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      The Two-State Prehensile Tail of the Antibacterial Toxin Colicin N

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          Abstract

          Intrinsically disordered regions within proteins are critical elements in many biomolecular interactions and signaling pathways. Antibacterial toxins of the colicin family, which could provide new antibiotic functions against resistant bacteria, contain disordered N-terminal translocation domains (T-domains) that are essential for receptor binding and the penetration of the Escherichia coli outer membrane. Here we investigate the conformational behavior of the T-domain of colicin N (ColN-T) to understand why such domains are widespread in toxins that target Gram-negative bacteria. Like some other intrinsically disordered proteins in the solution state of the protein, ColN-T shows dual recognition, initially interacting with other domains of the same colicin N molecule and later, during cell killing, binding to two different receptors, OmpF and TolA, in the target bacterium. ColN-T is invisible in the high-resolution x-ray model and yet accounts for 90 of the toxin’s 387 amino acid residues. To reveal its solution structure that underlies such a dynamic and complex system, we carried out mutagenic, biochemical, hydrodynamic and structural studies using analytical ultracentrifugation, NMR, and small-angle x-ray scattering on full-length ColN and its fragments. The structure was accurately modeled from small-angle x-ray scattering data by treating ColN as a flexible system, namely by the ensemble optimization method, which enables a distribution of conformations to be included in the final model. The results reveal, to our knowledge, for the first time the dynamic structure of a colicin T-domain. ColN-T is in dynamic equilibrium between a compact form, showing specific self-recognition and resistance to proteolysis, and an extended form, which most likely allows for effective receptor binding.

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          1H, 13C and 15N chemical shift referencing in biomolecular NMR.

          A considerable degree of variability exists in the way that 1H, 13C and 15N chemical shifts are reported and referenced for biomolecules. In this article we explore some of the reasons for this situation and propose guidelines for future chemical shift referencing and for conversion from many common 1H, 13C and 15N chemical shift standards, now used in biomolecular NMR, to those proposed here.
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            Sequence complexity of disordered protein.

            Intrinsic disorder refers to segments or to whole proteins that fail to self-fold into fixed 3D structure, with such disorder sometimes existing in the native state. Here we report data on the relationships among intrinsic disorder, sequence complexity as measured by Shannon's entropy, and amino acid composition. Intrinsic disorder identified in protein crystal structures, and by nuclear magnetic resonance, circular dichroism, and prediction from amino acid sequence, all exhibit similar complexity distributions that are shifted to lower values compared to, but significantly overlapping with, the distribution for ordered proteins. Compared to sequences from ordered proteins, these variously characterized intrinsically disordered segments and proteins, and also a collection of low-complexity sequences, typically have obviously higher levels of protein-specific subsets of the following amino acids: R, K, E, P, and S, and lower levels of subsets of the following: C, W, Y, I, and V. The Swiss Protein database of sequences exhibits significantly higher amounts of both low-complexity and predicted-to-be-disordered segments as compared to a non-redundant set of sequences from the Protein Data Bank, providing additional data that nature is richer in disordered and low-complexity segments compared to the commonness of these features in the set of structurally characterized proteins.
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              Global rigid body modeling of macromolecular complexes against small-angle scattering data.

              New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms.
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                Author and article information

                Contributors
                Journal
                Biophys J
                Biophys. J
                Biophysical Journal
                The Biophysical Society
                0006-3495
                1542-0086
                17 October 2017
                17 October 2017
                17 October 2017
                : 113
                : 8
                : 1673-1684
                Affiliations
                [1 ]Centre for Bacterial Cell Biology, Institute for Cell and Molecular Biosciences, The Medical School, Newcastle University, Newcastle upon Tyne, United Kingdom
                [2 ]Centre for Structural and Molecular Biology, School of Chemistry, University of East Anglia, Norwich, United Kingdom
                [3 ]Institute of Integrative Biology, Structural and Chemical Biology, Liverpool, United Kingdom
                Author notes
                []Corresponding author alexandra.solovyova@ 123456ncl.ac.uk
                Article
                S0006-3495(17)30923-2
                10.1016/j.bpj.2017.08.030
                5647543
                29045862
                3f362531-b508-4991-8048-779f4aa8c1af
                © 2017 Biophysical Society.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 21 December 2016
                : 2 August 2017
                Categories
                Proteins

                Biophysics
                Biophysics

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