Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2

RosettaDock has been increasingly used in protein docking and design strategies in order to predict the structure of protein-protein interfaces. Here we test capabilities of RosettaDock 3.2, part of the newly developed Rosetta v3.2 modeling suite, against Docking Benchmark 3.0, and compare it with RosettaDock v2.3, the latest version of the previous Rosetta software package. The benchmark contains a diverse set of 116 docking targets including 22 antibody-antigen complexes, 33 enzyme-inhibitor complexes, and 60 ‘other’ complexes. These targets were further classified by expected docking difficulty into 84 rigid-body targets, 17 medium targets, and 14 difficult targets. We carried out local docking perturbations for each target, using the unbound structures when available, in both RosettaDock v2.3 and v3.2. Overall the performances of RosettaDock v2.3 and v3.2 were similar. RosettaDock v3.2 achieved 56 docking funnels, compared to 49 in v2.3. A breakdown of docking performance by protein complex type shows that RosettaDock v3.2 achieved docking funnels for 63% of antibody-antigen targets, 62% of enzyme-inhibitor targets, and 35% of ‘other’ targets. In terms of docking difficulty, RosettaDock v3.2 achieved funnels for 58% of rigid-body targets, 30% of medium targets, and 14% of difficult targets. For targets that failed, we carry out additional analyses to identify the cause of failure, which showed that binding-induced backbone conformation changes account for a majority of failures. We also present a bootstrap statistical analysis that quantifies the reliability of the stochastic docking results. Finally, we demonstrate the additional functionality available in RosettaDock v3.2 by incorporating small-molecules and non-protein co-factors in docking of a smaller target set. This study marks the most extensive benchmarking of the RosettaDock module to date and establishes a baseline for future research in protein interface modeling and structure prediction

Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system? Using a computational network model for the dominant neural populations of the olfactory bulb we show that fundamental aspects of the adult neurogenesis observed in the olfactory bulb -- the persistent addition of new inhibitory granule cells to the network, their activity-dependent survival, and the reciprocal character of their synapses with the principal mitral cells -- are sufficient to restructure the network and to alter its encoding of odor stimuli adaptively so as to reduce the correlations between the bulbar representations of similar stimuli. The decorrelation is quite robust with respect to various types of perturbations of the reciprocity. The model parsimoniously captures the experimentally observed role of neurogenesis in perceptual learning and the enhanced response of young granule cells to novel stimuli. Moreover, it makes specific predictions for the type of odor enrichment that should be effective in enhancing the ability of animals to discriminate similar odor mixtures

Modeling Peripheral Olfactory Coding in Drosophila Larvae

The Drosophila larva possesses just 21 unique and identifiable pairs of olfactory sensory neurons (OSNs), enabling investigation of the contribution of individual OSN classes to the peripheral olfactory code. We combined electrophysiological and computational modeling to explore the nature of the peripheral olfactory code in situ. We recorded firing responses of 19/21 OSNs to a panel of 19 odors. This was achieved by creating larvae expressing just one functioning class of odorant receptor, and hence OSN. Odor response profiles of each OSN class were highly specific and unique. However many OSN-odor pairs yielded variable responses, some of which were statistically indistinguishable from background activity. We used these electrophysiological data, incorporating both responses and spontaneous firing activity, to develop a Bayesian decoding model of olfactory processing. The model was able to accurately predict odor identity from raw OSN responses; prediction accuracy ranged from 12%–77% (mean for all odors 45.2%) but was always significantly above chance (5.6%). However, there was no correlation between prediction accuracy for a given odor and the strength of responses of wild-type larvae to the same odor in a behavioral assay. We also used the model to predict the ability of the code to discriminate between pairs of odors. Some of these predictions were supported in a behavioral discrimination (masking) assay but others were not. We conclude that our model of the peripheral code represents basic features of odor detection and discrimination, yielding insights into the information available to higher processing structures in the brain

Hepatobiliary and pancreatic tuberculosis: A two decade experience

<p>Abstract</p> <p>Background</p> <p>Isolated hepatobiliary or pancreatic tuberculosis (TB) is rare and preoperative diagnosis is difficult. We reviewed our experience over a period two decades with this rare site of abdominal tuberculosis.</p> <p>Methods</p> <p>The records of 18 patients with proven histological diagnosis of hepatobiliary and pancreatic tuberculosis were reviewed retrospectively. The demographic features, sign and symptoms, imaging, cytology/histopathology, procedures performed, outcome and follow up data were obtained from the departmental records. The diagnosis of tuberculosis was based on granuloma with caseation necrosis on histopathology or presence of acid fast bacilli.</p> <p>Results</p> <p>Of 18 patients (11 men), 11 had hepatobiliary TB while 7 had pancreatic TB. Two-thirds of the patients were < 40 years (mean: 42 yrs; range 19–70 yrs). The duration of the symptoms varied between 2 weeks to 104 weeks (mean: 20 weeks). The most common symptom was pain in the abdomen (n = 13), followed by jaundice (n = 10), fever, anorexia and weight loss (n = 9). Five patients (28%) had associated extra-abdominal TB which helped in preoperative diagnosis in 3 patients. Imaging demonstrated extrahepatic bile duct obstruction in the patients with jaundice and in addition picked up liver, gallbladder and pancreatic masses with or without lymphadenopathy (peripancreatic/periportal). Preoperative diagnosis was made in 4 patients and the other 14 were diagnosed after surgery. Two patients developed significant postoperative complications (pancreaticojejunostomy leak <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> intraabdominal abscess <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>) and 3 developed ATT induced hepatotoxicity. No patient died. The median follow up period was 12 months (9 – 96 months).</p> <p>Conclusion</p> <p>Tuberculosis should be considered as a differential diagnosis, particularly in young patients, with atypical signs and symptoms coming from areas where tuberculosis is endemic and preoperative tissue and/or cytological diagnosis should be attempted before labeling them as hepatobiliary and pancreatic malignancy.</p

Incorporation of albumin fusion proteins into fibrin clots in vitro and in vivo: comparison of different fusion motifs recognized by factor XIIIa

<p>Abstract</p> <p>Background</p> <p>The transglutaminase activated factor XIII (FXIIIa) acts to strengthen pathological fibrin clots and to slow their dissolution, in part by crosslinking active α₂-antiplasmin (α₂AP) to fibrin. We previously reported that a yeast-derived recombinant fusion protein comprising α₂AP residues 13-42 linked to human serum albumin (HSA) weakened <it>in vitro </it>clots but failed to become specifically incorporated into <it>in vivo </it>clots. In this study, our aims were to improve both the stability and clot localization of the HSA fusion protein by replacing α₂AP residues 13-42 with shorter sequences recognized more effectively by FXIIIa.</p> <p>Results</p> <p>Expression plasmids were prepared encoding recombinant HSA with the following N-terminal 23 residue extensions: H₆NQEQVSPLTLLAG₄Y (designated XL1); H₆DQMMLPWAVTLG₄Y (XL2); H₆WQHKIDLPYNGAG₄Y (XL3); and their 17 residue non-His-tagged equivalents (XL4, XL5, and XL6). The HSA moiety of XL4- to XL6-HSA proteins was C-terminally His-tagged. All chimerae were efficiently secreted from transformed <it>Pichia pastoris </it>yeast except XL3-HSA, and following nickel chelate affinity purification were found to be intact by amino acid sequencing, as was an N-terminally His-tagged version of α₂AP(13-42)-HSA. Of the proteins tested, XL5-HSA was cross-linked to biotin pentylamine (BPA) most rapidly by FXIIIa, and was the most effective competitor of α₂AP crosslinking not only to BPA but also to plasma fibrin clots. In the mouse ferric chloride <it>vena cava </it>thrombosis model, radiolabeled XL5-HSA was retained in the clot to a greater extent than recombinant HSA. In the rabbit jugular vein stasis thrombosis model, XL5-HSA was also retained in the clot, in a urea-insensitive manner indicative of crosslinking to fibrin, to a greater extent than recombinant HSA.</p> <p>Conclusions</p> <p>Fusion protein XL5-HSA (DQMMLPWAVTLG₄Y-HSAH₆) was found to be more active as a substrate for FXIIIa-mediated transamidation than seven other candidate fusion proteins <it>in vitro</it>. The improved stability and reactivity of this chimeric protein was further evidenced by its incorporation into <it>in vivo </it>clots formed in thrombosis models in both mice and rabbits.</p

Classifying the evolutionary and ecological features of neoplasms

The consensus conference was supported by Wellcome Genome Campus Advanced Courses and Scientific Conferences. C.C.M. is supported in part by US NIH grants P01 CA91955, R01 CA149566, R01 CA170595, R01 CA185138 and R01 CA140657 as well as CDMRP Breast Cancer Research Program Award BC132057. M.J. is supported by NIH grant K99CA201606. K.S.A. is supported by NCI 5R21 CA196460. K. Polyak is supported by R35 CA197623, U01 CA195469, U54 CA193461, and the Breast Cancer Research Foundation. K.J.P. is supported by NIH grants CA143803, CA163124, CA093900 and CA143055. D.P. is supported by the European Research Council (ERC-617457- PHYLOCANCER), the Spanish Ministry of Economy and Competitiveness (BFU2015-63774-P) and the Education, Culture and University Development Department of the Galician Government. K.S.A. is supported in part by the Breast Cancer Research Foundation and NCI R21CA196460. C.S. is supported by the Royal Society, Cancer Research UK (FC001169), the UK Medical Research Council (FC001169), and the Wellcome Trust (FC001169), NovoNordisk Foundation (ID 16584), the Breast Cancer Research Foundation (BCRF), the European Research Council (THESEUS) and Marie Curie Network PloidyNet. T.A.G. is a Cancer Research UK fellow and a Wellcome Trust funded Investigator. E.S.H. is supported by R01 CA185138-01 and W81XWH-14-1-0473. M.Gerlinger is supported by Cancer Research UK and The Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre. M.Ge., M.Gr., Y.Y., and A.So. were also supported in part by the Wellcome Trust [105104/Z/14/Z]. J.D.S. holds the Edward B. Clark, MD Chair in Pediatric Research, and is supported by the Primary Children's Hospital (PCH) Pediatric Cancer Research Program, funded by the Intermountain Healthcare Foundation and the PCH Foundation. A.S. is supported by the Chris Rokos Fellowship in Evolution and Cancer. Y.Y. is a Cancer Research UK fellow and supported by The Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre. E.S.H. was supported in part by PCORI grants 1505–30497 and 1503–29572, NIH grants R01 CA185138, T32 CA093245, and U10 CA180857, CDMRP Breast Cancer Research Program Award BC132057, a CRUK Grand Challenge grant, and the Breast Cancer Research Foundation. A.R.A.A. was funded in part by NIH grant U01CA151924. A.R.A.A., R.G. and J.S.B. were funded in part by NIH grant U54CA193489

Changes in blood coagulability as it traverses the ischemic limb.

OBJECTIVE: We undertook this study to determine whether changes in blood coagulability associated with peripheral arterial occlusive disease are due to contact with the atherosclerotic arterial wall or passage through distal ischemic tissue. METHODS: Thirty patients with peripheral arterial occlusive disease undergoing angiography participated in the study. Ankle-brachial pressure index was recorded before intervention. Blood samples taken from the aorta, common femoral artery, and common femoral vein were analyzed at thromboelastography. Angiograms were scored for stenotic disease by a radiologist blinded to the other results. RESULTS: When femoral artery samples were compared with aortic samples there was a decrease in reaction time (R; P &lt;.05), an increase in maximum amplitude (MA; P &lt;.05), and an increase in coagulation index (CI; P &lt;.002), indicating an increase in coagulability as blood flowed down the iliac segment. These changes also correlated (DeltaR, r = 0.442, P &lt;.05; DeltaMA, r = 0.379, P &lt;.05; DeltaCI, r = 0.429, P &lt;.05) with the severity of disease in the ipsilateral iliac segment. Significant differences in R (P &lt;.05), angle (P &lt;.05), MA (P &lt;.005), and CI (P &lt;.001) between common femoral arterial and venous samples confirmed that venous samples were more coagulable in this group of patients. This difference in Thromboelastography parameters across the arteriovenous segment correlated inversely with the degree of ischemia (represented by ankle-brachial pressure index; DeltaCI, r = -0.427, P &lt;.05; DeltaMA, r = -0.370, P &lt;.05) in the puncture side limb. CONCLUSION: Passage of blood down an atherosclerotic artery leads to an increase in coagulability proportional to the degree of stenosis in that vessel. Passage of blood through ischemic tissue may also contribute to increased coagulability in peripheral arterial occlusive disease