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In bacteria and archaea, tripartite ATP-independent periplasmic (TRAP) transporters uptake essential nutrients. TRAP transporters receive their substrates via a secreted soluble substrate-binding protein. How a sodium ion-driven secondary active transporter is strictly coupled to a substrate-binding protein is poorly understood. Here we report the cryo-EM structure of the sialic acid TRAP transporter SiaQM from Photobacterium profundum at 2.97 Å resolution. SiaM comprises a “transport” domain and a “scaffold” domain, with the transport domain consisting of helical hairpins as seen in the sodium ion-coupled elevator transporter VcINDY. The SiaQ protein forms intimate contacts with SiaM to extend the size of the scaffold domain, suggesting that TRAP transporters may operate as monomers, rather than the typically observed oligomers for elevator-type transporters. We identify the Na + and sialic acid binding sites in SiaM and demonstrate a strict dependence on the substrate-binding protein SiaP for uptake. We report the SiaP crystal structure that, together with docking studies, suggest the molecular basis for how sialic acid is delivered to the SiaQM transporter complex. We thus propose a model for substrate transport by TRAP proteins, which we describe herein as an ‘elevator-with-an-operator’ mechanism. Bacteria and archaea use tripartite ATP-independent periplasmic (TRAP) transporters to import essential nutrients. Davies et al. report a high resolution structure of a TRAP and show that it uses an ‘elevator-with-an operator’ mechanism.

Bond orders and formal charges are fundamental chemical descriptors. In cheminformatic applications it is necessary to be able to assign these properties to a given molecular structure automatically, given minimal input information. Here we describe a method for determining the bond order and formal charge assignments from only the atom types and connectivity. Our method utilises a graph theoretical description of electron positions. Each electron position assignment is scored according to lookup tables of atomic and bond dissociation energies derived from quantum chemical calculations. We tested three different optimisation methods—local optimisation, an A* pathfinding method, and an FPT optimisation method utilising tree decompositions—for finding the best electron position assignment, from which the bond orders and formal charges are extracted. We show that our method can assign bond orders and formal charges at a high degree of accuracy across a wide range of molecules from two different databases, and that the FPT algorithm provides the best combination of speed and accuracy.

Tripartite ATP-independent periplasmic (TRAP) transporters are secondary-active transporters that receive their substrates via a soluble-binding protein to move bioorganic acids across bacterial or archaeal cell membranes. Recent cryo-electron microscopy (cryo-EM) structures of TRAP transporters provide a broad framework to understand how they work, but the mechanistic details of transport are not yet defined. Here we report the cryo-EM structure of the Haemophilus influenzae N -acetylneuraminate TRAP transporter ( Hi SiaQM) at 2.99 Å resolution (extending to 2.2 Å at the core), revealing new features. The improved resolution (the previous Hi SiaQM structure is 4.7 Å resolution) permits accurate assignment of two Na + sites and the architecture of the substrate-binding site, consistent with mutagenic and functional data. Moreover, rather than a monomer, the Hi SiaQM structure is a homodimer. We observe lipids at the dimer interface, as well as a lipid trapped within the fusion that links the SiaQ and SiaM subunits. We show that the affinity ( K D ) for the complex between the soluble Hi SiaP protein and Hi SiaQM is in the micromolar range and that a related SiaP can bind Hi SiaQM. This work provides key data that enhances our understanding of the ‘elevator-with-an-operator’ mechanism of TRAP transporters.

Evolutionary arms races between pathogens and their hosts may be manifested as selection for rapid evolutionary change of key genes, and are sometimes detectable through sequence-level analyses. In the case of protein-coding genes, such analyses frequently predict that specific codons are under positive selection. However, detecting positive selection can be non-trivial, and false positive predictions are a common concern in such analyses. It is therefore helpful to place such predictions within a structural and functional context. Here, we focus on the p19 protein from tombusviruses. P19 is a homodimer that sequesters siRNAs, thereby preventing the host RNAi machinery from shutting down viral infection. Sequence analysis of the p19 gene is complicated by the fact that it is constrained at the sequence level by overprinting of a viral movement protein gene. Using homology modeling, in silico mutation and molecular dynamics simulations, we assess how non-synonymous changes to two residues involved in forming the dimer interface-one invariant, and one predicted to be under positive selection-impact molecular function. Interestingly, we find that both observed variation and potential variation (where a non-synonymous change to p19 would be synonymous for the overprinted movement protein) does not significantly impact protein structure or RNA binding. Consequently, while several methods identify residues at the dimer interface as being under positive selection, MD results suggest they are functionally indistinguishable from a site that is free to vary. Our analyses serve as a caveat to using sequence-level analyses in isolation to detect and assess positive selection, and emphasize the importance of also accounting for how non-synonymous changes impact structure and function.

For evaluating the deepest evolutionary relationships among proteins, sequence similarity is too low for application of sequence-based homology search or phylogenetic methods. In such cases, comparison of protein structures, which are often better conserved than sequences, may provide an alternative means of uncovering deep evolutionary signal. Although major protein structure databases such as SCOP and CATH hierarchically group protein structures, they do not describe the specific evolutionary relationships within a hierarchical level. Structural phylogenies have the potential to fill this gap. However, it is difficult to assess evolutionary relationships derived from structural phylogenies without some means of assessing confidence in such trees. We therefore address two shortcomings in the application of structural data to deep phylogeny. First, we examine whether phylogenies derived from pairwise structural comparisons are sensitive to differences in protein length and shape. We find that structural phylogenetics is best employed where structures have very similar lengths, and that shape fluctuations generated during molecular dynamics simulations impact pairwise comparisons, but not so drastically as to eliminate evolutionary signal. Second, we address the absence of statistical support for structural phylogeny. We present a method for assessing confidence in a structural phylogeny using shape fluctuations generated via molecular dynamics or Monte Carlo simulations of proteins. Our approach will aid the evolutionary reconstruction of relationships across structurally defined protein superfamilies. With the Protein Data Bank now containing in excess of 158,000 entries (December 2019), we predict that structural phylogenetics will become a useful tool for ordering the protein universe.

The contemporary proteinogenic repertoire contains 20 amino acids with diverse functional groups and side chain geometries. Primordial proteins, in contrast, were presumably constructed from a subset of these building blocks. Subsequent expansion of the proteinogenic alphabet would have enhanced their capabilities, fostering the metabolic prowess and organismal fitness of early living systems. While the addition of amino acids bearing innovative functional groups directly enhances the chemical repertoire of proteomes, the inclusion of chemically redundant monomers is difficult to rationalize. Here, we studied how a simplified chorismate mutase evolves upon expanding its amino acid alphabet from nine to potentially 20 letters. Continuous evolution provided an enhanced enzyme variant that has only two point mutations, both of which extend the alphabet and jointly improve protein stability by >4 kcal/mol and catalytic activity tenfold. The same, seemingly innocuous substitutions (Ile→Thr, Leu→Val) occurred in several independent evolutionary trajectories. The increase in fitness they confer indicates that building blocks with very similar side chain structures are highly beneficial for fine-tuning protein structure and function.

Abstract Summary Protein structures carry signal of common ancestry and can therefore aid in reconstructing their evolutionary histories. To expedite the structure-informed inference process, a web server, Structome, has been developed that allows users to rapidly identify protein structures similar to a query protein and to assemble datasets useful for structure-based phylogenetics. Structome was created by clustering ∼94% of the structures in RCSB PDB using 90% sequence identity and representing each cluster by a centroid structure. Structure similarity between centroid proteins was calculated, and annotations from PDB, SCOP, and CATH were integrated. To illustrate utility, an H3 histone was used as a query, and results show that the protein structures returned by Structome span both sequence and structural diversity of the histone fold. Additionally, the pre-computed nexus-formatted distance matrix, provided by Structome, enables analysis of evolutionary relationships between proteins not identifiable using searches based on sequence similarity alone. Our results demonstrate that, beginning with a single structure, Structome can be used to rapidly generate a dataset of structural neighbours and allows deep evolutionary history of proteins to be studied. Availability and Implementation Structome is available at: https://structome.bii.a-star.edu.sg.

Residual dipolar couplings, chemical shift anisotropies and quadrupolar couplings provide information about the orientation of inter-spin vectors and the anisotropic contribution of the local environment to the chemical shifts of nuclei, respectively. Structural interpretation of these observables requires parameterization of their angular dependence in terms of an alignment tensor. We compare and evaluate two algorithms for generating the optimal alignment tensor for a given molecular structure and set of experimental data, namely SVD (Losonczi et al. in J Magn Reson 138(2):334–342, 1999 ), which scales as O ( n 2 ) , and the linear least squares algorithm (Press et al. in Numerical recipes in C. The art of scientific computing, 2nd edn. Cambridge University Press, Cambridge, 1997 ), which scales as O ( n ) .

Milk components, such as proteins and lipids, have different physicochemical properties depending upon the mammalian species from which they come. Understanding the different responses of these milks to digestion, processing, and differences in their immunogenicity requires detailed knowledge of these physicochemical properties. Here we report on the oligomeric state of β-lactoglobulin from caprine milk, the most abundant protein present in the whey fraction. At pH 2.5 caprine β-lactoglobulin is predominantly monomeric, whereas bovine β-lactoglobulin exists in a monomer–dimer equilibrium at the same protein concentrations. This behaviour was also observed in molecular dynamics simulations and can be rationalised in terms of the amino acid substitutions present between caprine and bovine β-lactoglobulin that result in a greater positive charge on each subunit of caprine β-lactoglobulin at low pH. The denaturation of β-lactoglobulin when milk is heat-treated contributes to the fouling of heat-exchange surfaces, reducing yields and increasing cleaning costs. The bovine and caprine orthologues of β-lactoglobulin display different responses to thermal treatment, with caprine β-lactoglobulin precipitating at higher pH values than bovine β-lactoglobulin (pH 7.1 compared to pH 5.6) that are closer to the natural pH of these milks (pH 6.7). This property of caprine β-lactoglobulin likely contributes to the reduced heat stability of caprine milk compared to bovine milk at its natural pH.

For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, 3 J -couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.