Algorithm and data structures for efficient energy maintenance during Monte Carlo simulation of proteins.

Monte Carlo simulation (MCS) is a common methodology to compute pathways and thermodynamic properties of proteins. A simulation run is a series of random steps in conformation space, each perturbing some degrees of freedom of the molecule. A step is accepted with a probability that depends on the change in value of an energy function. Typical energy functions sum many terms. The most costly ones to compute are contributed by atom pairs closer than some cutoff distance. This paper introduces a new method that speeds up MCS by exploiting the facts that proteins are long kinematic chains and that few degrees of freedom are changed at each step. A novel data structure, called the ChainTree, captures both the kinematics and the shape of a protein at successive levels of detail. It is used to efficiently detect self-collision (steric clash between atoms) and/or find all atom pairs contributing to the energy. It also makes it possible to identify partial energy sums left unchanged by a perturbation, thus allowing the energy value to be incrementally updated. Computational tests on four proteins of sizes ranging from 68 to 755 amino acids show that MCS with the ChainTree method is significantly faster (as much as 10 times faster for the largest protein) than with the widely used grid method. They also indicate that speed-up increases with larger proteins.     

Leveraging the HapMap correlation structure in association studies

Recent high-throughput genotyping technologies, such as the Affymetrix 500k array and the Illumina HumanHap 550 beadchip, have driven down the costs of association studies and have enabled the measurement of single-nucleotide polymorphism (SNP) allele frequency differences between case and control populations on a genomewide scale. A key aspect in the efficiency of association studies is the notion of "indirect association," where only a subset of SNPs are collected to serve as proxies for the uncollected SNPs, taking advantage of the correlation structure between SNPs. Recently, a new class of methods for indirect association, multimarker methods, has been proposed. Although the multimarker methods are a considerable advancement, current methods do not fully take advantage of the correlation structure between SNPs and their multimarker proxies. In this article, we propose a novel multimarker indirect-association method, WHAP, that is based on a weighted sum of the haplotype frequency differences. In contrast to traditional indirect-association methods, we show analytically that there is a considerable gain in power achieved by our method compared with both single-marker and multimarker tests, as well as traditional haplotype-based tests. Our results are supported by empirical evaluation across the HapMap reference panel data sets, and a software implementation for the Affymetrix 500k and Illumina HumanHap 550 chips is available for download.     

Generation, comparison, and merging of pathways between protein conformations: gating in K-channels

We present a general framework for the generation, alignment, comparison, and hybridization of motion pathways between two known protein conformations. The framework, which is rooted in probabilistic motion-planning techniques in robotics, allows for the efficient generation of collision-free motion pathways, while considering a wide range of degrees of freedom involved in the motion. Within the framework, we provide the means to hybridize pathways, thus producing, the motion pathway of the lowest energy barrier out of the many pathways proposed by our algorithm. This method for comparing and hybridizing pathways is modular, and may be used within the context of molecular dynamics and Monte Carlo simulations. The framework was implemented within the Rosetta software suite, where the protein is represented in atomic detail. The K-channels switch between open and closed conformations, and we used the overall framework to investigate this transition. Our analysis suggests that channel-opening may follow a three-phase pathway. First, the channel unlocks itself from the closed state; second, it opens; and third, it locks itself in the open conformation. A movie that depicts the proposed pathway is available in the Supplementary Material (Movie S1) and at http://www.cs.tau.ac.il/(angela/SuppKcsA.html.     

Quasi-symmetry in the cryo-EM structure of EmrE provides the key to modeling its transmembrane domain

Small multidrug resistance (SMR) transporters contribute to bacterial resistance by coupling the efflux of a wide range of toxic aromatic cations, some of which are commonly used as antibiotics and antiseptics, to proton influx. EmrE is a prototypical small multidrug resistance transporter comprising four transmembrane segments (M1-M4) that forms dimers. It was suggested recently that EmrE molecules in the dimer have different topologies, i.e. monomers have opposite orientations with respect to the membrane plane. A 3-D structure of EmrE acquired by electron cryo-microscopy (cryo-EM) at 7.5 Angstroms resolution in the membrane plane showed that parts of the structure are related by quasi-symmetry. We used this symmetry relationship, combined with sequence conservation data, to assign the transmembrane segments in EmrE to the densities seen in the cryo-EM structure. A C alpha model of the transmembrane region was constructed by considering the evolutionary conservation pattern of each helix. The model is validated by much of the biochemical data on EmrE with most of the positions that were identified as affecting substrate translocation being located around the substrate-binding cavity. A suggested mechanism for proton-coupled substrate translocation in small multidrug resistance antiporters provides a mechanistic rationale to the experimentally observed inverted topology.     

MolAxis: efficient and accurate identification of channels in macromolecules

Channels and cavities play important roles in macromolecular functions, serving as access/exit routes for substrates/products, cofactor and drug binding, catalytic sites, and ligand/protein. In addition, channels formed by transmembrane (TM) proteins serve as transporters and ion channels. MolAxis is a new sensitive and fast tool for the identification and classification of channels and cavities of various sizes and shapes in macromolecules. MolAxis constructs corridors, which are pathways that represent probable routes taken by small molecules passing through channels. The outer medial axis of the molecule is the collection of points that have more than one closest atom. It is composed of two-dimensional surface patches and can be seen as a skeleton of the complement of the molecule. We have implemented in MolAxis a novel algorithm that uses state-of-the-art computational geometry techniques to approximate and scan a useful subset of the outer medial axis, thereby reducing the dimension of the problem and consequently rendering the algorithm extremely efficient. MolAxis is designed to identify channels that connect buried cavities to the outside of macromolecules and to identify TM channels in proteins. We apply MolAxis to enzyme cavities and TM proteins. We further utilize MolAxis to monitor channel dimensions along Molecular Dynamics trajectories of a human Cytochrome P450. MolAxis constructs high quality corridors for snapshots at picosecond time-scale intervals substantiating the gating mechanism in the 2e substrate access channel. We compare our results with previous tools in terms of accuracy, performance and underlying theoretical guarantees of finding the desired pathways. MolAxis is available on line as a web-server and as a stand alone easy-to-use program (http://bioinfo3d.cs.tau.ac.il/MolAxis/).     

Expression and Immunogenicity of a Recombinant Diphtheria Toxin Fragment A in Streptococcus gordonii

A nontoxic mutant diphtheria toxin fragment A (DTA) was genetically fused in single, double, or triple copy to the major surface protein antigen P1 (SpaP) and surface expressed in Streptococcus gordonii DL-1. The expression was verified by Western immunoblotting. Mouse antisera raised against the recombinant S. gordonii recognized the native diphtheria toxinm suggesting the recombinant DTA was immunogenic. When given intranasally to mice with cholera toxin subunit B as the adjuvant, the recombinant S. gordonii expressing double copies of DTA (SpaP-DTA₂) induced a mucosal immunoglobulin A response and a weak systemic immunoglobulin G response. S. gordonii SpaP-DTA₂ was able to orally colonize BALB/c mice for a 15-week period and elicited a mucosal response, but a serum immunoglobulin G response was not apparent. The antisera failed to neutralize diphtheria toxin cytotoxicity in a Vero cell assay.     

Evaluating supervised and unsupervised background noise correction in human gut microbiome data

The ability to predict human phenotypes and identify biomarkers of disease from metagenomic data is crucial for the development of therapeutics for microbiome-associated diseases. However, metagenomic data is commonly affected by technical variables unrelated to the phenotype of interest, such as sequencing protocol, which can make it difficult to predict phenotype and find biomarkers of disease. Supervised methods to correct for background noise, originally designed for gene expression and RNA-seq data, are commonly applied to microbiome data but may be limited because they cannot account for unmeasured sources of variation. Unsupervised approaches address this issue, but current methods are limited because they are ill-equipped to deal with the unique aspects of microbiome data, which is compositional, highly skewed, and sparse. We perform a comparative analysis of the ability of different denoising transformations in combination with supervised correction methods as well as an unsupervised principal component correction approach that is presently used in other domains but has not been applied to microbiome data to date. We find that the unsupervised principal component correction approach has comparable ability in reducing false discovery of biomarkers as the supervised approaches, with the added benefit of not needing to know the sources of variation apriori. However, in prediction tasks, it appears to only improve prediction when technical variables contribute to the majority of variance in the data. As new and larger metagenomic datasets become increasingly available, background noise correction will become essential for generating reproducible microbiome analyses.     

In vivo anti-inflammatory effects of the M20 IL-1 Inhibitor: II. Effects on serum reactants

We have previously described an IL-1 Inhibitor derived from the M20 myelomoncytic cell line. This line also secretes several molecules of IL-1. We have shown that this factor is specific to IL-1in vitro, as well asin vivo. In vitro IL-1 induced proliferative responses of mouse thymocytes, human T cells and fibroblasts and IL-1 stimulated PGE₂ secretion from fibroblasts, were all inhibited by the M20 IL-1 Inhibitor.In vivo, the IL-1 Inhibitor reduced parameters of acute inflammation such as fever, leukocytosis and local inflammation. This study describes additional effects of the M20 IL-1 Inhibitor on inflammatory serum reactants. Levels of corticosterone and fibrinogen were increased by injection of IL-1, and decreased by the IL-1 Inhibitor. IL-1 reduced zinc and iron plasma levels and elevated copper plasma levels. The M20 IL-1 Inhibitor reversed these changes in a dose dependent manner. Similar effects produced by IL-6 and TNF were unaffected by the M20 IL-1 Inhibitor. Our results indicate that the M20 IL-1 Inhibitor acts specifically on IL-1 induced responsesin vivo. Therefore we conclude that this IL-1 Inhibitor has a great potential as an anti-inflammatory agent.Abbreviations IL-1 Interleukin 1 - IL-6 Interleukin 6 - IL-1ra Interleukin 1 receptor antagonist - TNF tumor necrosis factor     

Importance of medullary events in ammonium excretion: studies in acute respiratory and acute metabolic acidosis

The renal medulla can play an important role in acid excretion by modulating both hydrogen ion secretion in the medullary collecting duct and the medullary PNH3. The purpose of these experiments was to characterize the intrarenal events associated with ammonium excretion in acute acidosis. Cortical events were monitored in two ways: first, the rates of glutamine extraction and ammoniagenesis were assessed by measuring arteriovenous differences and the rate of renal blood flow; second, the biochemical response of the ammoniagenesis pathway was examined by measuring glutamate and 2-oxoglutarate, key renal cortical metabolites in this pathway. There were no significant differences noted in any of these cortical parameters between acute respiratory and metabolic acidosis. Despite a comparable twofold rise in ammonium excretion in both cases, the urine pH, PNH3, and the urine minus blood PCO2 difference (U-B PCO2) were lower during acute hypercapnia. In these experiments, the urine PCO2 was 34 mmHg (1 mmHg = 133.322 Pa) lower than that of the blood during acute respiratory acidosis while the U-B PCO2 was 5 +/- 3 mmHg in acute metabolic acidosis. Thus there were significant differences in medullary events during these two conditions. Although the urine pH is critical in determining ammonium excretion in certain circumstances, these results suggest that regional variations in the medullary PNH3 can modify this relationship.