Predicted structures of agonist and antagonist bound complexes of adenosine A3 receptor

We used the GEnSeMBLE Monte Carlo method to predict ensemble of the 20 best packings (helix rotations and tilts) based on the neutral total energy (E) from a vast number (10 trillion) of potential packings for each of the four subtypes of the adenosine G protein-coupled receptors (GPCRs), which are involved in many cytoprotective functions. We then used the DarwinDock Monte Carlo methods to predict the binding pose for the human A(3) adenosine receptor (hAA(3)R) for subtype selective agonists and antagonists. We found that all four A(3) agonists stabilize the 15th lowest conformation of apo-hAA(3)R while also binding strongly to the 1st and 3rd. In contrast the four A(3) antagonists stabilize the 2nd or 3rd lowest conformation. These results show that different ligands can stabilize different GPCR conformations, which will likely affect function, complicating the design of functionally unique ligands. Interestingly all agonists lead to a trans χ1 angle for W6.48 that experiments on other GPCRs associate with G-protein activation while all 20 apo-AA(3)R conformations have a W6.48 gauche+ χ1 angle associated experimentally with inactive GPCRs for other systems. Thus docking calculations have identified critical ligand-GPCR structures involved with activation. We found that the predicted binding site for selective agonist Cl-IB-MECA to the predicted structure of hAA(3)R shows favorable interactions to three subtype variable residues, I253(6.58), V169(EL2), and Q167(EL2), while the predicted structure for hAA(2A)R shows weakened to the corresponding amino acids: T256(6.58), E169(EL2), and L167(EL2), explaining the observed subtype selectivity.     

Software extensions to UCSF chimera for interactive visualization of large molecular assemblies

Many structures of large molecular assemblies such as virus capsids and ribosomes have been experimentally determined to atomic resolution. We consider four software problems that arise in interactive visualization and analysis of large assemblies: how to represent multimers efficiently, how to make cartoon representations, how to calculate contacts efficiently, and how to select subassemblies. We describe techniques and algorithms we have developed and give examples of their use. Existing molecular visualization programs work well for single protein and nucleic acid molecules and for small complexes. The methods presented here are proposed as features to add to existing programs or include in next-generation visualization software to allow easy exploration of assemblies containing tens to thousands of macromolecules. Our approach is pragmatic, emphasizing simplicity of code, reliability, and speed. The methods described have been distributed as the Multiscale extension of the UCSF Chimera (www.cgl.ucsf.edu/chimera) molecular graphics program.     

Test of the Binding Threshold Hypothesis for olfactory receptors: explanation of the differential binding of ketones to the mouse and human orthologs of olfactory receptor 912-93

We tested the Binding Threshold Hypothesis (BTH) for activation of olfactory receptors (ORs): To activate an OR, the odorant must bind to the OR with binding energy above some threshold value. The olfactory receptor (OR) 912-93 is known experimentally to be activated by ketones in mouse, but is inactive to ketones in human, despite an amino acid sequence identity of approximately 66%. To investigate the origins of this difference, we used the MembStruk first-principles method to predict the tertiary structure of the mouse OR 912-93 (mOR912-93), and the HierDock first-principles method to predict the binding site for ketones to this receptor. We found that the strong binding of ketones to mOR912-93 is dominated by a hydrogen bond of the ketone carbonyl group to Ser105. All ketones predicted to have a binding energy stronger than EBindThresh = 26 kcal/mol were observed experimentally to activate this OR, while the two ketones predicted to bind more weakly do not. In addition, we predict that 2-undecanone and 2-dodecanone both bind sufficiently strongly to activate mOR912-93. A similar binding site for ketones was predicted in hOR912-93, but the binding is much weaker because the human ortholog has a Gly at the position of Ser105. We predict that mutating this Gly to Ser in human should lead to activation of hOR912-93 by these ketones. Experimental substantiations of the above predictions would provide further tests of the validity of the BTH, our predicted 3D structures, and our predicted binding sites for these ORs.     

A functional analysis of mouse models of cardiac disease through metabolic profiling

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. Tools are needed for assessing the phenotypes of the many mouse models that are now being generated, where genes have been "knocked out," "knocked in," or mutated, so that gene expression can be understood in its biological context. Metabolic profiling of cardiac tissue through high resolution NMR spectroscopy in conjunction with multivariate statistics has been used to classify mouse models of cardiac disease. The data sets included metabolic profiles from mouse models of Duchenne muscular dystrophy, two models of cardiac arrhythmia, and one of cardiac hypertrophy. The metabolic profiles demonstrate that the strain background is an important component of the global metabolic phenotype of a mouse, providing insight into how a given gene deletion may result in very different responses in diverse populations. Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease. Thus, this approach is a rapid method of phenotyping mouse models of disease.     

Population genetics of the wild yeast Saccharomyces paradoxus

Saccharomyces paradoxus is the closest known relative of the well-known S. cerevisiae and an attractive model organism for population genetic and genomic studies. Here we characterize a set of 28 wild isolates from a 10-km(2) sampling area in southern England. All 28 isolates are homothallic (capable of mating-type switching) and wild type with respect to nutrient requirements. Nine wild isolates and two lab strains of S. paradoxus were surveyed for sequence variation at six loci totaling 7 kb, and all 28 wild isolates were then genotyped at seven polymorphic loci. These data were used to calculate nucleotide diversity and number of segregating sites in S. paradoxus and to investigate geographic differentiation, population structure, and linkage disequilibrium. Synonymous site diversity is approximately 0.3%. Extensive incompatibilities between gene genealogies indicate frequent recombination between unlinked loci, but there is no evidence of recombination within genes. Some localized clonal growth is apparent. The frequency of outcrossing relative to inbreeding is estimated at 1.1% on the basis of heterozygosity. Thus, all three modes of reproduction known in the lab (clonal replication, inbreeding, and outcrossing) have been important in molding genetic variation in this species.     

Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

Background

In the analysis of complex traits, genetic effects can be confounded with non-genetic effects, especially when using full-sib families. Dominance and epistatic effects are typically confounded with additive genetic and non-genetic effects. This confounding may cause the estimated genetic variance components to be inaccurate and biased.

Methods

In this study, we constructed genetic covariance structures from whole-genome marker data, and thus used realized relationship matrices to estimate variance components in a heterogenous population of ~ 2200 mice for which four complex traits were investigated. These mice were genotyped for more than 10,000 single nucleotide polymorphisms (SNP) and the variances due to family, cage and genetic effects were estimated by models based on pedigree information only, aggregate SNP information, and model selection for specific SNP effects.

Results and conclusions

We show that the use of genome-wide SNP information can disentangle confounding factors to estimate genetic variances by separating genetic and non-genetic effects. The estimated variance components using realized relationship were more accurate and less biased, compared to those based on pedigree information only. Models that allow the selection of individual SNP in addition to fitting a relationship matrix are more efficient for traits with a significant dominance variance.     

Identification of a Diagnostic Marker To Detect Freshwater Cyanophages of Filamentous Cyanobacteria

Cyanophages are viruses that infect the cyanobacteria, globally important photosynthetic microorganisms. Cyanophages are considered significant components of microbial communities, playing major roles in influencing host community diversity and primary productivity, terminating cyanobacterial water blooms, and influencing biogeochemical cycles. Cyanophages are ubiquitous in both marine and freshwater systems; however, the majority of molecular research has been biased toward the study of marine cyanophages. In this study, a diagnostic probe was developed to detect freshwater cyanophages in natural waters. Oligonucleotide PCR-based primers were designed to specifically amplify the major capsid protein gene from previously characterized freshwater cyanomyoviruses that are infectious to the filamentous, nitrogen-fixing cyanobacterial genera Anabaena and Nostoc. The primers were also successful in yielding PCR products from mixed virus communities concentrated from water samples collected from freshwater lakes in the United Kingdom. The probes are thought to provide a useful tool for the investigation of cyanophage diversity in freshwater environments.     

Apoptosis of vascular smooth muscle cells induces features of plaque vulnerability in atherosclerosis

Vascular smooth muscle cell (VSMC) apoptosis occurs in many arterial diseases, including aneurysm formation, angioplasty restenosis and atherosclerosis. Although VSMC apoptosis promotes vessel remodeling, coagulation and inflammation, its precise contribution to these diseases is unknown, given that apoptosis frequently accompanies vessel injury or alterations to flow. To study the direct consequences of VSMC apoptosis, we generated transgenic mice expressing the human diphtheria toxin receptor (hDTR, encoded by HBEGF) from a minimal Tagln (also known as SM22alpha) promoter. Despite apoptosis inducing loss of 50-70% of VSMCs, normal arteries showed no inflammation, reactive proliferation, thrombosis, remodeling or aneurysm formation. In contrast, VSMC apoptosis in atherosclerotic plaques of SM22alpha-hDTR Apoe-/- mice induced marked thinning of fibrous cap, loss of collagen and matrix, accumulation of cell debris and intense intimal inflammation. We conclude that VSMC apoptosis is 'silent' in normal arteries, which have a large capacity to withstand cell loss. In contrast, VSMC apoptosis alone is sufficient to induce features of plaque vulnerability in atherosclerosis. SM22alpha-hDTR Apoe-/- mice may represent an important new model to test agents proposed to stabilize atherosclerotic plaques.