Skeletal Muscle Degeneration and Regeneration in Mice and Flies

Many aspects of skeletal muscle biology are remarkably similar between mammals and tiny insects, and experimental models of mice and flies (Drosophila) provide powerful tools to understand factors controlling the growth, maintenance, degeneration (atrophy and necrosis), and regeneration of normal and diseased muscles, with potential applications to the human condition. This review compares the limb muscles of mice and the indirect flight muscles of flies, with respect to the mechanisms of adult myofiber formation, homeostasis, atrophy, hypertrophy, and the response to muscle degeneration, with some comment on myogenic precursor cells and common gene regulatory pathways. There is a striking similarity between the species for events related to muscle atrophy and hypertrophy, without contribution of any myoblast fusion. Since the flight muscles of adult flies lack a population of reserve myogenic cells (equivalent to satellite cells), this indicates that such cells are not required for maintenance of normal muscle function. However, since satellite cells are essential in postnatal mammals for myogenesis and regeneration in response to myofiber necrosis, the extent to which such regeneration might be possible in flight muscles of adult flies remains unclear. Common cellular and molecular pathways for both species are outlined related to neuromuscular disorders and to age-related loss of skeletal muscle mass and function (sarcopenia). The commonality of events related to skeletal muscles in these disparate species (with vast differences in size, growth duration, longevity, and muscle activities) emphasizes the combined value and power of these experimental animal models.

The relationship between classification of multi-domain proteins using an alignment-free approach and their functions: a case study with immunoglobulins

Establishing functional relationships between multi-domain protein sequences is a non-trivial task. Traditionally, delineating functional assignment and relationships of proteins requires domain assignments as a prerequisite. This process is sensitive to alignment quality and domain definitions. In multi-domain proteins due to multiple reasons, the quality of alignments is poor. We report the correspondence between the classification of proteins represented as full-length gene products and their functions. Our approach differs fundamentally from traditional methods in not performing the classification at the level of domains. Our method is based on an alignment free local matching scores (LMS) computation at the amino-acid sequence level followed by hierarchical clustering. As there are no gold standards for full-length protein sequence classification, we resorted to Gene Ontology and domain-architecture based similarity measures to assess our classification. The final clusters obtained using LMS show high functional and domain architectural similarities. Comparison of the current method with alignment based approaches at both domain and full-length protein showed superiority of the LMS scores. Using this method we have recreated objective relationships among different protein kinase sub-families and also classified immunoglobulin containing proteins where sub-family definitions do not exist currently. This method can be applied to any set of protein sequences and hence will be instrumental in analysis of large numbers of full-length protein sequences.

Steady mixed convection flow of Maxwell fluid over an exponentially stretching vertical surface with magnetic field and viscous dissipation

The steady mixed convection flow and heat transfer from an exponentially stretching vertical surface in a quiescent Maxwell fluid in the presence of magnetic field, viscous dissipation and Joule heating have been studied. The stretching velocity, surface temperature and magnetic field are assumed to have specific exponential function forms for the existence of the local similarity solution. The coupled nonlinear ordinary differential equations governing the local similarity flow and heat transfer have been solved numerically by Chebyshev finite difference method. The influence of the buoyancy parameter, viscous dissipation, relaxation parameter of Maxwell fluid, magnetic field and Prandtl number on the flow and heat transfer has been considered in detail. The Nusselt number increases significantly with the Prandtl number, but the skin friction coefficient decreases. The Nusselt number slightly decreases with increasing viscous dissipation parameter, but the skin friction coefficient slightly increases. Maxwell fluid reduces both skin friction coefficient and Nusselt number, whereas buoyancy force enhances them.

PLIC: protein-ligand interaction clusters

Most of the biological processes are governed through specific protein-ligand interactions. Discerning different components that contribute toward a favorable protein-ligand interaction could contribute significantly toward better understanding protein function, rationalizing drug design and obtaining design principles for protein engineering. The Protein Data Bank (PDB) currently hosts the structure of similar to 68 000 protein-ligand complexes. Although several databases exist that classify proteins according to sequence and structure, a mere handful of them annotate and classify protein-ligand interactions and provide information on different attributes of molecular recognition. In this study, an exhaustive comparison of all the biologically relevant ligand-binding sites (84 846 sites) has been conducted using PocketMatch: a rapid, parallel, in-house algorithm. PocketMatch quantifies the similarity between binding sites based on structural descriptors and residue attributes. A similarity network was constructed using binding sites whose PocketMatch scores exceeded a high similarity threshold (0.80). The binding site similarity network was clustered into discrete sets of similar sites using the Markov clustering (MCL) algorithm. Furthermore, various computational tools have been used to study different attributes of interactions within the individual clusters. The attributes can be roughly divided into (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of atomic probes, (ii) atomic contacts consisting of various types of polar, hydrophobic and aromatic contacts along with binding site water molecules that could play crucial roles in protein-ligand interactions and (iii) binding energetics involved in interactions derived from scoring functions developed for docking. For each ligand-binding site in each protein in the PDB, site similarity information, clusters they belong to and description of site attributes are provided as a relational database-protein-ligand interaction clusters (PLIC).

Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions

Background: The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown. Results: We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of similar to 58% and similar to 40% for localization and functions respectively of proteins were determined at a threshold of similar to 30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k nearest neighbor classifier confirmed that our results compared favorably. Conclusions: This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions, especially for genes identified in GWAS studies to be associated with diseases, which are of translational interest.

PocketMatch (version 2.0): A parallel algorithm for the detection of structural similarities between protein ligand binding-sites

Knowledge of protein-ligand interactions is essential to understand several biological processes and important for applications ranging from understanding protein function to drug discovery and protein engineering. Here, we describe an algorithm for the comparison of three-dimensional ligand-binding sites in protein structures. A previously described algorithm, PocketMatch (version 1.0) is optimised, expanded, and MPI-enabled for parallel execution. PocketMatch (version 2.0) rapidly quantifies binding-site similarity based on structural descriptors such as residue nature and interatomic distances. Atomic-scale alignments may also be obtained from amino acid residue pairings generated. It allows an end-user to compute database-wide, all-to-all comparisons in a matter of hours. The use of our algorithm on a sample dataset, performance-analysis, and annotated source code is also included.

Flame surface statistics of constant-pressure turbulent expanding premixed flames

In this paper we investigate the local flame surface statistics of constant-pressure turbulent expanding flames. First the statistics of local length ratio is experimentally determined from high-speed planar Mie scattering images of spherically expanding flames, with the length ratio on the measurement plane, at predefined equiangular sectors, defined as the ratio of the actual flame length to the length of a circular-arc of radius equal to the average radius of the flame. Assuming isotropic distribution of such flame segments we then convolute suitable forms of the length-ratio probability distribution functions (pdfs) to arrive at the corresponding area-ratio pdfs. It is found that both the length ratio and area ratio pdfs are near log-normally distributed and shows self-similar behavior with increasing radius. Near log-normality and rather intermittent behavior of the flame-length ratio suggests similarity with dissipation rate quantities which stimulates multifractal analysis. (C) 2014 AIP Publishing LLC.

CONFORMATIONAL FEATURES OF SIGMA FACTOR/ANTI-SIGMA COMPLEXES

The association of a factors with the RNA polymerase dictates the expression profile of a bacterial cell. Major changes to the transcription profile are achieved by the use of multiple sigma factors that confer distinct promoter selectivity to the holoenzyme. The cellular concentration of a sigma factor is regulated by diverse mechanisms involving transcription, translation and post-translational events. The number of sigma factors varies substantially across bacteria. The diversity in the interactions between sigma factors also vary-ranging from collaboration, competition or partial redundancy in some cellular or environmental contexts. These interactions can be rationalized by a mechanistic model referred to as the partitioning of a space model of bacterial transcription. The structural similarity between different sigma/anti-sigma complexes despite poor sequence conservation and cellular localization reveals an elegant route to incorporate diverse regulatory mechanisms within a structurally conserved scaffold. These features are described here with a focus on sigma/anti-sigma complexes from Mycobacterium tuberculosis. In particular, we discuss recent data on the conditional regulation of sigma/anti-sigma factor interactions. Specific stages of M. tuberculosis infection, such as the latent phase, as well as the remarkable adaptability of this pathogen to diverse environmental conditions can be rationalized by the synchronized action of different a factors.

Local structural distortions and their role in superconductivity in SmFeAsO1-xFx superconductors

EXAFS studies at the As K edge as a function of temperature were carried out in SmFeAsO1-xFx (x = 0 and 0.2) compounds to understand the role of local structural distortions in superconductivity observed in F-doped compounds. A significant correlation between the thermal variation of local structural parameters such as anion height and superconducting onset is found in the fluorinated compounds. Such a variation in anion height is absent in the non-superconducting compound. An increase in the Fe-As bond distance just below the superconducting onset temperature indicates a similarity between the distortions observed in the high-T-C cuprates and these Fe-based superconductors.

Crystal structure of a putative aspartic proteinase domain of the Mycobacterium tuberculosis cell surface antigen PE_PGRS16

We report the crystal structure of the first prokaryotic aspartic proteinase-like domain identified in the genome of Mycobacterium tuberculosis. A search in the genomes of Mycobacterium species showed that the C-terminal domains of some of the PE family proteins contain two classic DT/SG motifs of aspartic proteinases with a low overall sequence similarity to HIV proteinase. The three-dimensional structure of one of them, Rv0977 (PE_PGRS16) of M. tuberculosis revealed the characteristic pepsinf-old and catalytic site architecture. However, the active site was completely blocked by the N-terminal His-tag. Surprisingly, the enzyme was found to be inactive even after the removal of the N-terminal His-tag. A comparison of the structure with pepsins showed significant differences in the critical substrate binding residues and in the flap tyrosine conformation that could contribute to the lack of proteolytic activity of Rv0977. (C) 2013 The Authors. Published by Elsevier B.V. on behalf of Federation of European Biochemical Societies. All rights reserved.

Skeletal Muscle Degeneration and Regeneration in Mice and Flies

Many aspects of skeletal muscle biology are remarkably similar between mammals and tiny insects, and experimental models of mice and flies (Drosophila) provide powerful tools to understand factors controlling the growth, maintenance, degeneration (atrophy and necrosis), and regeneration of normal and diseased muscles, with potential applications to the human condition. This review compares the limb muscles of mice and the indirect flight muscles of flies, with respect to the mechanisms of adult myofiber formation, homeostasis, atrophy, hypertrophy, and the response to muscle degeneration, with some comment on myogenic precursor cells and common gene regulatory pathways. There is a striking similarity between the species for events related to muscle atrophy and hypertrophy, without contribution of any myoblast fusion. Since the flight muscles of adult flies lack a population of reserve myogenic cells (equivalent to satellite cells), this indicates that such cells are not required for maintenance of normal muscle function. However, since satellite cells are essential in postnatal mammals for myogenesis and regeneration in response to myofiber necrosis, the extent to which such regeneration might be possible in flight muscles of adult flies remains unclear. Common cellular and molecular pathways for both species are outlined related to neuromuscular disorders and to age-related loss of skeletal muscle mass and function (sarcopenia). The commonality of events related to skeletal muscles in these disparate species (with vast differences in size, growth duration, longevity, and muscle activities) emphasizes the combined value and power of these experimental animal models.

Characterizing the pocketome of Mycobacterium tuberculosis and application in rationalizing polypharmacological target selection

Polypharmacology is beginning to emerge as an important concept in the field of drug discovery. However, there are no established approaches to either select appropriate target sets or design polypharmacological drugs. Here, we propose a structural-proteomics approach that utilizes the structural information of the binding sites at a genome-scale obtained through in-house algorithms to characterize the pocketome, yielding a list of ligands that can participate in various biochemical events in the mycobacterial cell. The pocket-type space is seen to be much larger than the sequence or fold-space, suggesting that variations at the site-level contribute significantly to functional repertoire of the organism. All-pair comparisons of binding sites within Mycobacterium tuberculosis (Mtb), pocket-similarity network construction and clustering result in identification of binding-site sets, each containing a group of similar binding sites, theoretically having a potential to interact with a common set of compounds. A polypharmacology index is formulated to rank targets by incorporating a measure of druggability and similarity to other pockets within the proteome. This study presents a rational approach to identify targets with polypharmacological potential along with possible drugs for repurposing, while simultaneously, obtaining clues on lead compounds for use in new drug-discovery pipelines.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Chern-Simons vortices and holography

In this paper, based on the AdS(4)/CFT3 duality, we have explored the precise connection between the abelian Chern-Simons (CS) Higgs model in (2 + 1) dimensions to that with its dual gravitational counterpart living in one higher dimension. It has been observed that theU(1) current computed at the boundary of the AdS(4) could be expressed as the local function of the vortex solution that has the remarkable structural similarity to that with the Ginzburg-Landau (GL) type local expression for the current associated with the Maxwell-CS type vortices in (2 + 1) dimensions. In order to explore this duality a bit further we have also computed the coherence length as well as the magnetic penetration depth associated with these vortices. Finally using the knowledge of both the coherence length as well as the magnetic penetration depth we have computed the Ginzburg-Landau coefficient for the Maxwell-CS type vortices in (2 + 1) dimensions.

Subexponential Algorithm for d-Cluster Edge Deletion: Exception or Rule?

The correlation clustering problem is a fundamental problem in both theory and practice, and it involves identifying clusters of objects in a data set based on their similarity. A traditional modeling of this question as a graph theoretic problem involves associating vertices with data points and indicating similarity by adjacency. Clusters then correspond to cliques in the graph. The resulting optimization problem, Cluster Editing (and several variants) are very well-studied algorithmically. In many situations, however, translating clusters to cliques can be somewhat restrictive. A more flexible notion would be that of a structure where the vertices are mutually ``not too far apart'', without necessarily being adjacent. One such generalization is realized by structures called s-clubs, which are graphs of diameter at most s. In this work, we study the question of finding a set of at most k edges whose removal leaves us with a graph whose components are s-clubs. Recently, it has been shown that unless Exponential Time Hypothesis fail (ETH) fails Cluster Editing (whose components are 1-clubs) does not admit sub-exponential time algorithm STACS, 2013]. That is, there is no algorithm solving the problem in time 2 degrees((k))n(O(1)). However, surprisingly they show that when the number of cliques in the output graph is restricted to d, then the problem can be solved in time O(2(O(root dk)) + m + n). We show that this sub-exponential time algorithm for the fixed number of cliques is rather an exception than a rule. Our first result shows that assuming the ETH, there is no algorithm solving the s-Club Cluster Edge Deletion problem in time 2 degrees((k))n(O(1)). We show, further, that even the problem of deleting edges to obtain a graph with d s-clubs cannot be solved in time 2 degrees((k))n(O)(1) for any fixed s, d >= 2. This is a radical contrast from the situation established for cliques, where sub-exponential algorithms are known.