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Bacterial binding to host receptors underlies both commensalism and pathogenesis. Many streptococci adhere to protein-attached carbohydrates expressed on cell surfaces using Siglec-like binding regions (SLBRs). The precise glycan repertoire recognized may dictate whether the organism is a strict commensal versus a pathogen. However, it is currently not clear what drives receptor selectivity. Here, we use five representative SLBRs and identify regions of the receptor binding site that are hypervariable in sequence and structure. We show that these regions control the identity of the preferred carbohydrate ligand using chimeragenesis and single amino acid substitutions. We further evaluate how the identity of the preferred ligand affects the interaction with glycoprotein receptors in human saliva and plasma samples. As point mutations can change the preferred human receptor, these studies suggest how streptococci may adapt to changes in the environmental glycan repertoire.

The insertion of nascent polypeptide chains into lipid bilayer membranes and the stability of membrane proteins crucially depend on the equilibrium partitioning of polypeptides. For this, the transfer of full sequences of amino-acid residues into the bilayer, rather than individual amino acids, must be understood. Earlier studies have revealed that the most likely reference state for partitioning very hydrophobic sequences is the membrane interface. We have used μs-scale simulations to calculate the interface-to-transmembrane partitioning free energies ΔGS→TM for two hydrophobic carrier sequences in order to estimate the insertion free energy for all 20 amino acid residues when bonded to the center of a partitioning hydrophobic peptide. Our results show that prior single-residue scales likely overestimate the partitioning free energies of polypeptides. The correlation of ΔGS→TM with experimental full-peptide translocon insertion data is high, suggesting an important role for the membrane interface in translocon-based insertion. The choice of carrier sequence greatly modulates the contribution of each single-residue mutation to the overall partitioning free energy. Our results demonstrate the importance of quantifying the observed full-peptide partitioning equilibrium, which is between membrane interface and transmembrane inserted, rather than combining individual water-to-membrane amino acid transfer free energies.

Knowledge of the physical properties of ionic liquids (ILs), such as the surface tension and speed of sound, is important for both industrial and research applications. Unfortunately, technical challenges and costs limit exhaustive experimental screening efforts of ILs for these critical properties. Previous work has demonstrated that the use of quantum-mechanics-based thermochemical property prediction tools, such as the conductor-like screening model for real solvents, when combined with machine learning (ML) approaches, may provide an alternative pathway to guide the rapid screening and design of ILs for desired physiochemical properties. However, the question of which machine-learning approaches are most appropriate remains. In the present study, we examine how different ML architectures, ranging from tree-based approaches to feed-forward artificial neural networks, perform in generating nonlinear multivariate quantitative structure–property relationship models for the prediction of the temperature- and pressure-dependent surface tension of and speed of sound in ILs over a wide range of surface tensions (16.9–76.2 mN/m) and speeds of sound (1009.7–1992 m/s). The ML models are further interrogated using the powerful interpretation method, shapley additive explanations. We find that several different ML models provide high accuracy, according to traditional statistical metrics. The decision tree-based approaches appear to be the most accurate and precise, with extreme gradient-boosting trees and gradient-boosting trees being the best performers. However, our results also indicate that the promise of using machine-learning to gain deep insights into the underlying physics driving structure–property relationships in ILs may still be somewhat premature. [ABSTRACT FROM AUTHOR]

Pretreatment facilitates cost-effective operations on lignocellulosic biomass ranging from densification to deconstruction and bioproduct development. However, determining molecular-level mechanisms behind pretreatment and their effects has remained elusive. Here, we combine computational simulation and experiment to investigate the effects on wheat straw agricultural residue densification of an emerging pretreatment solvent, namely, a deep eutectic solvent (DES) consisting of choline chloride (ChCl) and oxalic acid (OA). Ab initio molecular dynamics indicates that dissociation of lignin from cellulose in lignin–carbohydrate complexes, which does not occur to a significant extent in aqueous solution, is favorable in the DES and occurs via cleavage of the guaiacyl : xylose ether bond linkage by OA. The ensuing hemicellulose removal exposes lignin to the DES which, molecular dynamics simulation indicates, leads to lignin expansion. The resulting changes in wheat straw fiber structure, lignin distribution, and functional group modifications upon DES treatment by scanning electron and fluorescence microscopy along with Fourier-transform infrared spectroscopy. The molecular expansion of lignin enhances inter-particle binding in wheat straw, leading to denser structures under pelletization. The resulting high mechanical stability and combustion properties make the wheat straw a suitable precursor of high-quality densified solids (e.g., solid biofuel). Overall, we shed light on the molecular-level mechanisms involved in DES pretreatment for biomass densification, demonstrated here in the development of a solid biofuel. The approach here illuminates the rational design from first chemical principles of methods to convert lignocellulosic resources into advanced materials. [ABSTRACT FROM AUTHOR]

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators. [ABSTRACT FROM AUTHOR]

Contemporary research into community music programmes highlights diverse contexts for collaborative music making. This article contributes a case of the collaboration in music making to a growing literature on creative practice in community music initiatives led by major orchestras. The authors reflect on field research involving an after-school programme that provides free, classical instrumental music instruction to primary school-age students who would not normally have an opportunity due to their socio-economic circumstances. The Pizzicato Effect, run by the Melbourne Symphony Orchestra (MSO) in the City of Hume, Australia has operated in the northern suburbs of Melbourne since 2009. Through focus group interviews with students, family members and teaching artists, the researchers examined community experiences of accruing cultural capital in conditions of social inequality and multicultural practice. Using qualitative methods, the case study aimed to position respondents as experts in their own lives, who own their knowledge of their worlds. Collaboration was central to a model of improvisation developed locally by teaching artists and applied on site. Furthermore, improvisation took the programme in different directions to the El Sistema model of youth orchestra training in Venezuela, which had been the original source of inspiration for the programme. [ABSTRACT FROM AUTHOR]

Ensemble docking corresponds to the generation of an "ensemble" of drug target conformations in computational structure-based drug discovery, often obtained by using molecular dynamics simulation, that is used in docking candidate ligands. This approach is now well established in the field of early-stage drug discovery. This review gives a historical account of the development of ensemble docking and discusses some pertinent methodological advances in conformational sampling.

Classical and contemporary civilizational analysis has not sat comfortably with theoretical constructions of the intercultural or their empirical applications. A 'classical era' of civilizations analysis generated a program of research problems that was productive in critical and multidisciplinary ways and limited in scope and vision in others, but this failed to generate a provisional notion of the intercultural. Contemporary civilizational analysis improves on this position significantly in respect of the intercultural, particularly in the development of a current around 'intercivilizational encounters'. This essay examines this current especially in the work of Benjamin Nelson, Marshall Hodgson and Johann P. Arnason. Arguing that this approach represents vital advances for theoretical constructions of the intercultural in civilizational analysis and more generally in the human sciences, the essay also identifies limitations in latter-day approaches. [ABSTRACT FROM AUTHOR]

Dihedral conformational transitions are analyzed systematically in a model globular protein, cytochrome P450cam, to examine their structural and chemical dependences through combined conventional molecular dynamics (cMD), accelerated molecular dynamics (aMD) and adaptive biasing force (ABF) simulations. The aMD simulations are performed at two acceleration levels, using dihedral and dual boost, respectively. In comparison with cMD, aMD samples protein dihedral transitions approximately two times faster on average using dihedral boost, and ∼ 3.5 times faster using dual boost. In the protein backbone, significantly higher dihedral transition rates are observed in the bend, coil, and turn flexible regions, followed by the β bridge and β sheet, and then the helices. Moreover, protein side chains of greater length exhibit higher transition rates on average in the aMD-enhanced sampling. Side chains of the same length (particularly Nχ = 2) exhibit decreasing transition rates with residues when going from hydrophobic to polar, then charged and aromatic chemical types. The reduction of dihedral transition rates is found to be correlated with increasing energy barriers as identified through ABF free energy calculations. These general trends of dihedral conformational transitions provide important insights into the hierarchical dynamics and complex free energy landscapes of functional proteins.

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

The functional efficacy of colocalized, linked protein domains is dependent on linker flexibility and system compaction. However, the detailed characterization of these properties in aqueous solution presents an enduring challenge. Here, we employ a novel, to our knowledge, combination of complementary techniques, including small-angle neutron scattering, neutron spin-echo spectroscopy, and all-atom molecular dynamics and coarse-grained simulation, to identify and characterize in detail the structure and dynamics of a compact form of mercuric ion reductase (MerA), an enzyme central to bacterial mercury resistance. MerA possesses metallochaperone-like N-terminal domains (NmerA) tethered to its catalytic core domain by linkers. The NmerA domains are found to interact principally through electrostatic interactions with the core, leashed by the linkers so as to subdiffuse on the surface over an area close to the core C-terminal Hg(II)-binding cysteines. How this compact, dynamical arrangement may facilitate delivery of Hg(II) from NmerA to the core domain is discussed.

A recently proposed wide-angle velocity selector (WAVES) device for choosing the velocity of detected neutrons after they have been scattered by the sample paves the way for inverted geometry neutron spectrometers with continuously adjustable final neutron wavelength. BWAVES broadband inverted geometry spectrometer proposed for the Second Target Station at the Spallation Neutron Source at Oak Ridge National Laboratory is designed using WAVES to simultaneously probe dynamic processes spanning 4.5 decades in time (energy transfer). This makes BWAVES a uniquely flexible instrument which can be viewed as either a quasielasitc neutron scattering (QENS) spectrometer with a practically unlimited (overlapping with the vibrational excitations) range of energy transfers, or a broadband inelastic vibrational neutron spectrometer with QENS capabilities, including a range of accessible momentum transfer (Q) and a sufficiently high energy resolution at the elastic line. The new capabilities offered by BWAVES will expand the application of neutron scattering in ways not possible with existing neutron spectrometers.