrome 1a (PtAu1a) di ers from other light-oxygen-voltage (LOV) proteins for its uncommon structural topology. The mechanism of signaling transduction in PtAu1a LOV domain (AuLOV) including flanking helices remains unclear because of this dissimilarity, which hinders the study of PtAu1a as an optogenetic tool. To clarify this mechanism, we employed a combination of tree-based machine learning models, Markov state models, machine learning based community analysis and transition path theory to quantitatively analyze the allosteric process. Our results are in good agreement with reported experimental findings and revealed a previously overlooked C-alpha helix and linkers as important in promoting the protein conformational change. This integrated approach can be considered as a general workflow and applied on other allosteric proteins to provide detailed information about their allosteric mechanisms.