Protein-ligand binding region prediction (PLB-SAVE) based on geometric features and CUDA acceleration

[[abstract]]Background Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. Results Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. Conclusions In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance for protein-ligand binding region prediction. Based on the same approach and rationale, this method can also be applied to predict carbohydrate-antibody interactions for further design and development of carbohydrate-based vaccines. PLB-SAVE is available at http://save.cs.ntou.edu.tw.[[booktype]]電子

Predicting the Severity and Prognosis of Trismus after Intensity-Modulated Radiation Therapy for Oral Cancer Patients by Magnetic Resonance Imaging

To develop magnetic resonance imaging (MRI) indicators to predict trismus outcome for post-operative oral cavity cancer patients who received adjuvant intensity-modulated radiation therapy (IMRT), 22 patients with oral cancer treated with IMRT were studied over a two-year period. Signal abnormality scores (SA scores) were computed from Likert-type ratings of the abnormalities of nine masticator structures and compared with the Mann-Whitney U-test and Kruskal–Wallis one-way ANOVA test between groups. Seventeen patients (77.3%) experienced different degrees of trismus during the two-year follow-up period. The SA score correlated with the trismus grade (r = 0.52, p<0.005). Patients having progressive trismus had higher mean doses of radiation to multiple structures, including the masticator and lateral pterygoid muscles, and the parotid gland (p<0.05). In addition, this group also had higher SA-masticator muscle dose product at 6 months and SA scores at 12 months (p<0.05). At the optimum cut-off points of 0.38 for the propensity score, the sensitivity was 100% and the specificity was 93% for predicting the prognosis of the trismus patients. The SA score, as determined using MRI, can reflect the radiation injury and correlate to trismus severity. Together with the radiation dose, it could serve as a useful biomarker to predict the outcome and guide the management of trismus following radiation therapy

Social Cognitive Role of Schizophrenia Candidate Gene GABRB2

10.1371/journal.pone.0062322PLoS ONE84

A Recombination Hotspot in a Schizophrenia-Associated Region of GABRB2

Background: Schizophrenia is a major disorder with complex genetic mechanisms. Earlier, population genetic studies revealed the occurrence of strong positive selection in the GABRB2 gene encoding the β2 subunit of GABAA receptors, within a segment of 3,551 bp harboring twenty-nine single nucleotide polymorphisms (SNPs) and containing schizophrenia-associated SNPs and haplotypes. Methodology/Principal Findings:In the present study, the possible occurrence of recombination in this 'S1-S29' segment was assessed. The occurrence of hotspot recombination was indicated by high resolution recombination rate estimation, haplotype diversity, abundance of rare haplotypes, recurrent mutations and torsos in haplotype networks, and experimental haplotyping of somatic and sperm DNA. The sub-segment distribution of relative recombination strength, measured by the ratio of haplotype diversity (Hd) over mutation rate (θ), was indicative of a human specific Alu-Yi6 insertion serving as a central recombining sequence facilitating homologous recombination. Local anomalous DNA conformation attributable to the Alu-Yi6 element, as suggested by enhanced DNase I sensitivity and obstruction to DNA sequencing, could be a contributing factor of the increased sequence diversity. Linkage disequilibrium (LD) analysis yielded prominent low LD points that supported ongoing recombination. LD contrast revealed significant dissimilarity between control and schizophrenic cohorts. Among the large array of inferred haplotypes, H26 and H73 were identified to be protective, and H19 and H81 risk-conferring, toward the development of schizophrenia. Conclusions/Significance: The co-occurrence of hotspot recombination and positive selection in the S1-S29 segment of GABRB2 has provided a plausible contribution to the molecular genetics mechanisms for schizophrenia. The present findings therefore suggest that genome regions characterized by the co-occurrence of positive selection and hotspot recombination, two interacting factors both affecting genetic diversity, merit close scrutiny with respect to the etiology of common complex disorders. © 2010 Ng et al

Alternative-Splicing in the Exon-10 Region of GABAA Receptor β2 Subunit Gene: Relationships between Novel Isoforms and Psychotic Disorders

BACKGROUND: Non-coding single nucleotide polymorphisms (SNPs) in GABRB2, the gene for beta(2)-subunit of gamma-aminobutyric acid type A (GABA(A)) receptor, have been associated with schizophrenia (SCZ) and quantitatively correlated to mRNA expression and alternative splicing. METHODS AND FINDINGS: Expression of the Exon 10 region of GABRB2 from minigene constructs revealed this region to be an "alternative splicing hotspot" that readily gave rise to differently spliced isoforms depending on intron sequences. This led to a search in human brain cDNA libraries, and the discovery of two novel isoforms, beta(2S1) and beta(2S2), bearing variations in the neighborhood of Exon-10. Quantitative real-time PCR analysis of postmortem brain samples showed increased beta(2S1) expression and decreased beta(2S2) expression in both SCZ and bipolar disorder (BPD) compared to controls. Disease-control differences were significantly correlated with SNP rs187269 in BPD males for both beta(2S1) and beta(2S2) expressions, and significantly correlated with SNPs rs2546620 and rs187269 in SCZ males for beta(2S2) expression. Moreover, site-directed mutagenesis indicated that Thr(365), a potential phosphorylation site in Exon-10, played a key role in determining the time profile of the ATP-dependent electrophysiological current run-down. CONCLUSION: This study therefore provided experimental evidence for the importance of non-coding sequences in the Exon-10 region in GABRB2 with respect to beta(2)-subunit splicing diversity and the etiologies of SCZ and BPD

Clinical association of body symptoms and primary dysmenorrhea among young and middle-aged women: an observational study

BackgroundThe mechanism of primary dysmenorrhea remains unraveled. Body symptoms not related to menstrual cycle may indicate the potential mechanism of primary dysmenorrhea, albeit the association has not been proven. Furthermore, we hypothesize that the cumulative burden of these symptoms may influence the incidence of primary dysmenorrhea. Therefore, we aim to design a study to identify bodily symptoms potentially related to primary dysmenorrhea and test the hypothesis in understanding and managing primary dysmenorrhea.MethodsA total of 3,140 female participants aged 30–50 years were enrolled from the Taiwan Biobank. Stepwise logistic regression was used to select potential body symptoms associated with primary dysmenorrhea from a training dataset. Selected body symptoms were validated in a test dataset. Female participants without dysmenorrhea in the baseline survey were divided into two groups (with and without body symptoms) in a baseline survey. Cox regression and Kaplan-Meier survival analyses were used to evaluate the risk of incident dysmenorrhea.ResultsWomen with body symptoms such as cold extremities (adjusted odds ratio [AdjOR], 1.53, 95% confidence interval [CI], 1.12–2.21), dull abdominal pain (AdjOR, 1.45, 95% CI, 1.03–2.04), and edema (AdjOR, 1.43, 95% CI, 1.02–1.99) were significantly associated with dysmenorrhea. Women with the three body symptoms had a significantly higher risk of dysmenorrhea (adjusted hazard ratio, 2.74, 95%CI, 1.18–6.31; log-rank test, p = 0.0017) than those without body symptoms. Trend analysis showed that the risk of dysmenorrhea increased with the number of body symptoms (p-trend = 0.025).ConclusionThis study identified cold extremities, dull abdominal pain, and edema as predictors of primary dysmenorrhea, with their accumulation associated with a higher risk of developing dysmenorrhea. We propose that further research explore pharmacological and non-pharmacological interventions targeting these symptoms, as they may provide long-term benefits in the management of primary dysmenorrhea

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Synthetic BZLF1-targeted transcriptional activator for efficient lytic induction therapy against EBV-associated epithelial cancers.

The unique virus-cell interaction in Epstein-Barr virus (EBV)-associated malignancies implies targeting the viral latent-lytic switch is a promising therapeutic strategy. However, the lack of specific and efficient therapeutic agents to induce lytic cycle in these cancers is a major challenge facing clinical implementation. We develop a synthetic transcriptional activator that specifically activates endogenous BZLF1 and efficiently induces lytic reactivation in EBV-positive cancer cells. A lipid nanoparticle encapsulating nucleoside-modified mRNA which encodes a BZLF1-specific transcriptional activator (mTZ3-LNP) is synthesized for EBV-targeted therapy. Compared with conventional chemical inducers, mTZ3-LNP more efficiently activates EBV lytic gene expression in EBV-associated epithelial cancers. Here we show the potency and safety of treatment with mTZ3-LNP to suppress tumor growth in EBV-positive cancer models. The combination of mTZ3-LNP and ganciclovir yields highly selective cytotoxic effects of mRNA-based lytic induction therapy against EBV-positive tumor cells, indicating the potential of mRNA nanomedicine in the treatment of EBV-associated epithelial cancers

Positive Selection within the Schizophrenia-Associated GABA(A) Receptor β(2) Gene

The gamma-aminobutyric acid type-A (GABA(A)) receptor plays a major role in inhibitory neurotransmissions. Intronic SNPs and haplotypes in GABRB2, the gene for GABA(A) receptor β(2) subunit, are associated with schizophrenia and correlated with the expression of two alternatively spliced β(2) isoforms. In the present study, using chimpanzee as an ancestral reference, high frequencies were observed for the derived (D) alleles of the four SNPs rs6556547, rs187269, rs1816071 and rs1816072 in GABRB2, suggesting the occurrence of positive selection for these derived alleles. Coalescence-based simulation showed that the population frequency spectra and the frequencies of H56, the haplotype having all four D alleles, significantly deviated from neutral-evolution expectation in various demographic models. Haplotypes containing the derived allele of rs1816072 displayed significantly less diversity compared to haplotypes containing its ancestral allele, further supporting positive selection. The variations in DD-genotype frequencies in five human populations provided a snapshot of the evolutionary history, which suggested that the positive selections of the D alleles are recent and likely ongoing. The divergence between the DD-genotype profiles of schizophrenic and control samples pointed to the schizophrenia-relevance of positive selections, with the schizophrenic samples showing weakened selections compared to the controls. These DD-genotypes were previously found to increase the expression of β(2), especially its long isoform. Electrophysiological analysis showed that this long β(2) isoform favored by the positive selections is more sensitive than the short isoform to the inhibition of GABA(A) receptor function by energy depletion. These findings represent the first demonstration of positive selection in a schizophrenia-associated gene