Carbon hydrogen bonds between Cα-H donors and carbonyl acceptors are frequently observed between transmembrane helices (Cα-H···O=C). Networks of these interactions occur often at helix-helix ...interfaces mediated by GxxxG and similar patterns. Cα-H hydrogen bonds have been hypothesized to be important in membrane protein folding and association, but evidence that they are major determinants of helix association is still lacking. Here we present a comprehensive geometric analysis of homodimeric helices that demonstrates the existence of a single region in conformational space with high propensity for Cα-H···O=C hydrogen bond formation. This region corresponds to the most frequent motif for parallel dimers, GASright, whose best-known example is glycophorin A. The finding suggests a causal link between the high frequency of occurrence of GASright and its propensity for carbon hydrogen bond formation. Investigation of the sequence dependency of the motif determined that Gly residues are required at specific positions where only Gly can act as a donor with its "side chain" Hα. Gly also reduces the steric barrier for non-Gly amino acids at other positions to act as Cα donors, promoting the formation of cooperative hydrogen bonding networks. These findings offer a structural rationale for the occurrence of GxxxG patterns at the GASright interface. The analysis identified the conformational space and the sequence requirement of Cα-H···O=C mediated motifs; we took advantage of these results to develop a structural prediction method. The resulting program, CATM, predicts ab initio the known high-resolution structures of homodimeric GASright motifs at near-atomic level.
Parallel extraction of headspace volatiles from multiwell plates using sorbent sheets (HS-SPMESH) followed by direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) can be used as ...a rapid alternative to solid-phase micro-extraction (SPME) gas-chromatography mass-spectrometry (GC-MS) for trace level volatile analyses. However, an earlier validation study of SPMESH-DART-MS using 3-isobutyl-2-methoxypyrazine (IBMP) in grape juice showed poor correlation between SPMESH-DART-MS and a gold standard SPME-GC-MS around the compound’s odor detection threshold (<10 ng/kg) in grape juice, and lacked sufficient sensitivity to detect IBMP at this concentration in grape homogenate. In this work, we report on the development and validation of an improved SPMESH extraction approach that lowers the limit of detection (LOD < 0.5 ng/kg), and regulates crosstalk between wells (<0.5%) over a calibration range of 0.5−100 ng/kg. The optimized SPMESH-DART-MS method was validated using Cabernet Sauvignon and Merlot grape samples harvested from commercial vineyards in the central valley of California (n = 302) and achieved good correlation and agreement with SPME-GC-MS (R2 = 0.84) over the native range of IBMP (<0.5−20 ng/kg). Coupling of SPMESH to a lower resolution triple quadrupole (QqQ)-MS via a new JumpShot-HTS DART source also achieved low ng/kg detection limits, and throughput was improved through positioning stage optimizations which reduced time spent on intra-well SPMESH areas.
Lewis base directed α,α-dehydrogenation of 2-(methoxymethyl)aniline gives a cationic iridium(III) alkoxycarbene. This alkoxycarbene is found to be subject to pyridine-promoted C–O bond cleavage in ...the formation of a delocalized iridium benzylidene. X-ray diffraction and DFT calculations support a structural distortion away from a classic benzylidene structure stemming from azaquinone methide character. Treatment of the iridium azaquinone methide with ethylene results in formal ethylene insertion into the vinylic C–H bond, demonstrating an unusual mechanism for net C–C bond formation via benzylic C–O cleavage.
The GxxxG motif is frequently found at the dimerization interface of a transmembrane structural motif called GASright, which is characterized by a short interhelical distance and a right-handed ...crossing angle between the helices. In GASright dimers, such as glycophorin A (GpA), BNIP3, and members of the ErbB family, the backbones of the helices are in contact, and they invariably display networks of 4 to 8 weak hydrogen bonds between Cα–H carbon donors and carbonyl acceptors on opposing helices (Cα–H···OC hydrogen bonds). These networks of weak hydrogen bonds at the helix–helix interface are presumably stabilizing, but their energetic contribution to dimerization has yet to be determined experimentally. Here, we present a computational and experimental structure-based analysis of GASright dimers of different predicted stabilities, which show that a combination of van der Waals packing and Cα–H hydrogen bonding predicts the experimental trend of dimerization propensities. This finding provides experimental support for the hypothesis that the networks of Cα–H hydrogen bonds are major contributors to the free energy of association of GxxxG-mediated dimers. The structural comparison between groups of GASright dimers of different stabilities reveals distinct sequence as well as conformational preferences. Stability correlates with shorter interhelical distances, narrower crossing angles, better packing, and the formation of larger networks of Cα–H hydrogen bonds. The identification of these structural rules provides insight on how nature could modulate stability in GASright and finely tune dimerization to support biological function.
Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials Kaufmann, K. W., et al. (2010) ...Biochemistry 49, 2987–2998. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.
A range of membrane protein modeling tools has been developed in the past 5-10 years, yet few of these tools are integrated and make use of existing functionality for soluble proteins. To extend ...existing methods in the Rosetta biomolecular modeling suite for membrane proteins, we recently implemented RosettaMP, a general framework for membrane protein modeling. While RosettaMP facilitates implementation of new methods, addressing real-world biological problems also requires a set of accessory tools that are used to carry out standard modeling tasks.
Here, we present six modeling tools, including de novo prediction of single trans-membrane helices, making mutations and refining the structure with different amounts of flexibility, transforming a protein into membrane coordinates and optimizing its embedding, computing a Rosetta energy score, and visualizing the protein in the membrane bilayer. We present these methods with complete protocol captures that allow non-expert modelers to carry out the computations.
The presented tools are part of the Rosetta software suite, available at www.rosettacommons.org .
julia.koehler.leman@gmail.com.
Supplementary data are available at Bioinformatics online.
Abstract The mucus surface layer serves vital functions for scleractinian corals and consists mainly of carbohydrates. Its carbohydrate composition has been suggested to be influenced by ...environmental conditions (e.g., temperature, nutrients) and microbial pressures (e.g., microbial degradation, microbial coral symbionts), yet to what extend the coral mucus composition is determined by phylogeny remains to be tested. To investigate the variation of mucus carbohydrate compositions among coral species, we analyzed the composition of mucosal carbohydrate building blocks (i.e., monosaccharides) for five species of scleractinian corals, supplemented with previously reported data, to discern overall patterns using cluster analysis. Monosaccharide composition from a total of 23 species (belonging to 14 genera and 11 families) revealed significant differences between two phylogenetic clades that diverged early in the evolutionary history of scleractinian corals (i.e., complex and robust; p = 0.001, R 2 = 0.20), mainly driven by the absence of arabinose in the robust clade. Despite considerable differences in environmental conditions and sample analysis protocols applied, coral phylogeny significantly correlated with monosaccharide composition (Mantel test: p < 0.001, R 2 = 0.70). These results suggest that coral mucus carbohydrates display phylogenetic dependence and support their essential role in the functioning of corals.
Chemokine receptors are a subset of G protein-coupled receptors defined by the distinct property of binding small protein ligands in the chemokine family. Chemokine receptors recognize their ligands ...by a mechanism that is distinct from other class A GPCRs that bind peptides or small molecules. For this reason, structural information on other ligand-GPCR interactions are only indirectly relevant to understanding the chemokine receptor interface. Additionally, the experimentally determined structures of chemokine-GPCR complexes represent less than 3% of the known interactions of this complex, multi-ligand/multi-receptor network. To enable predictive modeling of the remaining 97% of interactions, a general in silico protocol was designed to utilize existing chemokine receptor crystal structures, co-crystal structures, and NMR ensembles of chemokines bound to receptor fragments. This protocol was benchmarked on the ability to predict each of the three published co-crystal structures, while being blinded to the target structure. Averaging ensembles selected from the top-ranking models reproduced up to 84% of the intermolecular contacts found in the crystal structure, with the lowest Cα-RMSD of the complex at 3.3 Å. The chemokine receptor N-terminus, unresolved in crystal structures, was included in the modeling and recapitulates contacts with known sulfotyrosine binding pockets seen in structures derived from experimental NMR data. This benchmarking experiment suggests that realistic homology models of chemokine-GPCR complexes can be generated by leveraging current structural data.
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•A Rosetta-based protocol was developed to model chemokine-GPCR complexes.•Target complexes reproduced with overall Cα RMSD values approaching 3 Å.•Up to 84% of intermolecular contacts were correctly predicted.•Modeling recapitulates sulfotyrosine recognition elements important for chemokine binding.
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