98 research outputs found

    Predicting active site residue annotations in the Pfam database

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    <p>Abstract</p> <p>Background</p> <p>Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for catalysis determined. To increase the active site annotations in the Pfam database, we have developed a strict set of rules, chosen to reduce the rate of false positives, which enable the transfer of experimentally determined active site residue data to other sequences within the same Pfam family.</p> <p>Description</p> <p>We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and <it>MEROPS </it>we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives.</p> <p>Conclusion</p> <p>We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.</p

    Deciphering the Arginine-Binding Preferences at the Substrate-Binding Groove of Ser/Thr Kinases by Computational Surface Mapping

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    Protein kinases are key signaling enzymes that catalyze the transfer of γ-phosphate from an ATP molecule to a phospho-accepting residue in the substrate. Unraveling the molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor is important for understanding kinase specificities toward their substrates and for designing substrate-like peptidic inhibitors. We applied ANCHORSmap, a new fragment-based computational approach for mapping amino acid side chains on protein surfaces, to predict and characterize the preference of kinases toward Arginine binding. We focus on positions P−2 and P−5, commonly occupied by Arginine (Arg) in substrates of basophilic Ser/Thr kinases. The method accurately identified all the P−2/P−5 Arg binding sites previously determined by X-ray crystallography and produced Arg preferences that corresponded to those experimentally found by peptide arrays. The predicted Arg-binding positions and their associated pockets were analyzed in terms of shape, physicochemical properties, amino acid composition, and in-silico mutagenesis, providing structural rationalization for previously unexplained trends in kinase preferences toward Arg moieties. This methodology sheds light on several kinases that were described in the literature as having non-trivial preferences for Arg, and provides some surprising departures from the prevailing views regarding residues that determine kinase specificity toward Arg. In particular, we found that the preference for a P−5 Arg is not necessarily governed by the 170/230 acidic pair, as was previously assumed, but by several different pairs of acidic residues, selected from positions 133, 169, and 230 (PKA numbering). The acidic residue at position 230 serves as a pivotal element in recognizing Arg from both the P−2 and P−5 positions

    Multidisciplinary management of acromegaly: A consensus.

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    The 13th Acromegaly Consensus Conference was held in November 2019 in Fort Lauderdale, Florida, and comprised acromegaly experts including endocrinologists and neurosurgeons who considered optimal approaches for multidisciplinary acromegaly management. Focused discussions reviewed techniques, results, and side effects of surgery, radiotherapy, and medical therapy, and how advances in technology and novel techniques have changed the way these modalities are used alone or in combination. Effects of treatment on patient outcomes were considered, along with strategies for optimizing and personalizing therapeutic approaches. Expert consensus recommendations emphasize how best to implement available treatment options as part of a multidisciplinary approach at Pituitary Tumor Centers of Excellence

    Final results from the PERUSE study of first-line pertuzumab plus trastuzumab plus a taxane for HER2-positive locally recurrent or metastatic breast cancer, with a multivariable approach to guide prognostication

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    Background: The phase III CLinical Evaluation Of Pertuzumab And TRAstuzumab (CLEOPATRA) trial established the combination of pertuzumab, trastuzumab and docetaxel as standard first-line therapy for human epidermal growth factor receptor 2 (HER2)-positive locally recurrent/metastatic breast cancer (LR/mBC). The multicentre single-arm PERtUzumab global SafEty (PERUSE) study assessed the safety and efficacy of pertuzumab and trastuzumab combined with investigator-selected taxane in this setting. Patients and methods: Eligible patients with inoperable HER2-positive LR/mBC and no prior systemic therapy for LR/mBC (except endocrine therapy) received docetaxel, paclitaxel or nab-paclitaxel with trastuzumab and pertuzumab until disease progression or unacceptable toxicity. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS) and overall survival (OS). Prespecified subgroup analyses included subgroups according to taxane, hormone receptor (HR) status and prior trastuzumab. Exploratory univariable analyses identified potential prognostic factors; those that remained significant in multivariable analysis were used to analyse PFS and OS in subgroups with all, some or none of these factors. Results: Of 1436 treated patients, 588 (41%) initially received paclitaxel and 918 (64%) had HR-positive disease. The most common grade 653 adverse events were neutropenia (10%, mainly with docetaxel) and diarrhoea (8%). At the final analysis (median follow-up: 5.7 years), median PFS was 20.7 [95% confidence interval (CI) 18.9-23.1] months overall and was similar irrespective of HR status or taxane. Median OS was 65.3 (95% CI 60.9-70.9) months overall. OS was similar regardless of taxane backbone but was more favourable in patients with HR-positive than HR-negative LR/mBC. In exploratory analyses, trastuzumab-pretreated patients with visceral disease had the shortest median PFS (13.1 months) and OS (46.3 months). Conclusions: Mature results from PERUSE show a safety and efficacy profile consistent with results from CLEOPATRA and median OS exceeding 5 years. Results suggest that paclitaxel is a valid alternative to docetaxel as backbone chemotherapy. Exploratory analyses suggest risk factors that could guide future trial design

    Final results from the PERUSE study of first-line pertuzumab plus trastuzumab plus a taxane for HER2-positive locally recurrent or metastatic breast cancer, with a multivariable approach to guide prognostication

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    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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