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Martinez Goikoetxea, M.

Publications and source records attributed to Martinez Goikoetxea, M..

2 recordsLinked to original sources

Conformational diversity in poly-HAMP arrays and its implications for signal transduction

Prokaryotic transmembrane receptors are built around a helical coiled-coil backbone, with specialized sensory, modulatory, and effector domains arranged along its length. The modulatory HAMP domain forms a four-helix parallel coiled coil that is structurally integrated into this backbone, typically connecting transmembrane segments with downstream cytosolic domains. In many systems, HAMP domains have been shown to transduce signals through axial rotation of their helices; however, it is not clear how broadly applicable this mechanism is. Here, we describe two families of soluble chemoreceptors and sensory kinases that contain long arrays of concatenated HAMP domains, which we term poly-HAMP. Although their poly-HAMP arrays have clearly evolved independently, both families share many sequence features consistent with convergence on a similar functional system. We determined the crystal structures of 4-HAMP and 6-HAMP segments from the poly-HAMP array of histidine kinase HskS of Myxococcus xanthus, revealing unusually tight packing between adjacent domains and conformational patterns compatible with the rotational signaling model. To assess whether these features are general and to define the broader conformational landscape of poly-HAMP arrays, we computed AlphaFold2 models of over 200 chemoreceptor- and kinase-associated arrays. The models were consistent with the HskS structures, yet revealed distinct preferences in the two array types: HAMP domains of chemoreceptor arrays were consistently predicted to adopt stable conformations along their lengths, whereas those of kinase arrays were predicted to be biased toward less favorable conformations. By modeling HAMP domains from kinase arrays in isolation from the neighboring domains, we show that they adopt alternative, stable conformations that are related to the array-embedded forms through axial helix rotation. Taken together, our results suggest that, despite their independent origins and structural diversity, HAMP-containing systems ranging from the poly-HAMP arrays studied here through multi-HAMP architectures to canonical single-HAMP receptors may have converged on the same conserved mode of signal transduction that involves axial helix rotation.

molecular biology↗

CCfrag: Scanning folding potential of coiled-coil fragments with AlphaFold

Structured abstractO_ST_ABSMotivationC_ST_ABSCoiled coils are a widespread structural motif consisting of multiple -helices that wind around a central axis to bury their hydrophobic core. Although their backbone can be uniquely described by the Crick parametric equations, these have little practical application in structural prediction, given that most coiled coils in nature feature non-canonical repeats that locally distort their geometry. While AlphaFold has emerged as an effective coiled-coil modeling tool, capable of accurately predicting changes in periodicity and core geometry along coiled-coil stalks, it is not without limitations. These include the generation of spuriously bent models and the inability to effectively model globally non-canonical coiled coils. In an effort to overcome these limitations, we investigated whether dividing full-length sequences into fragments would result in better models. ResultsWe developed CCfrag to leverage AlphaFold for the piece-wise modeling of coiled coils. The user can create a specification, defined by window size, length of overlap, and oligomerization state, and the program produces the files necessary to run structural predictions with AlphaFold. Then, the structural models and their scores are integrated into a rich per-residue representation defined by sequence-or structure-based features, which can be visualized or employed for further analysis. Our results suggest that removing coiled-coil sequences from their native context can in some case improve the prediction confidence and avoids bent models with spurious contacts. In this paper, we present various use cases of CCfrag, and propose that fragment-based prediction is useful for understanding the properties of long, fibrous coiled coils, by showing local features not seen in full-length models. Availability and ImplementationThe program is implemented as a Python module. The code and its documentation are available at https://github.com/Mikel-MG/CCfrag. Contactmikel.martinez@tuebingen.mpg.de

bioinformatics↗