When can we trust structural models derived from pair distribution function measurements?

The pair distribution function (PDF) is an important metric for characterising structure in complex materials, but it is well known that meaningfully different structural models can sometimes give rise to equivalent PDFs. In this paper, we discuss the use of model likelihoods as a general approach for discriminating between such homometric structure solutions. Drawing on two main case studies-one concerning the structure of a small peptide and the other amorphous calcium carbonate-we show how consideration of model likelihood can help drive robust structure solution, even in cases where the PDF is particularly information-poor. The obvious thread of these individual case studies is the potential role for machine-learning approaches to help guide structure determination from the PDF, and our paper finishes with some forward-looking discussion along these lines.

Allenamides as a Powerful Tool to Incorporate Diversity: Thia-Michael Lipidation of Semisynthetic Peptides and Access to ß-Keto Amides.

Lipopeptides are an important class of biomolecules for drug development. Compared with conventional acylation, a chemoselective lipidation strategy offers a more efficient strategy for late-stage structural derivatisation of a peptide scaffold. It provides access to chemically diverse compounds possessing intriguing and non-native moieties. Utilising an allenamide, we report the first semisynthesis of antimicrobial lipopeptides leveraging a highly efficient thia-Michael addition of chemically diverse lipophilic thiols. Using chemoenzymatically prepared polymyxin B nonapeptide (PMBN) as a model scaffold, an optimised allenamide-mediated thia-Michael addition effected rapid and near quantitative lipidation, affording vinyl sulfide-linked lipopeptide derivatives. Harnessing the utility of this new methodology, 22 lipophilic thiols of unprecedented chemical diversity were introduced to the PMBN framework. These included alkyl thiols, substituted aromatic thiols, heterocyclic thiols and those bearing additional functional groups (e.g., amines), ultimately yielding analogues with potent Gram-negative antimicrobial activity and substantially attenuated nephrotoxicity. Furthermore, we report facile routes to transform the allenamide into a ß-keto amide on unprotected peptides, offering a powerful "jack-of-all-trades" synthetic intermediate to enable further peptide modification.

Flexibility of the petunia strigolactone receptor DAD2 promotes its interaction with signaling partners.

Strigolactones (SLs) are terpenoid-derived plant hormones that regulate various developmental processes, particularly shoot branching, root development, and leaf senescence. The SL receptor has an unusual mode of action. Upon binding SL, it hydrolyzes the hormone, and then covalently binds one of the hydrolytic products. These initial events enable the SL receptor DAD2 (in petunia) to interact with the F-box protein PhMAX2A of the Skp-Cullin-F-box (SCF) complex and/or a repressor of SL signaling, PhD53A. However, it remains unclear how binding and hydrolysis structurally alters the SL receptor to enable its engagement with signaling partners. Here, we used mutagenesis to alter DAD2 and affect SL hydrolysis or DAD2's ability to interact with its signaling partners. We identified three DAD2 variants whose hydrolytic activity had been separated from the receptor's interactions with PhMAX2A or PhD53A. Two variants, DAD2N242I and DAD2F135A, having substitutions in the core α/ß hydrolase-fold domain and the hairpin, exhibited hormone-independent interactions with PhMAX2A and PhD53A, respectively. Conversely, the DAD2D166A variant could not interact with PhMAX2A in the presence of SL, but its interaction with PhD53A remained unaffected. Structural analyses of DAD2N242I and DAD2D166A revealed only small differences compared with the structure of the WT receptor. Results of molecular dynamics simulations of the DAD2N242I structure suggested that increased flexibility is a likely cause for its SL-independent interaction with PhMAX2A. Our results suggest that PhMAX2A and PhD53A have distinct binding sites on the SL receptor and that its flexibility is a major determinant of its interactions with these two downstream regulators.

Structural Phylogenetics with Confidence.

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.

Illustration of a computational pipeline for evaluating cyclodextrin host-guest complex formation through conformational capture of bullvalene.

Cyclodextrins have a diverse range of applications, including as supramolecular hosts, as enzyme active-site analogs, in improving drug solubility and delivery, and in molecular selection. We have investigated their ability to form stable complexes with bullvalenes, unusual organic cage molecules that spontaneously interconvert between numerous degenerate isomers. The shape-shifting nature of substituted bullvalenes raises the potential for dynamic adaptive binding to biological targets. We tested whether ß- and γ-cyclodextrins can capture particular bullvalene isomers and whether the preferred binding mode(s) differ between isomers. We first applied our computational host-guest interaction potential energy profiling to determine the best binding mode(s) of unsubstituted bullvalene and each isomer of methylenehydroxybullvalene to ß- and γ-cyclodextrin. Subsequent molecular dynamics simulations of the predicted host-guest complexes showed that while unsubstituted bullvalene has a single, albeit ill-defined, binding mode with either cyclodextrin, each isomer of methylenehydroxybullvalene has two possible modes of binding to ß-cyclodextrin but only a single, nebulous mode of binding to γ-cyclodextrin. Experimental determination of the binding free energy of each methylenehydroxybullvalene-cyclodextrin complex showed that methylenehydroxybullvalene is more likely to bind to ß-cyclodextrin than to γ-cyclodextrin, despite its smaller cavity. Together, our results suggest that ß-cyclodextrin, but not γ-cyclodextrin, shows promise for conformational capture of mono-substituted bullvalenes. More broadly, our computational pipeline should prove useful for rapid characterization of cyclodextrin host-guest complexes, avoiding the need for costly synthesis of guest molecules that are unlikely to bind stably, as well as providing detailed atomic-level insight into the nature of complexation.

Site-specific glycation of Aß1-42 affects fibril formation and is neurotoxic.

Aß1-42 is involved in Alzheimer's disease (AD) pathogenesis and is prone to glycation, an irreversible process where proteins accumulate advanced glycated end products (AGEs). Nϵ-(Carboxyethyl)lysine (CEL) is a common AGE associated with AD patients and occurs at either Lys-16 or Lys-28 of Aß1-42. Methyglyoxal is commonly used for the unspecific glycation of Aß1-42, which results in a complex mixture of AGE-modified peptides and makes interpretation of a causative AGE at a specific amino acid residue difficult. We address this issue by chemically synthesizing defined CEL modifications on Aß1-42 at Lys-16 (Aß-CEL16), Lys-28 (Aß-CEL28), and Lys-16 and -28 (Aß-CEL16&28). We demonstrated that double-CEL glycations at Lys-16 and Lys-28 of Aß1-42 had the most profound impact on the ability to form amyloid fibrils. In silico predictions indicated that Aß-CEL16&28 had a substantial decrease in free energy change, which contributes to fibril destabilization, and a increased aggregation rate. Single-CEL glycations at Lys-28 of Aß1-42 had the least impact on fibril formation, whereas CEL glycations at Lys-16 of Aß1-42 delayed fibril formation. We also tested these peptides for neuronal toxicity and mitochondrial function on a retinoic acid-differentiated SH-SY5Y human neuroblastoma cell line (RA-differentiated SH-SY5Y). Only Aß-CEL16 and Aß-CEL28 were neurotoxic, possibly through a nonmitochondrial pathway, whereas Aß-CEL16&28 showed no neurotoxicity. Interestingly, Aß-CEL16&28 had depolarized the mitochondrial membrane potential, whereas Aß-CEL16 had increased mitochondrial respiration at complex II. These results may indicate mitophagy or an alternate route of metabolism, respectively. Therefore, our results provides insight into potential therapeutic approaches against neurotoxic CEL-glycated Aß1-42.

Computational methods for exploring protein conformations.

Proteins are dynamic molecules that can transition between a potentially wide range of structures comprising their conformational ensemble. The nature of these conformations and their relative probabilities are described by a high-dimensional free energy landscape. While computer simulation techniques such as molecular dynamics simulations allow characterisation of the metastable conformational states and the transitions between them, and thus free energy landscapes, to be characterised, the barriers between states can be high, precluding efficient sampling without substantial computational resources. Over the past decades, a dizzying array of methods have emerged for enhancing conformational sampling, and for projecting the free energy landscape onto a reduced set of dimensions that allow conformational states to be distinguished, known as collective variables (CVs), along which sampling may be directed. Here, a brief description of what biomolecular simulation entails is followed by a more detailed exposition of the nature of CVs and methods for determining these, and, lastly, an overview of the myriad different approaches for enhancing conformational sampling, most of which rely upon CVs, including new advances in both CV determination and conformational sampling due to machine learning.

The self-association and thermal denaturation of caprine and bovine ß-lactoglobulin.

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 ß-lactoglobulin from caprine milk, the most abundant protein present in the whey fraction. At pH 2.5 caprine ß-lactoglobulin is predominantly monomeric, whereas bovine ß-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 ß-lactoglobulin that result in a greater positive charge on each subunit of caprine ß-lactoglobulin at low pH. The denaturation of ß-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 ß-lactoglobulin display different responses to thermal treatment, with caprine ß-lactoglobulin precipitating at higher pH values than bovine ß-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 ß-lactoglobulin likely contributes to the reduced heat stability of caprine milk compared to bovine milk at its natural pH.

Molecular Dynamics Simulation of ß-Lactoglobulin at Different Oil/Water Interfaces.

Controlling and manipulating protein behavior at an interface is of immense relevance to a broad range of physicochemical and biological phenomena and technological processes. Although many experimental studies have contributed to rapid progress in the fundamental knowledge of protein behavior at interfaces, detailed molecular-level understanding of the mechanism of protein adsorption at an interface is still remarkably lacking. In this study, atomistic molecular dynamics simulations were used to characterize the adsorption of ß-lactoglobulin at two different oil/water (O/W) interfaces, where the oil was either the marginally hydrophilic octanol or the more hydrophilic triolein, and the results were compared to those of a previous study utilizing the hydrophobic oil decane. Both the approach to the surface and the mechanism of adsorption depend upon the hydrophilicity of the oil and the interfacial tension of the O/W interface, with the nature of the adsorption, the accompanying structural changes, and the energetic driving force differing markedly between the different oils. Intriguingly, the behavior of the protein resembles that predicted for a soft spherical particle at an O/W interface. The results are also in agreement with key experimental findings, particularly the observation that proteins undergo more conformational change upon adsorption to hydrophobic surfaces, flattening out to expose hydrophobic interior residues to the surface, and that a thicker layer of native-like adsorbed protein forms at hydrophilic surfaces, and reveal structural and mechanistic detail behind each mechanism of adsorption.

Chromosome conformation maps in fission yeast reveal cell cycle dependent sub nuclear structure.

Successful progression through the cell cycle requires spatial and temporal regulation of gene transcript levels and the number, positions and condensation levels of chromosomes. Here we present a high resolution survey of genome interactions in Schizosaccharomyces pombe using synchronized cells to investigate cell cycle dependent changes in genome organization and transcription. Cell cycle dependent interactions were captured between and within S. pombe chromosomes. Known features of genome organization (e.g. the clustering of telomeres and retrotransposon long terminal repeats (LTRs)) were observed throughout the cell cycle. There were clear correlations between transcript levels and chromosomal interactions between genes, consistent with a role for interactions in transcriptional regulation at specific stages of the cell cycle. In silico reconstructions of the chromosome organization within the S. pombe nuclei were made by polymer modeling. These models suggest that groups of genes with high and low, or differentially regulated transcript levels have preferred positions within the S. pombe nucleus. We conclude that the S. pombe nucleus is spatially divided into functional sub-nuclear domains that correlate with gene activity. The observation that chromosomal interactions are maintained even when chromosomes are fully condensed in M phase implicates genome organization in epigenetic inheritance and bookmarking.

Directed evolution of a model primordial enzyme provides insights into the development of the genetic code.

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.

Deriving Structural Information from Experimentally Measured Data on Biomolecules.

During the past half century, the number and accuracy of experimental techniques that can deliver values of observables for biomolecular systems have been steadily increasing. The conversion of a measured value Qexp of an observable quantity Q into structural information is, however, a task beset with theoretical and practical problems: 1) insufficient or inaccurate values of Qexp , 2) inaccuracies in the function Q(r→) used to relate the quantity Q to structure r→ , 3) how to account for the averaging inherent in the measurement of Qexp , 4) how to handle the possible multiple-valuedness of the inverse r→(Q) of the function Q(r→) , to mention a few. These apply to a variety of observable quantities Q and measurement techniques such as X-ray and neutron diffraction, small-angle and wide-angle X-ray scattering, free-electron laser imaging, cryo-electron microscopy, nuclear magnetic resonance, electron paramagnetic resonance, infrared and Raman spectroscopy, circular dichroism, Förster resonance energy transfer, atomic force microscopy and ion-mobility mass spectrometry. The process of deriving structural information from measured data is reviewed with an eye to non-experts and newcomers in the field using examples from the literature of the effect of the various choices and approximations involved in the process. A list of choices to be avoided is provided.

Fitting alignment tensor components to experimental RDCs, CSAs and RQCs.

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 [Formula: see text], 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 [Formula: see text].

Deciphering ß-Lactoglobulin Interactions at an Oil-Water Interface: A Molecular Dynamics Study.

Protein adsorption at liquid-liquid interfaces is of immense relevance to many biological processes and dairy-based functional foods. Due to experimental limitations, however, there is still a remarkable lack of understanding of the adsorption mechanism, particularly at a molecular level. In this study, atomistic molecular dynamics simulations were used to elucidate the approach and adsorption mechanism of ß-lactoglobulin (ß-LG) at a decane-water interface. Through multiple independent simulations starting from three representative initial orientations of ß-LG relative to the decane surface the rate at which ß-LG approaches the oil/water interface is found to be independent of its initial orientation, and largely stochastic in nature. While the residues that first make contact with the decane and the final orientation of ß-LG upon adsorption are similar in all cases, the adsorption process is driven predominantly by structural rearrangements that preserve the secondary structure but expose hydrophobic residues to the decane surface. This detailed characterization of the adsorption of ß-LG at an oil/water interface should inform the design and development of novel encapsulation and delivery systems in the food and pharmaceutical sciences.

A relationship between the transient structure in the monomeric state and the aggregation propensities of α-synuclein and ß-synuclein.

α-Synuclein is an intrinsically disordered protein whose aggregation is implicated in Parkinson's disease. A second member of the synuclein family, ß-synuclein, shares significant sequence similarity with α-synuclein but is much more resistant to aggregation. ß-Synuclein is missing an 11-residue stretch in the central non-ß-amyloid component region that forms the core of α-synuclein amyloid fibrils, yet insertion of these residues into ß-synuclein to produce the ßSHC construct does not markedly increase the aggregation propensity. To investigate the structural basis of these different behaviors, quantitative nuclear magnetic resonance data, in the form of paramagnetic relaxation enhancement-derived interatomic distances, are combined with molecular dynamics simulations to generate ensembles of structures representative of the solution states of α-synuclein, ß-synuclein, and ßSHC. Comparison of these ensembles reveals that the differing aggregation propensities of α-synuclein and ß-synuclein are associated with differences in the degree of residual structure in the C-terminus coupled to the shorter separation between the N- and C-termini in ß-synuclein and ßSHC, making protective intramolecular contacts more likely.

Enzyme Kinetics Analysis: An online tool for analyzing enzyme initial rate data and teaching enzyme kinetics.

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and cellular biology to pharmacology. However, because enzyme kinetics involves concepts rarely employed in other areas of biology, it can be challenging for students and researchers. Traditional graphical analysis was replaced by computational analysis, requiring another skill not core to many life sciences curricula. Computational analysis can be time-consuming and difficult in free software (e.g., R) or require costly software (e.g., GraphPad Prism). We present Enzyme Kinetics Analysis (EKA), a web-tool to augment teaching and learning and streamline EKA. EKA is an interactive and free tool for analyzing enzyme kinetic data and improving student learning through simulation, built using R and RStudio's ShinyApps. EKA provides kinetic models (Michaelis-Menten, Hill, simple reversible inhibition models, ternary-complex, and ping-pong) for users to fit experimental data, providing graphical results and statistics. Additionally, EKA enables users to input parameters and create data and graphs, to visualize changes to parameters (e.g., K M or number of measurements). This function is designed for students learning kinetics but also for researchers to design experiments. EKA (enzyme-kinetics.shinyapps.io/enzkinet_webpage/) provides a simple, interactive interface for teachers, students, and researchers to explore enzyme kinetics. It gives researchers the ability to design experiments and analyze data without specific software requirements.

Structural and biophysical analysis of a Haemophilus influenzae tripartite ATP-independent periplasmic (TRAP) transporter.

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 (HiSiaQM) at 2.99 Å resolution (extending to 2.2 Å at the core), revealing new features. The improved resolution (the previous HiSiaQM 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 HiSiaQM 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 (KD) for the complex between the soluble HiSiaP protein and HiSiaQM is in the micromolar range and that a related SiaP can bind HiSiaQM. This work provides key data that enhances our understanding of the 'elevator-with-an-operator' mechanism of TRAP transporters.

Molecular dynamics simulations of barley and maize lipid transfer proteins show different ligand binding preferences in agreement with experimental data.

Experimental studies of barley and maize lipid transfer proteins (LTPs) show that the two proteins bind the ligand palmitate in opposite orientations in their internal cavities. Moreover, maize LTP is reported to bind the ligand caprate in the internal cavity in a mixture of two orientations with approximately equal occupancy. Six 30 ns molecular dynamics (MD) simulations of maize and barley LTP with ligands bound in two orientations (modes M and B) have been used to understand the different ligand binding preferences. The simulations show that both maize and barley LTP could bind palmitate in the orientation observed experimentally for maize LTP (mode M), with the predominant interaction being a salt bridge between the ligand carboxylate headgroup and a conserved arginine side chain. However, the simulation of barley LTP with palmitate in the mode B orientation shows the most favorable protein-ligand interaction energy. In contrast, the simulations of maize LTP with palmitate and with caprate in the mode B orientation show no persistent ligand binding, the ligands leaving the cavity during the simulations. Sequence differences between maize and barley LTP in the AB loop region, in residues at the base of the hydrophobic cavity, and in the helix A region are identified as contributing to the different behavior. The simulations reproduce well the experimentally observed binding preferences for palmitate and suggest that the experimental data for maize LTP with caprate reflect ligand mobility in binding mode M rather than the population of binding modes M and B.

Relative free enthalpies for point mutations in two proteins with highly similar sequences but different folds.

Enveloping distribution sampling was used to calculate free-enthalpy changes associated with single amino acid mutations for a pair of proteins, GA95 and GB95, that show 95% sequence identity yet fold into topologically different structures. Of the L → A, I → F, and L → Y mutations at positions 20, 30, and 45, respectively, of the 56-residue sequence, the first and the last contribute the most to the free-enthalpy difference between the native and non-native sequence-structure combinations, in agreement with the experimental findings for this protein pair. The individual free-enthalpy changes are almost sequence-independent in the four-strand/one-helix structure, the stable form of GB95, while in the three-helix bundle structure, the stable form of GA95, an interplay between residues 20 and 45 is observed.

Structome: a tool for the rapid assembly of datasets for structural phylogenetics.

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.