Structural Correspondence of Solution, Liquid Crystal, and Crystalline Phases of the Chromonic Mesogen Sunset Yellow

The azo dye, sunset yellow, is a prototypical, chromonic liquid crystal in which assembly in aqueous solution at high volume fraction leads to lyotropic mesophases with a “package of properties distinct in almost every aspect” (Lydon, J. Curr. Opin. Colloid Interface Sci. 2004, 8, 480). In particular, the isotropic to nematic transition in such phases, the consequence of stacking of dye molecules in chains, is difficult to bring into correspondence with athermal theories for rigid rods as well as modifications that consider chain interactions with one another. Chromonic mesogens, small molecules that stack to form lyotropic liquid crystals, prompt structural questions that have yet to be answered; a full understanding of structure should inform colligative properties. Herein, the single crystal structure of a guanidinium salt of the sunset yellow dianion, a known chromonic mesogen, is reported. The compound crystallizes as a dihydrate, tetrahydrofuran solvate in the orthorhombic space group Pnna, with a = 6.8426(5) Å, b = 20.048(1) Å, c = 21.466(2) Å. The sunset yellow molecules, point group approximately Cs, are disordered about a crystallographic diad axis.The structure is informative because pairwise interactions in the disordered crystal structure show a remarkable correspondence with the stereochemistry of sunset yellow molecules in solution and in the liquid crystal phase. The solution structure is here simulated by the combination of molecular dynamics,metadynamics, and quantum chemical computations. The comparable disorder in the fluid and solid states suggests the possibility that stacked aggregates adhere to growing crystals intact. Computations were used to evaluate proposals that stacking faults and branching points lower the X-ray correlation lengths while preserving extended structures. Evidence is found forstacking faults but not branches. The solution stereochemistry and stereodynamics has implications for the geometry of long rods, for which understanding is a prerequisite for reckoning properties of vexing chromonic mesophases

Tip dependence of three-dimensional scanning force microscopy images of calcite-water interfaces investigated by simulation and experiments

In this study, we have investigated the influence of the tip on the three-dimensional scanning force microscopy (3D-SFM) images of calcite-water interfaces by experiments and simulations. We calculated 3D force images by simulations with the solvent tip approximation (STA), Ca, CO(3)and OH tip models. For all the 3D images, thezprofiles at the surface Ca and CO(3)sites alternately show oscillatory peaks corresponding to the hydration layers. However, the peak heights and spacings become larger when the mechanical stability of the tip becomes higher. For analyzing thexyslices of the 3D force images, we developed the extended STA (E-STA) model which allowed us to reveal the strong correlation between the hydration structure just under the tip and the atomic-scale force contrasts. Based on these understandings on the image features showing the strong tip dependence, we developed a method for objectively estimating the similarity between 3D force images. With this method, we compared the simulated images with the three experimentally obtained ones. Among them, two images showed a relatively high similarity with the image obtained by the simulation with the Ca or the CO(3)tip model. Based on these agreements, we characterized the hydration structure and mechanical stability of the experimentally used tips. The understanding and methodology presented here should help us to derive accurate information on the tip and the interfacial structure from experimentally obtained 3D-SFM images.Peer reviewe

Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

Towards Reliable Automatic Protein Structure Alignment

A variety of methods have been proposed for structure similarity calculation, which are called structure alignment or superposition. One major shortcoming in current structure alignment algorithms is in their inherent design, which is based on local structure similarity. In this work, we propose a method to incorporate global information in obtaining optimal alignments and superpositions. Our method, when applied to optimizing the TM-score and the GDT score, produces significantly better results than current state-of-the-art protein structure alignment tools. Specifically, if the highest TM-score found by TMalign is lower than (0.6) and the highest TM-score found by one of the tested methods is higher than (0.5), there is a probability of (42%) that TMalign failed to find TM-scores higher than (0.5), while the same probability is reduced to (2%) if our method is used. This could significantly improve the accuracy of fold detection if the cutoff TM-score of (0.5) is used. In addition, existing structure alignment algorithms focus on structure similarity alone and simply ignore other important similarities, such as sequence similarity. Our approach has the capacity to incorporate multiple similarities into the scoring function. Results show that sequence similarity aids in finding high quality protein structure alignments that are more consistent with eye-examined alignments in HOMSTRAD. Even when structure similarity itself fails to find alignments with any consistency with eye-examined alignments, our method remains capable of finding alignments highly similar to, or even identical to, eye-examined alignments.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Four small puzzles that Rosetta doesn't solve

A complete macromolecule modeling package must be able to solve the simplest structure prediction problems. Despite recent successes in high resolution structure modeling and design, the Rosetta software suite fares poorly on deceptively small protein and RNA puzzles, some as small as four residues. To illustrate these problems, this manuscript presents extensive Rosetta results for four well-defined test cases: the 20-residue mini-protein Trp cage, an even smaller disulfide-stabilized conotoxin, the reactive loop of a serine protease inhibitor, and a UUCG RNA tetraloop. In contrast to previous Rosetta studies, several lines of evidence indicate that conformational sampling is not the major bottleneck in modeling these small systems. Instead, approximations and omissions in the Rosetta all-atom energy function currently preclude discriminating experimentally observed conformations from de novo models at atomic resolution. These molecular "puzzles" should serve as useful model systems for developers wishing to make foundational improvements to this powerful modeling suite.Comment: Published in PLoS One as a manuscript for the RosettaCon 2010 Special Collectio

Designing succinct structural alphabets

Motivation: The 3D structure of a protein sequence can be assembled from the substructures corresponding to small segments of this sequence. For each small sequence segment, there are only a few more likely substructures. We call them the ‘structural alphabet’ for this segment. Classical approaches such as ROSETTA used sequence profile and secondary structure information, to predict structural fragments. In contrast, we utilize more structural information, such as solvent accessibility and contact capacity, for finding structural fragments