Application of classical molecular dynamics for evaluation of proton transfer mechanism on a protein

AbstractProton transfer reactions on surfaces are prevalent in biology, chemistry and physics. In the present study, we employed classical Molecular Dynamics simulations to search for the presence of transient configurations that enable proton transfer, or proton sharing, between adjacent carboxylate groups on the protein surface. The results demonstrate that, during random fluctuations of the residues on the surface, there are repeated situations in which nearby carboxylates either share a common proton through a hydrogen bond, or are connected by a few water molecules that form conducting networks. These networks do not extend out of the common Coulomb cage of the participating residues and the lifetimes of the bridged structures are sufficiently long to allow passage of a proton between the carboxylates. The detection of domains capable of supporting a rapid proton transfer on a protein supports the notion that clusters of carboxylates are the operative elements of proton collecting antennae, as in bacteriorhodopsin, cytochrome c oxidase or the photosynthetic reaction center

Haplotype structure and selection of the MDM2 oncogene in humans

The MDM2 protein is an ubiquitin ligase that plays a critical role in regulating the levels and activity of the p53 protein, which is a central tumor suppressor. A SNP in the human MDM2 gene (SNP309 T/G) occurs at frequencies dependent on demographic history and has been shown to have important differential effects on the activity of the MDM2 and p53 proteins and to associate with altered risk for the development of several cancers. In this report, the haplotype structure of the MDM2 gene is determined by using 14 different SNPs across the gene from three different population samples: Caucasians, African Americans, and the Ashkenazi Jewish ethnic group. The results presented in this report indicate that there is a substantially reduced variability of the deleterious SNP309 G allele haplotype in all three populations studied, whereas multiple common T allele haplotypes were found in all three populations. This observation, coupled with the relatively high frequency of the G allele haplotype in both and Caucasian and Ashkenazi Jewish population data sets, suggests that this haplotype could have undergone a recent positive selection sweep. An entropy-based selection test is presented that explicitly takes into account the correlations between different SNPs, and the analysis of MDM2 reveals a significant departure from the standard assumptions of selective neutrality

Alternative Splicing Regulates Targeting of Malate Dehydrogenase in Yarrowia lipolytica

Alternative pre-mRNA splicing is a major mechanism contributing to the proteome complexity of most eukaryotes, especially mammals. In less complex organisms, such as yeasts, the numbers of genes that contain introns are low and cases of alternative splicing (AS) with functional implications are rare. We report the first case of AS with functional consequences in the yeast Yarrowia lipolytica. The splicing pattern was found to govern the cellular localization of malate dehydrogenase, an enzyme of the central carbon metabolism. This ubiquitous enzyme is involved in the tricarboxylic acid cycle in mitochondria and in the glyoxylate cycle, which takes place in peroxisomes and the cytosol. In Saccharomyces cerevisiae, three genes encode three compartment-specific enzymes. In contrast, only two genes exist in Y. lipolytica. One gene (YlMDH1, YALI0D16753g) encodes a predicted mitochondrial protein, whereas the second gene (YlMDH2, YALI0E14190g) generates the cytosolic and peroxisomal forms through the alternative use of two 3′-splice sites in the second intron. Both splicing variants were detected in cDNA libraries obtained from cells grown under different conditions. Mutants expressing the individual YlMdh2p isoforms tagged with fluorescent proteins confirmed that they localized to either the cytosolic or the peroxisomal compartment

The Dynamics of Ca2+ Ions within the Solvation Shell of Calbindin D9k

The encounter of a Ca2+ ion with a protein and its subsequent binding to specific binding sites is an intricate process that cannot be fully elucidated from experimental observations. We have applied Molecular Dynamics to study this process with atomistic details, using Calbindin D9k (CaB) as a model protein. The simulations show that in most of the time the Ca2+ ion spends within the Debye radius of CaB, it is being detained at the 1st and 2nd solvation shells. While being detained near the protein, the diffusion coefficient of the ion is significantly reduced. However, due to the relatively long period of detainment, the ion can scan an appreciable surface of the protein. The enhanced propagation of the ion on the surface has a functional role: significantly increasing the ability of the ion to scan the protein's surface before being dispersed to the bulk. The contribution of this mechanism to Ca2+ binding becomes significant at low ion concentrations, where the intervals between successive encounters with the protein are getting longer. The efficiency of the surface diffusion is affected by the distribution of charges on the protein's surface. Comparison of the Ca2+ binding dynamics in CaB and its E60D mutant reveals that in the wild type (WT) protein the carboxylate of E60 function as a preferred landing-site for the Ca2+ arriving from the bulk, followed by delivering it to the final binding site. Replacement of the glutamate by aspartate significantly reduced the ability to transfer Ca2+ ions from D60 to the final binding site, explaining the observed decrement in the affinity of the mutated protein to Ca2+

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen.Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.Peer reviewe