Computational modelling of protein/protein and protein/DNA docking.

The docking problem is to start with unbound conformations for the components of a complex, and computationally model a near-native structure for the complex. This thesis describes work in developing computer programs to tackle both protein/protein and protein/DNA docking. Empirical pair potential functions are generated from datasets of residue/residue interactions. A scoring function was parameterised and then used to screen possible complexes, generated by the global search computer algorithm FTDOCK using shape complementarity and electrostatics, for 9 systems. A correct docking (RMSD < 2.5A) is placed within the top 12% of the pair potential score ranked complexes for all systems. The computer software FTDOCK is modified for the docking of proteins to DNA, starting from the unbound protein and DNA coordinates modelled computationally. Complexes are then ranked by protein/DNA pair potentials derived from a database of 20 protein/DNA complexes. A correct docking (at least 65% of correct contacts) was identified at rank < 4 for 3 of the 8 complexes. This improved to 4 out of 8 when the complexes were filtered using experimental data defining the DNA footprint. The FTDOCK program was rewritten, and improved pair potential functions were developed from a set of non-homologous protein/protein interfaces. The algorithms were tested on a non-homologous set of 18 protein/protein complexes, starting with unbound conformations. Us ing cross-validated pair potential functions and the energy rninimisation software MultiDock, a correct docking ( RMSD of CQ interface 25% correct contacts) is found in the top 10 ranks in 6 out of 18 systems. The current best computational docking algorithms are discussed, and strategies for improvement are suggested

Combination of scoring schemes for protein docking

<p>Abstract</p> <p>Background</p> <p>Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function.</p> <p>Results</p> <p>The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures.</p> <p>Conclusion</p> <p>We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.</p

Protein binding hot spots and the residue-residue pairing preference: a water exclusion perspective

<p>Abstract</p> <p>Background</p> <p>A protein binding hot spot is a small cluster of residues tightly packed at the center of the interface between two interacting proteins. Though a hot spot constitutes a small fraction of the interface, it is vital to the stability of protein complexes. Recently, there are a series of hypotheses proposed to characterize binding hot spots, including the pioneering O-ring theory, the insightful 'coupling' and 'hot region' principle, and our 'double water exclusion' (DWE) hypothesis. As the perspective changes from the O-ring theory to the DWE hypothesis, we examine the physicochemical properties of the binding hot spots under the new hypothesis and compare with those under the O-ring theory.</p> <p>Results</p> <p>The requirements for a cluster of residues to form a hot spot under the DWE hypothesis can be mathematically satisfied by a biclique subgraph if a vertex is used to represent a residue, an edge to indicate a close distance between two residues, and a bipartite graph to represent a pair of interacting proteins. We term these hot spots as DWE bicliques. We identified DWE bicliques from crystal packing contacts, obligate and non-obligate interactions. Our comparative study revealed that there are abundant <it>unique </it>bicliques to the biological interactions, indicating specific biological binding behaviors in contrast to crystal packing. The two sub-types of biological interactions also have their own signature bicliques. In our analysis on residue compositions and residue pairing preferences in DWE bicliques, the focus was on interaction-preferred residues (ipRs) and interaction-preferred residue pairs (ipRPs). It is observed that hydrophobic residues are heavily involved in the ipRs and ipRPs of the obligate interactions; and that aromatic residues are in favor in the ipRs and ipRPs of the biological interactions, especially in those of the non-obligate interactions. In contrast, the ipRs and ipRPs in crystal packing are dominated by hydrophilic residues, and most of the anti-ipRs of crystal packing are the ipRs of the obligate or non-obligate interactions.</p> <p>Conclusions</p> <p>These ipRs and ipRPs in our DWE bicliques describe a diverse binding features among the three types of interactions. They also highlight the specific binding behaviors of the biological interactions, sharply differing from the artifact interfaces in the crystal packing. It can be noted that DWE bicliques, especially the unique bicliques, can capture deep insights into the binding characteristics of protein interfaces.</p

Initial data release from the INT Photometric H alpha Survey of the Northern Galactic Plane (IPHAS)

The INT/WFC Photometric Hα Survey of the Northern Galactic Plane (IPHAS) is an imaging survey being carried out in Hα, r′ and i′ filters, with the Wide Field Camera (WFC) on the 2.5-m Isaac Newton Telescope (INT) to a depth of r′= 20 (10σ). The survey is aimed at revealing the large scale organization of the Milky Way and can be applied to identifying a range of stellar populations within it. Mapping emission line objects enables a particular focus on objects in the young and old stages of stellar evolution ranging from early T-Tauri stars to late planetary nebulae. In this paper we present the IPHAS Initial Data Release, primarily a photometric catalogue of about 200 million unique objects, coupled with associated image data covering about 1600 deg2 in three passbands. We note how access to the primary data products has been implemented through use of standard virtual observatory publishing interfaces. Simple traditional web access is provided to the main IPHAS photometric catalogue, in addition to a number of common catalogues (such as 2MASS) which are of immediate relevance. Access through the AstroGrid VO Desktop opens up the full range of analysis options, and allows full integration with the wider range of data and services available through the Virtual Observatory. The IDR represents the largest data set published primarily through VO interfaces to date, and so stands as an exemplar of the future of survey data mining. Examples of data access are given, including a cross-matching of IPHAS photometry with sources in the UKIDSS Galactic Plane Survey that validates the existing calibration of the best data

Four Distances between Pairs of Amino Acids Provide a Precise Description of their Interaction

The three-dimensional structures of proteins are stabilized by the interactions between amino acid residues. Here we report a method where four distances are calculated between any two side chains to provide an exact spatial definition of their bonds. The data were binned into a four-dimensional grid and compared to a random model, from which the preference for specific four-distances was calculated. A clear relation between the quality of the experimental data and the tightness of the distance distribution was observed, with crystal structure data providing far tighter distance distributions than NMR data. Since the four-distance data have higher information content than classical bond descriptions, we were able to identify many unique inter-residue features not found previously in proteins. For example, we found that the side chains of Arg, Glu, Val and Leu are not symmetrical in respect to the interactions of their head groups. The described method may be developed into a function, which computationally models accurately protein structures

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors

Intraoperative assessment of biliary anatomy for prevention of bile duct injury: a review of current and future patient safety interventions

Background Bile duct injury (BDI) is a dreaded complication of cholecystectomy, often caused by misinterpretation of biliary anatomy. To prevent BDI, techniques have been developed for intraoperative assessment of bile duct anatomy. This article reviews the evidence for the different techniques and discusses their strengths and weaknesses in terms of efficacy, ease, and cost-effectiveness. Method PubMed was searched from January 1980 through December 2009 for articles concerning bile duct visualization techniques for prevention of BDI during laparoscopic cholecystectomy. Results Nine techniques were identified. The critical-view-of-safety approach, indirectly establishing biliary anatomy, is accepted by most guidelines and commentaries as the surgical technique of choice to minimize BDI risk. Intraoperative cholangiography is associated with lower BDI risk (OR 0.67, CI 0.61-0.75). However, it incurs extra costs, prolongs the operative procedure, and may be experienced as cumbersome. An established reliable alternative is laparoscopic ultrasound, but its longer learning curve limits widespread implementation. Easier to perform are cholecystocholangiography and dye cholangiography, but these yield poor-quality images. Light cholangiography, requiring retrograde insertion of an optical fiber into the common bile duct, is too unwieldy for routine use. Experimental techniques are passive infrared cholangiography, hyperspectral cholangiography, and near-infrared fluorescence cholangiography. The latter two are performed noninvasively and provide real-time images. Quantitative data in patients are necessary to further evaluate these techniques. Conclusions The critical-view-of-safety approach should be used during laparoscopic cholecystectomy. Intraoperative cholangiography or laparoscopic ultrasound is recommended to be performed routinely. Hyperspectral cholangiography and near-infrared fluorescence cholangiography are promising novel techniques to prevent BDI and thus increase patient safety

An overview of treatment approaches for chronic pain management

Pain which persists after healing is expected to have taken place, or which exists in the absence of tissue damage, is termed chronic pain. By definition chronic pain cannot be treated and cured in the conventional biomedical sense; rather, the patient who is suffering from the pain must be given the tools with which their long-term pain can be managed to an acceptable level. This article will provide an overview of treatment approaches available for the management of persistent non-malignant pain. As well as attempting to provide relief from the physical aspects of pain through the judicious use of analgesics, interventions, stimulations, and irritations, it is important to pay equal attention to the psychosocial complaints which almost always accompany long-term pain. The pain clinic offers a biopsychosocial approach to treatment with the multidisciplinary pain management programme; encouraging patients to take control of their pain problem and lead a fulfilling life in spite of the pain. © 2016 Springer-Verlag Berlin Heidelber