PCRPi-DB:a database of computationally annotated hot spots in protein interfaces

Protein–protein interactions are central to almost any cellular process. Although typically protein interfaces are large, it is well established that only a relatively small region, the so-called ‘hot spot’, contributes the most to the total binding energy. There is a clear interest in identifying hot spots because of its application in drug discovery and protein design. Presaging Critical Residues in Protein Interfaces Database (PCRPi-DB) is a public repository that archives computationally annotated hot spots in protein complexes for which the 3D structure is known. Hot spots have been annotated using a new and highly accurate computational method developed in the lab. PCRPi-DB is freely available to the scientific community at http://www.bioinsilico.org/PCRPIDB. Besides browsing and querying the contents of the database, extensive documentation and links to relevant on-line resources and contents are available to users. PCRPi-DB is updated on a weekly basis

A holistic in silico approach to predict functional sites in protein structures

Abstract Motivation: Proteins execute and coordinate cellular functions by interacting with other biomolecules. Among these interactions, protein–protein (including peptide-mediated), protein–DNA and protein–RNA interactions cover a wide range of critical processes and cellular functions. The functional characterization of proteins requires the description and mapping of functional biomolecular interactions and the identification and characterization of functional sites is an important step towards this end. Results: We have developed a novel computational method, Multi-VORFFIP (MV), a tool to predicts protein-, peptide-, DNA- and RNA-binding sites in proteins. MV utilizes a wide range of structural, evolutionary, experimental and energy-based information that is integrated into a common probabilistic framework by means of a Random Forest ensemble classifier. While remaining competitive when compared with current methods, MV is a centralized resource for the prediction of functional sites and is interfaced by a powerful web application tailored to facilitate the use of the method and analysis of predictions to non-expert end-users. Availability:  http://www.bioinsilico.org/MVORFFIP Supplementary information:  Supplementary data are available at Bioinformatics online. Contact:  [email protected]; [email protected]</jats:p

Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams

BACKGROUND: Protein binding site prediction by computational means can yield valuable information that complements and guides experimental approaches to determine the structure of protein complexes. Predictions become even more relevant and timely given the current resolution of protein interaction maps, where there is a very large and still expanding gap between the available information on: (i) which proteins interact and (ii) how proteins interact. Proteins interact through exposed residues that present differential physicochemical properties, and these can be exploited to identify protein interfaces. RESULTS: Here we present VORFFIP, a novel method for protein binding site prediction. The method makes use of broad set of heterogeneous data and defined of residue environment, by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensemble classifier. Four sets of residue features (structural, energy terms, sequence conservation, and crystallographic B-factors) used in different combinations together with three definitions of residue environment (Voronoi Diagrams, sequence sliding window, and Euclidian distance) have been analyzed in order to maximize the performance of the method. CONCLUSIONS: The integration of different forms information such as structural features, energy term, evolutionary conservation and crystallographic B-factors, improves the performance of binding site prediction. Including the information of neighbouring residues also improves the prediction of protein interfaces. Among the different approaches that can be used to define the environment of exposed residues, Voronoi Diagrams provide the most accurate description. Finally, VORFFIP compares favourably to other methods reported in the recent literature

Presaging critical residues in protein interfaces-web server (PCRPi-W):a web server to chart hot spots in protein interfaces

BACKGROUND: It is well established that only a portion of residues that mediate protein-protein interactions (PPIs), the so-called hot spot, contributes the most to the total binding energy, and thus its identification is an important and relevant question that has clear applications in drug discovery and protein design. The experimental identification of hot spots is however a lengthy and costly process, and thus there is an interest in computational tools that can complement and guide experimental efforts. PRINCIPAL FINDINGS: Here, we present Presaging Critical Residues in Protein interfaces-Web server (http://www.bioinsilico.org/PCRPi), a web server that implements a recently described and highly accurate computational tool designed to predict critical residues in protein interfaces: PCRPi. PRCPi depends on the integration of structural, energetic, and evolutionary-based measures by using Bayesian Networks (BNs). CONCLUSIONS: PCRPi-W has been designed to provide an easy and convenient access to the broad scientific community. Predictions are readily available for download or presented in a web page that includes among other information links to relevant files, sequence information, and a Jmol applet to visualize and analyze the predictions in the context of the protein structure

A Newtonian model for the WASP-148 exoplanetary system enhanced with TESS and ground-based photometric observations

The WASP-148 planetary system has a rare architecture with a transiting Saturn-mass planet on a tight orbit which is accompanied by a slightly more massive planet on a nearby outer orbit. Using new space-born photometry and ground-based follow-up transit observations and data available in literature, we performed modeling that accounts for gravitational interactions between both planets. Thanks to the new transit timing data for planet b, uncertainties of orbital periods and eccentricities for both planets were reduced relative to previously published values by a factor of 3-4. Variation in transit timing has an amplitude of about 20 minutes and can be easily followed-up with a 1-m class telescopes from the ground. An approximated transit ephemeris, which accounts for gravitational interactions with an accuracy up to 5 minutes, is provided. No signature of transits was found for planet c down to the Neptune-size regime. No other transiting companions were found down to a size of about 2.4 Earth radii for interior orbits. We notice, however, that the regime of terrestrial-size planets still remains unexplored in that system.Comment: Accepted for publication in Acta Astronomic

1.3 mm Polarized emission in the circumstellar disk of a massive protostar

We present the first resolved observations of the 1.3 mm polarized emission from the disk-like structure surrounding the high-mass protostar Cepheus A HW2. These CARMA data partially resolve the dust polarization, suggesting a uniform morphology of polarization vectors with an average position angle of 57° ± 6° and an average polarization fraction of 2.0% ± 0.4%. The distribution of the polarization vectors can be attributed to (1) the direct emission of magnetically aligned grains of dust by a uniform magnetic field, or (2) the pattern produced by the scattering of an inclined disk. We show that both models can explain the observations, and perhaps a combination of the two mechanisms produces the polarized emission. A third model including a toroidal magnetic field does not match the observations. Assuming scattering is the polarization mechanism, these observations suggest that during the first few 104 years of high-mass star formation, grain sizes can grow from1 mm to several 10s μm.Fil: Fernandez Lopez, Manuel. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomia; ArgentinaFil: Stephens, I. W.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos. Boston University; Estados Unidos. University of Illinois; Estados UnidosFil: Girart, J. M.. Harvard-Smithsonian Center for Astrophysics; Estados Unidos. Institut de Ciències de l’Espai; EspañaFil: Looney, L.. University of Illinois; Estados UnidosFil: Curiel, S.. Universidad Nacional Autónoma de México; MéxicoFil: Segura Cox, D.. University of Illinois; Estados UnidosFil: Eswaraiah, C.. National Tsing Hua University; República de ChinaFil: Lai, S. P.. National Tsing Hua University; República de Chin

Environmental Processing in Meiothermus ruber: the Inorganic Phosphate ABC Transporter

Bioinformatics analysis of M. rube