mCSM–NA: predicting the effects of mutations on protein–nucleic acids interactions

Over the past two decades, several computational methods have been proposed to predict how missense mutations can affect protein structure and function, either by altering protein stability or interactions with its partners, shedding light into potential molecular mechanisms giving rise to different phenotypes. Effectively and efficiently predicting consequences of mutations on protein–nucleic acid interactions, however, remained until recently a great and unmet challenge. Here we report an updated webserver for mCSM–NA, the only scalable method we are aware of capable of quantitatively predicting the effects of mutations in protein coding regions on nucleic acid binding affinities. We have significantly enhanced the original method by including a pharmacophore modelling and information of nucleic acid properties into our graph-based signatures, considering the reverse mutation and by using a refined, more reliable data set, based on a new release of the ProNIT database, which has significantly improved the reliability and applicability of the methodology. Our new predictive model was capable of achieving a correlation coefficient of up to 0.70 on cross-validation and 0.68 on blind-tests, outperforming its previous version. The server is freely available via a user-friendly web interface at: http://structure.bioc.cam.ac.uk/mcsm_na.Jack Brockhoff Foundation [JBF 4186, 2016 to D.B.A.]; Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [MR/M026302/1 to D.B.A. and D.E.V.P.]; National Health and Medical Research Council of Australia [APP1072476 to D.B.A.]; Victorian Life Sciences Computation Initiative (VLSCI), an initiative of the Victorian Government, Australia, on its Facility hosted at the University of Melbourne [UOM0017]; Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil [to D.E.V.P.]; Department of Biochemistry and Molecular Biology, University of Melbourne [to D.B.A.]. Funding for open access charge: MRC

Optimizing genomic medicine in epilepsy through a gene-customized approach to missense variant interpretation

Gene panel and exome sequencing have revealed a high rate of molecular diagnoses among diseases where the genetic architecture has proven suitable for sequencing approaches, with a large number of distinct and highly penetrant causal variants identified among a growing list of disease genes. The challenge is, given the DNA sequence of a new patient, to distinguish disease-causing from benign variants. Large samples of human standing variation data highlight regional variation in the tolerance to missense variation within the protein-coding sequence of genes. This information is not well captured by existing bioinformatic tools, but is effective in improving variant interpretation. To address this limitation in existing tools, we introduce the missense tolerance ratio (MTR), which summarizes available human standing variation data within genes to encapsulate population level genetic variation. We find that patient-ascertained pathogenic variants preferentially cluster in low MTR regions (P < 0.005) of well-informed genes. By evaluating 20 publicly available predictive tools across genes linked to epilepsy, we also highlight the importance of understanding the empirical null distribution of existing prediction tools, as these vary across genes. Subsequently integrating the MTR with the empirically selected bioinformatic tools in a gene-specific approach demonstrates a clear improvement in the ability to predict pathogenic missense variants from background missense variation in disease genes. Among an independent test sample of case and control missense variants, case variants (0.83 median score) consistently achieve higher pathogenicity prediction probabilities than control variants (0.02 median score; Mann-Whitney U test, P < 1 × 10(-16)). We focus on the application to epilepsy genes; however, the framework is applicable to disease genes beyond epilepsy

Achieving selectivity in space and time with DNA double-strand-break response and repair: molecular stages and scaffolds come with strings attached

When double-strand breaks (DSBs) in DNA remain unrepaired, catastrophic loss of genes occurs, leading to translocations, mutations and carcinogenesis. If a sister chromatid is not available at the DNA DSB, nonhomologous end joining (NHEJ) is used to join broken ends. The NHEJ pathway comprises synapsis, end processing and ligation. Here, we ask how DSBs in DNA are repaired efficiently. We suggest that colocation of proteins is achieved over time by the following components: stages, where the main actors are assembled, scaffolds that are erected quickly around broken parts to give access, and strings that tether proteins together. In NHEJ, a $\textit{stage}$ is provided by the Ku heterodimer interacting with DSBs and several other proteins including DNA-PKcs, APLF, BRCA1 and PAXX. A further $\textit{stage}$, DNA-PKcs, links the kinase with DNA, Ku, PARP1, BRCA1 and Artemis. A temporary $\textit{scaffold}$ facilitates repair and is constructed from XRCC4/XLF filaments that bridge Ku bound at DSB ends. LigIV bound to XRCC4 C-termini likely terminates the scaffold, bringing LigIV close to the DNA broken ends. A $\textit{string}$, provided by the Artemis C-terminal region, is intrinsically disordered but includes short linear ‘‘epitopes’’ that recognise DNA-PKcs, LigIV and PTIP, so keeping these components nearby. We show that these stages, scaffolds and strings facilitate colocation and efficient DSB repair. Understanding these processes provides insight into the biology of DNA repair and possible therapeutic intervention in cancer and other diseases.Wellcome Trust (Programme Grant ID: 093167/Z/ 10/Z), National Health and Medical Research Council of Australia (C. J. Martin Research Fellowship, Grant ID: APP1072476), Gates Cambridge ScholarshipThis is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s11224-016-0841-

SDM: a server for predicting effects of mutations on protein stability

Here, we report a webserver for the improved SDM, used for predicting the effects of mutations on protein stability. As a pioneering knowledge-based approach, SDM has been highlighted as the most appropriate method to use in combination with many other approaches. We have updated the environment-specific amino-acid substitution tables based on the current expanded PDB (a 5-fold increase in information), and introduced new residue-conformation and interaction parameters, including packing density and residue depth. The updated server has been extensively tested using a benchmark containing 2690 point mutations from 132 different protein structures. The revised method correlates well against the hypothetical reverse mutations, better than comparable methods built using machine-learning approaches, highlighting the strength of our knowledge-based approach for identifying stabilising mutations. Given a PDB file (a Protein Data Bank file format containing the 3D coordinates of the protein atoms), and a point mutation, the server calculates the stability difference score between the wildtype and mutant protein. The server is available at http://structure.bioc.cam.ac.uk/sdm2Gates HIT-TB and the EU MM4TB [Project ID: 260872 to A.P.P. and T.L.B.]; Bill & Melinda Gates Foundation [RG60453 to B.O.M.]; Jack Brockhoff Foundation [JBF 4186, 2016 to D.B.A.]; C.J. Martin Research Fellowship from the National Health and Medical Research Council of Australia [APP1072476]; Wellcome Trust Programme Grant [093167/Z/10/Z to D.B.A., T.L.B.]; Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) [MR/M026302/1]. Funding for open access charge: Bill & Melinda Gates Foundation [RG60453] Gates HIT-TB; Wellcome Trust Programme Grant [093167/Z/10/Z]; Newton Fund RCUK-CONFAP Grant awarded by the Medical Research Council (MRC) [MR/M026302/1

Functional interactions between polypyrimidine tract binding protein and PRI peptide ligand containing proteins.

Polypyrimidine tract binding protein (PTBP1) is a heterogeneous nuclear ribonucleoprotein (hnRNP) that plays roles in most stages of the life-cycle of pre-mRNA and mRNAs in the nucleus and cytoplasm. PTBP1 has four RNA binding domains of the RNA recognition motif (RRM) family, each of which can bind to pyrimidine motifs. In addition, RRM2 can interact via its dorsal surface with proteins containing short peptide ligands known as PTB RRM2 interacting (PRI) motifs, originally found in the protein Raver1. Here we review our recent progress in understanding the interactions of PTB with RNA and with various proteins containing PRI ligands.This work was supported by the Biotechnology and Biological Sciences Research Council [grant number BB/H004203/1 (to C.W.J.S.)]; the Wellcome Trust [grant number 092900 (to C.W.J.S.)]; the Boehringer Ingelheim Fond (to J.A.); the Medical Research Council [grant number MR/M026302/1 (to D.B.A. and D.E.V.P.)]; the Fundação de Amparo à Pesquisa do Estado de Minas Gerais [grant number MR/M026302/1 (to D.B.A. and D.E.V.P.)]; and the National Health and Medical Research Council CJ Martin Fellowship [grant number APP1072476 (to D.B.A.)]

Arpeggio: A Web Server for Calculating and Visualising Interatomic Interactions in Protein Structures

Interactions between proteins and their ligands, such as small molecules, other proteins, and DNA, depend on specific interatomic interactions that can be classified on the basis of atom type and distance and angle constraints. Visualisation of these interactions provides insights into the nature of molecular recognition events and has practical uses in guiding drug design and understanding the structural and functional impacts of mutations. We present Arpeggio, a web server for calculating interactions within and between proteins and protein, DNA, or small-molecule ligands, including van der Waals', ionic, carbonyl, metal, hydrophobic, and halogen bond contacts, and hydrogen bonds and specific atom-aromatic ring (cation-π, donor-π, halogen-π, and carbon-π) and aromatic ring-aromatic ring (π-π) interactions, within user-submitted macromolecule structures. PyMOL session files can be downloaded, allowing high-quality publication images of the interactions to be generated. Arpeggio is implemented in Python and available as a user-friendly web interface at http://structure.bioc.cam.ac.uk/arpeggio/ and as a downloadable package at https://bitbucket.org/harryjubb/arpeggio.H.C.J. was supported by the Biotechnology and Biological Sciences Research Council and UCB [BB/J500574/1]. B.O.-M. was supported by the Bill and Melinda Gates Foundation. D.B.A. is the recipient of a C. J. Martin Research Fellowship from the National Health and Medical Research Council of Australia (APP1072476) and is funded by the Jack Brockhoff Foundation (JBF 4186, 2016) and a Wellcome Trust Programme Grant to TLB (093167/Z/10/Z). D.B.A. and T.L.B. are funded by a Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (MR/M026302/1). T.L.B. wishes to acknowledge the University of Cambridge and The Wellcome Trust for facilities and support. This work builds on work funded by the Wellcome Trust

Acute weight gain, gender, and therapeutic response to antipsychotics in the treatment of patients with schizophrenia

BACKGROUND: Previous research indicated that women are more vulnerable than men to adverse psychological consequences of weight gain. Other research has suggested that weight gain experienced during antipsychotic therapy may also psychologically impact women more negatively. This study assessed the impact of acute treatment-emergent weight gain on clinical and functional outcomes of patients with schizophrenia by patient gender and antipsychotic treatment (olanzapine or haloperidol). METHODS: Data were drawn from the acute phase (first 6-weeks) of a double-blind randomized clinical trial of olanzapine versus haloperidol in the treatment of 1296 men and 700 women with schizophrenia-spectrum disorders. The associations between weight change and change in core schizophrenia symptoms, depressive symptoms, and functional status were examined post-hoc for men and women and for each medication group. Core schizophrenia symptoms (positive and negative) were measured with the Brief Psychiatric Rating Scale (BPRS), depressive symptoms with the BPRS Anxiety/Depression Scale and the Montgomery-Asberg Depression Rating Scale, and functional status with the mental and physical component scores on the Medical Outcome Survey-Short Form 36. Statistical analysis included methods that controlled for treatment duration. RESULTS: Weight gain during 6-week treatment with olanzapine and haloperidol was significantly associated with improvements in core schizophrenia symptoms, depressive symptoms, mental functioning, and physical functioning for men and women alike. The conditional probability of clinical response (20% reduction in core schizophrenia symptom), given a clinically significant weight gain (at least 7% of baseline weight), showed that about half of the patients who lost weight responded to treatment, whereas three-quarters of the patients who had a clinically significant weight gain responded to treatment. The positive associations between therapeutic response and weight gain were similar for the olanzapine and haloperidol treatment groups. Improved outcomes were, however, more pronounced for the olanzapine-treated patients, and more olanzapine-treated patients gained weight. CONCLUSIONS: The findings of significant relationships between treatment-emergent weight gain and improvements in clinical and functional status at 6-weeks suggest that patients who have greater treatment-emergent weight gain are more likely to benefit from treatment with olanzapine or haloperidol regardless of gender

Predictors of metabolic monitoring among schizophrenia patients with a new episode of second-generation antipsychotic use in the Veterans Health Administration

<p>Abstract</p> <p>Background</p> <p>To examine the baseline metabolic monitoring (MetMon) for second generation antipsychotics (SGA) among patients with schizophrenia in the Veterans Integrated Service Network (VISN) 16 of the Veterans Health Administration (VHA).</p> <p>Methods</p> <p>VISN16 electronic medical records for 10/2002-08/2005 were used to identify patients with schizophrenia who received a new episode of SGA treatment after 10/2003, in which the VISN 16 baseline MetMon program was implemented. Patients who underwent MetMon (MetMon+: either blood glucose or lipid testing records) were compared with patients who did not (MetMon-), on patient characteristics and resource utilization in the year prior to index treatment episode. A parsimonious logistic regression was used to identify predictors for MetMon+ with adjusted odds ratios (OR) and 95% confidence intervals (CI).</p> <p>Results</p> <p>Out of 4,709 patients, 3,568 (75.8%) underwent the baseline MetMon. Compared with the MetMon- group, the MetMon+ patients were found more likely to have baseline diagnoses or mediations for diabetes (OR [CI]: 2.336 [1.846-2.955]), dyslipidemia (2.439 [2.029-2.932]), and hypertension (1.497 [1.287-1.743]), substance use disorders (1.460 [1.257-1.696]), or to be recorded as obesity (2.052 [1.724-2.443]). Increased likelihood for monitoring were positively associated with number of antipsychotics during the previous year (FGA: 1.434 [1.129-1.821]; SGA: 1.503 [1.290-1.751]). Other significant predictors for monitoring were more augmentation episodes (1.580 [1.145-2.179]), more outpatient visits (1.007 [1.002-1.013])), hospitalization days (1.011 [1.007-1.015]), and longer duration of antipsychotic use (1.001 [1.001-1.001]). Among the MetMon+ group, approximately 38.9% patient had metabolic syndrome.</p> <p>Discussion</p> <p>This wide time window of 180 days, although congruent with the VHA guidelines for the baseline MetMon process, needs to be re-evaluated and narrowed down, so that optimally the monitoring event occurs at the time of receiving a new episode of SGA treatment. Future research will examine whether or not patients prescribed an SGA are assessed for metabolic syndrome following the index episode of antipsychotic therapy, and whether or not such baseline and follow-up monitoring programs in routine care are cost-effective.</p> <p>Conclusion</p> <p>The baseline MetMon has been performed for a majority of the VISN 16 patients with schizophrenia prior to index SGA over the study period. Compared with MetMon- group, MetMon+ patients were more likely to be obese and manifest a more severe illness profile.</p