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      A thermostable flavin-based fluorescent protein from Chloroflexus aggregans: a framework for ultra-high resolution structural studies

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          Abstract

          A new thermostable fluorescent protein is shown to be a promising model for ultra-high resolution structural studies of LOV domains and for application as a fluorescent reporter.

          Abstract

          Light-Oxygen-Voltage (LOV) domains are conserved parts of photoreceptors in plants, bacteria and fungi that bind flavins as chromophores and detect blue light. In the past, LOV domain variants have been developed as fluorescent reporter proteins (called flavin-based fluorescent proteins; FbFPs), which due to their ability to fluoresce under anaerobic conditions, fast folding kinetics and a small size of ∼12–16 kDa are a promising reporter system for quantitative real-time analysis of biological processes. Here, we present a small thermostable flavin-based fluorescent protein CagFbFP derived from a soluble LOV domain-containing histidine kinase from the thermophilic bacterium Chloroflexus aggregans. CagFbFP is composed of 107 amino acids with a molecular weight of 11.6 kDa and consists only of the conserved LOV core domain. The protein is thermostable with a melting point of about 68 °C. It crystallizes easily and its crystals diffract to 1.07 Å. Both the crystal structure and small angle scattering data show that the protein is a dimer. Unexpectedly, glutamine 148, which in LOV photoreceptor proteins is the key residue responsible for signal transduction, occupies two conformations. Molecular dynamics simulations show that the two conformations interconvert rapidly. The crystal structure of the wild-type Chloroflexus aggregans LOV domain determined at 1.22 Å resolution confirmed the presence of two alternative conformations of the glutamine 148 side chain. Overall, this protein, due to its stability and ease of crystallization, appears to be a promising model for ultra-high resolution structural studies of LOV domains and for application as a fluorescent reporter.

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          Most cited references44

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          PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

          In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
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            Linking crystallographic model and data quality.

            In macromolecular x-ray crystallography, refinement R values measure the agreement between observed and calculated data. Analogously, R(merge) values reporting on the agreement between multiple measurements of a given reflection are used to assess data quality. Here, we show that despite their widespread use, R(merge) values are poorly suited for determining the high-resolution limit and that current standard protocols discard much useful data. We introduce a statistic that estimates the correlation of an observed data set with the underlying (not measurable) true signal; this quantity, CC*, provides a single statistically valid guide for deciding which data are useful. CC* also can be used to assess model and data quality on the same scale, and this reveals when data quality is limiting model improvement.
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              Ligand-binding PAS domains in a genomic, cellular, and structural context.

              Per-Arnt-Sim (PAS) domains occur in proteins from all kingdoms of life. In the bacterial kingdom, PAS domains are commonly positioned at the amino terminus of signaling proteins such as sensor histidine kinases, cyclic-di-GMP synthases/hydrolases, and methyl-accepting chemotaxis proteins. Although these domains are highly divergent at the primary sequence level, the structures of dozens of PAS domains across a broad section of sequence space have been solved, revealing a conserved three-dimensional architecture. An all-versus-all alignment of 63 PAS structures demonstrates that the PAS domain family forms structural clades on the basis of two principal variables: (a) topological location inside or outside the plasma membrane and (b) the class of small molecule that they bind. The binding of a chemically diverse range of small-molecule metabolites is a hallmark of the PAS domain family. PAS ligand binding either functions as a primary cue to initiate a cellular signaling response or provides the domain with the capacity to respond to secondary physical or chemical signals such as gas molecules, redox potential, or photons. This review synthesizes the current state of knowledge of the structural foundations and evolution of ligand recognition and binding by PAS domains.
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                Author and article information

                Journal
                PPSHCB
                Photochemical & Photobiological Sciences
                Photochem. Photobiol. Sci.
                Royal Society of Chemistry (RSC)
                1474-905X
                1474-9092
                2019
                2019
                Affiliations
                [1 ]Moscow Institute of Physics and Technology
                [2 ]Dolgoprudny
                [3 ]Russia
                [4 ]ICS-6: Structural Biochemistry
                [5 ]Forschungszentrum Jülich GmbH
                [6 ]Joint Institute for Nuclear Research
                [7 ]Dubna
                [8 ]Institute of Biotechnology
                [9 ]RWTH Aachen University
                [10 ]Aachen
                [11 ]Germany
                [12 ]DWI-Leibniz Institut für Interaktive Materialien
                [13 ]Institute of Molecular Enzyme Technology
                [14 ]Heinrich Heine University Düsseldorf
                [15 ]Forschungszentrum Jülich
                [16 ]Jülich
                Article
                10.1039/C9PP00067D
                31116222
                85d54f47-4805-4c37-acbf-140e1b216370
                © 2019

                http://rsc.li/journals-terms-of-use

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