Analysis of protein main-chain solvation as a function of secondary structure

We have analysed the hydration of main-chain carbonyl and amide groups in 24 high-resolution well-refined protein structures as a function of the secondary structure in which these polar groups occur. We find that main-chain atoms in beta-sheets are as hydrated as those in alpha-helices, with most interactions involving "free" amide and carbonyl groups that do not participate in secondary structure hydrogen bonds. The distributions of water molecules around these non-bonded carbonyl groups reflect specific steric interactions due to the local secondary structure. Approximately 20% and 4%, respectively of bonded carbonyl and amide groups interact with solvent. These include interactions with carbonyl groups on the exposed faces of alpha-helices that have been correlated previously with bending of the helix. Water molecules interacting with alpha-helices occur mainly at the amino and carbonyl termini of the helices, in which case the solvent sites maintain the hydrogen bonding by bridging between residues i and i-3 or i-4 at the amino terminus and between i and i+3 or i+4 at the carbonyl terminus. We also see a number of solvent-mediated Ncap and Ccap interactions. The water molecules interacting with beta-sheets occur mainly at the edges, in which case they extend the sheet structure, or at the ends of strands, in which case they extend the beta-ladder. In summary, the solvent networks appear to extend the hydrogen-bonding structure of the secondary structures. In beta-turns, which usually occur at the surface of a protein, exposed amide and carbonyl groups are often hydrated, especially close to glycine residues. Occasionally water molecules form a bridge between residues i and i+3 in the turn and this may provide extra stabilization.     

Identification of Targeted Analyte Clusters for Studies of Schizophrenia

The search for biomarkers to diagnose psychiatric disorders such as schizophrenia has been underway for decades. Many molecular profiling studies in this field have focused on identifying individual marker signals that show significant differences in expression between patients and the normal population. However, signals for multiple analyte combinations that exhibit patterned behaviors have been less exploited. Here, we present a novel approach for identifying biomarkers of schizophrenia using expression of serum analytes from first onset, drug-naïve patients and normal controls. The strength of patterned signals was amplified by analyzing data in reproducing kernel spaces. This resulted in the identification of small sets of analytes referred to as targeted clusters that have discriminative power specifically for schizophrenia in both human and rat models. These clusters were associated with specific molecular signaling pathways and less strongly related to other neuropsychiatric disorders such as major depressive disorder and bipolar disorder. These results shed new light concerning how complex neuropsychiatric diseases behave at the pathway level and demonstrate the power of this approach in identification of disease-specific biomarkers and potential novel therapeutic strategies.Schizophrenia is a debilitating neuropsychiatric disorder that affects more than 1% of the world population and costs hundreds of billions of United States dollars in healthcare provision and lost earnings (1). The diagnosis of this disease has not changed substantially over several decades and currently relies on subjective psychopathological ratings such as the Diagnostic and Statistical Manual of Mental Disorders (DSM)1-IV. Thus, diagnosis can be complicated by the presence of overlapping symptoms frequently occurring in other psychiatric illnesses such as bipolar disorder (BD) and major depressive disorder (MDD) and by the presence of confounding factors such as drug abuse and co-morbidities. This often results in diagnosis being delayed for several months to years. A delay in establishing an accurate diagnosis can have serious deleterious implications because a late or imprecise diagnosis can contribute to unsatisfactory outcomes to currently used drug therapies and to higher rates of relapse (2). Most importantly, more than half of schizophrenia subjects develop a progressive course of the disease associated with deficit symptoms (3).In contrast, early therapeutic intervention holds promise in preventing or diminishing such effects (4–6). An empirical assay for early and accurate diagnosis of schizophrenia would deliver improved patient outcomes and reduce the costs of the disease for healthcare services and society (7–9). Such an assay could also provide a means of stratifying patients and monitoring drug responses and may also lead to the development of translational medicine tools that are critical for discovery of novel therapeutic strategies. Molecular profiling methods that afford the simultaneous measurement of multiple analytes in clinical and preclinical samples have considerable promise in this endeavor. These methods have been aimed predominantly at identifying individual molecules that show differences in expression between the disease and control conditions. However, such studies have often been fraught with small fold-changes in analyte levels, a common obstacle when investigating complex neuropsychiatric disorders (10–12). Thus, standard statistical techniques such as t tests will not be able to explore patterned behaviors involving proteins that have subtle expression changes but still contribute to the development of schizophrenia.The main objective of this study was to determine whether unique patterns of biomarkers can be identified for subjects with first onset antipsychotic-naïve schizophrenia. Analyte expression lists were generated using the Multi-Analyte Profiling (MAP®) fluorescent bead-based technology for profiling serum samples from 77 male schizophrenia patients and 66 matched male controls. For comparison with other psychiatric disorders, we also analyzed the serum samples of 13 male BD and 17 male MDD patients. In parallel, serum samples from four relevant animal models were also profiled for comparison with the human disease state. Analysis of the respective expression lists was carried out using non-linear statistical analysis, which identifies small sets of analytes called targeted analyte clusters (TACs) that have the power to discriminate the patients from normal controls. We present here the performance of these clusters for diagnosis of schizophrenia. In addition, we show how this method can also contribute to increasing our understanding of the etiology of the disorder by determining its ability to classify various preclinical models of psychiatric disorders. The biological pathways associated with these clusters are discussed with their relevance to schizophrenia.     

Prediction of the three-dimensional structure of aflatoxin of Aspergillus flavus by homology modelling

Aflatoxins are polyketide-derived secondary metabolites produced by Aspergillus spp. The toxic effects of aflatoxins have adverse consequences for human health and agricultural economics. The aflR gene, a regulatory gene for aflatoxin biosynthesis, encodes a protein containing a zinc-finger DNA-binding motif. AFLR-Protein three-dimensional model was generated using Robetta server. The modeled AFLR-Protein was further optimization and validation using Rampage. In the simulations, we monitored the backbone atoms and the C-α-helix of the modeled protein. The low RMSD and the simulation time indicate that, as expected, the 3D structural model of AFLR-protein represents a stable folding conformation. This study paves the way for generating computer molecular models for proteins whose crystal structures are not available and which would aid in detailed molecular mechanism of inhibition of aflatoxin.     

Bioremediation of toxic heavy metals using acidothermophilic autotrophes

Investigations were carried out to isolate microbial strains from soil, mud and water samples from metallurgically polluted environment for bioremediation of toxic heavy metals. As a result of primary and secondary screening various 72 acidothermophilic autotrophic microbes were isolated and adapted for metal tolerance and biosorption potentiality. The multi-metal tolerance was developed with higher gradient of concentrations of Ag, As, Bi, Cd, Cr, Co, Cu, Hg, Li, Mo, Pb, Sn and Zn. The isolates were checked for their biosolubilization ability with copper containing metal sulfide ores. In case of chalcopyrite 85.82% and in covellite as high as 97.5% copper solubilization occurred in presence of 10(-3) M multi-heavy metals on fifth day at 55 degrees C and pH 2.5. Chemical analyses were carried out by inductively coupled plasma spectroscopy (ICP) for metal absorption. The selected highly potential isolate (ATh-14) showed maximum adsorption of Ag 73%, followed by Pb 35%, Zn 34%, As 19%, Ni 15% and Cr 9% in chalcopyrite.     

Sequence scanning chicken cosmids: a methodology for genome screening

The chicken genome is relatively poorly studied at the molecular level. The karyotype 2n=78 is divided into three main chromosomal sub-groups: the macrochromosomes (six pairs), the intermediate microchromosomes (four pairs) and the microchromosomes (29 pairs). Whilst the microchromosome group comprise only 25% of the DNA, increasing evidence is proving that this is disproportionate to their gene content. This paper demonstrates the utility of cosmid sequence scanning as a potential method for analysing the chicken genome, providing an economical method for the production of a molecular map. The GC content, gene density and repeat distribution are analysed relative to chromosomal origin. Results indicate that gene density is higher on the microchromosomes. During the scanning process an example of conserved linkage between chicken and human (12q34.2) has been demonstrated.     

Fugu orthologues of human major histocompatibility complex genes: a genome survey

The major histocompatibility complex (MHC) region in fish has been subjected to piecemeal analysis centering on the in-depth characterization of single genes. The emphasis has been on those genes proven to be involved in the immune response such as the class I and class II antigen presenting genes and the complement genes. The Fugu genome data presents the opportunity to examine the short-range linkage of potentially all the human MHC orthologues and examine conserved synteny with the human and, to a more limited extent, zebrafish genomes. Analysis confirms the existence of a limited MHC locus in Fugu comprising the MHC class Ia genes and associated class II region genes involved in class I antigen presentation. Identification of additional human MHC orthologues indicates the completely dispersed nature of this region in fish, with a maximum of six MHC genes maintained within close proximity in any one contig. The majority of the other genes are present in the genome data as either singletons or pairs. Comparison with zebrafish substantiates previously observed linkages between class III region orthologues and hints at an ancient conserved class III region.     

Mapping the amino acid properties of constituent nucleoporins onto the yeast nuclear pore complex

Visualization of molecular structures aids in the understanding of structural and functional roles of biological macromolecules. Macromolecular transport between the cell nucleus and cytoplasm is facilitated by the nuclear pore complex (NPC). The ring structure of the NPC is large and contains several distinct proteins (nucleoporins) which function as a selective gate for the passage of certain molecules into and out of the nucleus. In this note we demonstrate the utility of a python code that allows direct mapping of the physiochemical properties of the constituent nucleoporins on the scaffold of the yeast NPC׳s cytoplasmic view. We expect this tool to be useful for researchers to visualize the NPC based on their physiochemical properties and how it alters when specific mutations are introduced in one or more of the nucleoporins. The code developed using Python is available freely from the authors.     

Reference cDNA library facilities available from European sources

cDNA libraries are the cornerstone of efforts to identify the relatively small regions of genomes that are responsible for biological effects. Gene hunter seeking candidate genes, via a variety of approaches, ultimately focus on the cloning, sequencing, and expression of cDNAs. Assistance is now available to researchers in the form of genome programs, whose initial goals include assembly of a complete collection of expressed sequences derived from the genome of interest. The concept of reference sets of cDNA libraries is that the aims of genome programs are served most effectively by different laboratories working on a common set of high-quality arrayed cDNA libraries, using different experimental approaches, thereby reducing unnecessary duplication of effort, and maximizing the amount of information that one set of resources can provide.     

Comprehensive two-dimensional liquid chromatography mass spectrometric profiling of the rat hippocampal proteome

In this study, we performed the first high‐throughput and comprehensive proteomic profiling of the rat hippocampal proteome. Using a combination of 2‐D LC‐MS and data analysis with the Rosetta Elucidator^® system, we identified 1340 unique proteins. Functional classification showed that most of these were associated with synaptic function and comprised a high proportion of phosphorylated proteins and analytically challenging classes of membrane proteins such as ion channel receptor subunits.