RosettaAntibody: antibody variable region homology modeling server

The RosettaAntibody server (http://antibody.graylab.jhu.edu) predicts the structure of an antibody variable region given the amino-acid sequences of the respective light and heavy chains. In an initial stage, the server identifies and displays the most sequence homologous template structures for the light and heavy framework regions and each of the complementarity determining region (CDR) loops. Subsequently, the most homologous templates are assembled into a side-chain optimized crude model, and the server returns a picture and coordinate file. For users requesting a high-resolution model, the server executes the full RosettaAntibody protocol which additionally models the hyper-variable CDR H3 loop. The high-resolution protocol also relieves steric clashes by optimizing the CDR backbone torsion angles and by simultaneously perturbing the relative orientation of the light and heavy chains. RosettaAntibody generates 2000 independent structures, and the server returns pictures, coordinate files, and detailed scoring information for the 10 top-scoring models. The 10 models enable users to use rational judgment in choosing the best model or to use the set as an ensemble for further studies such as docking. The high-resolution models generated by RosettaAntibody have been used for the successful prediction of antibody–antigen complex structures

Adaptive evolution of the vertebrate skeletal muscle sodium channel

Tetrodotoxin (TTX) is a highly potent neurotoxin that blocks the action potential by selectively binding to voltage-gated sodium channels (Nav). The skeletal muscle Nav (Nav1.4) channels in most pufferfish species and certain North American garter snakes are resistant to TTX, whereas in most mammals they are TTX-sensitive. It still remains unclear as to whether the difference in this sensitivity among the various vertebrate species can be associated with adaptive evolution. In this study, we investigated the adaptive evolution of the vertebrate Nav1.4 channels. By means of the CODEML program of the PAML 4.3 package, the lineages of both garter snakes and pufferfishes were denoted to be under positive selection. The positively selected sites identified in the p-loop regions indicated their involvement in Nav1.4 channel sensitivity to TTX. Most of these sites were located in the intracellular regions of the Nav1.4 channel, thereby implying the possible association of these regions with the regulation of voltage-sensor movement

siRNA-Mediated Reduction of Inhibitor of Nuclear Factor-κB Kinase Prevents Tumor Necrosis Factor-α–Induced Insulin Resistance in Human Skeletal Muscle

OBJECTIVE—Proinflammatory cytokines contribute to systemic low-grade inflammation and insulin resistance. Tumor necrosis factor (TNF)-α impedes insulin signaling in insulin target tissues. We determined the role of inhibitor of nuclear factor-κB kinase (IKK)β in TNF-α–induced impairments in insulin signaling and glucose metabolism in skeletal muscle

Targeting Protein-Protein Interactions for Parasite Control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific ortholgous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable

SnugDock: Paratope Structural Optimization during Antibody-Antigen Docking Compensates for Errors in Antibody Homology Models

High resolution structures of antibody-antigen complexes are useful for analyzing the binding interface and to make rational choices for antibody engineering. When a crystallographic structure of a complex is unavailable, the structure must be predicted using computational tools. In this work, we illustrate a novel approach, named SnugDock, to predict high-resolution antibody-antigen complex structures by simultaneously structurally optimizing the antibody-antigen rigid-body positions, the relative orientation of the antibody light and heavy chains, and the conformations of the six complementarity determining region loops. This approach is especially useful when the crystal structure of the antibody is not available, requiring allowances for inaccuracies in an antibody homology model which would otherwise frustrate rigid-backbone docking predictions. Local docking using SnugDock with the lowest-energy RosettaAntibody homology model produced more accurate predictions than standard rigid-body docking. SnugDock can be combined with ensemble docking to mimic conformer selection and induced fit resulting in increased sampling of diverse antibody conformations. The combined algorithm produced four medium (Critical Assessment of PRediction of Interactions-CAPRI rating) and seven acceptable lowest-interface-energy predictions in a test set of fifteen complexes. Structural analysis shows that diverse paratope conformations are sampled, but docked paratope backbones are not necessarily closer to the crystal structure conformations than the starting homology models. The accuracy of SnugDock predictions suggests a new genre of general docking algorithms with flexible binding interfaces targeted towards making homology models useful for further high-resolution predictions

Roles of glial cells in synapse development

Brain function relies on communication among neurons via highly specialized contacts, the synapses, and synaptic dysfunction lies at the heart of age-, disease-, and injury-induced defects of the nervous system. For these reasons, the formation—and repair—of synaptic connections is a major focus of neuroscience research. In this review, I summarize recent evidence that synapse development is not a cell-autonomous process and that its distinct phases depend on assistance from the so-called glial cells. The results supporting this view concern synapses in the central nervous system as well as neuromuscular junctions and originate from experimental models ranging from cell cultures to living flies, worms, and mice. Peeking at the future, I will highlight recent technical advances that are likely to revolutionize our views on synapse–glia interactions in the developing, adult and diseased brain

Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities

This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “ancestry” (or biogeographical ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals’ biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals

An ab initio study of the structure and properties of aluminum hydroxide: Gibbsite and bayerite

The two most important polymorphs of aluminum hydroxide, namely gibbsite and bayerite, have been studied for the first time using solid state ab initio quantum mechanical methods, both using plane wave and localized basis set methodologies, within the framework of nonlocal density functional theory. The fully optimized structures have been determined for both phases, yielding improved hydrogen positions in the case of gibbsite for which the only previous information is from X-ray data. Mechanical properties have been calculated for gibbsite, including the full elastic constants tensor and the bulk modulus. The latter is found to be 55 GPa, which is significantly lower than a recent experimental estimate. Vibrational spectra have been calculated for both phases and assignments of the hydroxyl stretching modes are proposed