Publications by authors named "Thomas Peulen"

Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences and gating access to genes. Even when the binding of TFs and their cofactors to DNA is reversible, indicating a reversible control of gene expression, there is little knowledge about the molecular effect DNA has on TFs. Using single-molecule multiparameter fluorescence spectroscopy, molecular dynamics simulations, and biochemical assays, we find that the monomeric form of the forkhead (FKH) domain of the human FoxP1 behaves as a disordered protein and increases its folded population when it dimerizes.

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Förster Resonance Energy Transfer (FRET) combined with single-molecule spectroscopy probes macromolecular structure and dynamics and identifies coexisting conformational states. We review recent methodological developments in integrative structural modeling by satisfying spatial restraints on networks of FRET pairs (hybrid-FRET). We discuss procedures to incorporate prior structural knowledge and to obtain optimal distance networks.

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TGR5 is the first identified bile acid-sensing G-protein coupled receptor, which has emerged as a potential therapeutic target for metabolic disorders. So far, structural and multimerization properties are largely unknown for TGR5. We used a combined strategy applying cellular biology, Multiparameter Image Fluorescence Spectroscopy (MFIS) for quantitative FRET analysis, and integrative modelling to obtain structural information about dimerization and higher-order oligomerization assemblies of TGR5 wildtype (wt) and Y111 variants fused to fluorescent proteins.

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We present a comprehensive toolkit for Förster resonance energy transfer (FRET)-restrained modeling of biomolecules and their complexes for quantitative applications in structural biology. A dramatic improvement in the precision of FRET-derived structures is achieved by explicitly considering spatial distributions of dye positions, which greatly reduces uncertainties due to flexible dye linkers. The precision and confidence levels of the models are calculated by rigorous error estimation.

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