TESE: generating specific protein structure test set ensembles

Abstract Summary: TESE is a web server for the generation of test sets of protein sequences and structures fulfilling a number of different criteria. At least three different use cases can be envisaged: (i) benchmarking of novel methods; (ii) test sets tailored for special needs and (iii) extending available datasets. The CATH structure classification is used to control structural/sequence redundancy and a variety of structural quality parameters can be used to interactively select protein subsets with specific characteristics, e.g. all X-ray structures of α-helical repeat proteins with more than 120 residues and resolution <2.0 Å. The output includes FASTA-formatted sequences, PDB files and a clickable HTML index file containing images of the selected proteins. Multiple subsets for cross-validation are also supported. Availability: The TESE server is available for non-commercial use at URL: http://protein.bio.unipd.it/tese/. Contact: [email protected]

The pVHL neglected functions, a tale of hypoxia-dependent and -independent regulations in cancer

The von Hippel-Lindau protein (pVHL) is a tumour suppressor mainly known for its role as master regulator of hypoxia-inducible factor (HIF) activity. Functional inactivation of pVHL is causative of the von Hippel-Lindau disease, an inherited predisposition to develop different cancers. Due to its impact on human health, pVHL has been widely studied in the last few decades. However, investigations mostly focus on its role in degrading HIFs, whereas alternative pVHL protein-protein interactions and functions are insistently surfacing in the literature. In this review, we analyse these almost neglected functions by dissecting specific conditions in which pVHL is proposed to have differential roles in promoting cancer. We reviewed its role in regulating phosphorylation as a number of works suggest pVHL to act as an inhibitor by either degrading or promoting downregulation of specific kinases. Further, we summarize hypoxia-dependent and -independent pVHL interactions with multiple protein partners and discuss their implications in tumorigenesis

Genotype-phenotype relations of the von Hippel-Lindau tumor suppressor inferred from a large-scale analysis of disease mutations and interactors

Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease

Dynamic scaffolds for neuronal signaling: in silico analysis of the TANC protein family.

Fiesta de Tosantos (1101001

Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines

Intrinsically disordered proteins have long stretches of their polypeptide chain, which do not adopt a single native structure composed of stable secondary and tertiary structure in the absence of binding partners. The prediction of intrinsically disordered regions in proteins from sequence is increasingly becoming of interest, as the presence of many such regions in the complete genome sequences are discovered and important functional roles are associated with them. We have developed a machine learning approach based on two support vector machines (SVM) to discriminate disordered regions from sequence. The SVM are trained and benchmarked on two sets, representing long and short disordered regions. A preliminary version of Spritz was shown to perform consistently well at the recent biannual CASP-6 experiment [Critical Assessment of Techniques for Protein Structure Prediction (CASP), 2004]. The fully developed Spritz method is freely available as a web server at and

MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins

Abstract Motivation The earlier version of MobiDB-lite is currently used in large-scale proteome annotation platforms to detect intrinsic disorder. However, new theoretical models allow for the classification of intrinsically disordered regions into subtypes from sequence features associated with specific polymeric properties or compositional bias. Results MobiDB-lite 3.0 maintains its previous speed and performance but also provides a finer classification of disorder by identifying regions with characteristics of polyolyampholytes, positive or negative polyelectrolytes, low-complexity regions or enriched in cysteine, proline or glycine or polar residues. Subregions are abundantly detected in IDRs of the human proteome. The new version of MobiDB-lite represents a new step for the proteome level analysis of protein disorder. Availability and implementation Both the MobiDB-lite 3.0 source code and a docker container are available from the GitHub repository: https://github.com/BioComputingUP/MobiDB-lit

Calmodulin enhances cryptochrome binding to INAD in Drosophila photoreceptors

Light is the main environmental stimulus that synchronizes the endogenous timekeeping systems in most terrestrial organisms. Drosophila cryptochrome (dCRY) is a light-responsive flavoprotein that detects changes in light intensity and wavelength around dawn and dusk. We have previously shown that dCRY acts through Inactivation No Afterpotential D (INAD) in a light-dependent manner on the Signalplex, a multiprotein complex that includes visual-signaling molecules, suggesting a role for dCRY in fly vision. Here, we predict and demonstrate a novel Ca2+-dependent interaction between dCRY and calmodulin (CaM). Through yeast two hybrid, coimmunoprecipitation (Co-IP), nuclear magnetic resonance (NMR) and calorimetric analyses we were able to identify and characterize a CaM binding motif in the dCRY C-terminus. Similarly, we also detailed the CaM binding site of the scaffold protein INAD and demonstrated that CaM bridges dCRY and INAD to form a ternary complex in vivo. Our results suggest a process whereby a rapid dCRY light response stimulates an interaction with INAD, which can be further consolidated by a novel mechanism regulated by CaM

Bluues server

Abstract Motivation: Electrostatic calculations are an important tool for deciphering many functional mechanisms in proteins. Generalized Born (GB) models offer a fast and convenient computational approximation over other implicit solvent-based electrostatic models. Here we present a novel GB-based web server, using the program Bluues, to calculate numerous electrostatic features including pKa-values and surface potentials. The output is organized allowing both experts and beginners to rapidly sift the data. A novel feature of the Bluues server is that it explicitly allows to find electrostatic differences between wild-type and mutant structures. Availability: The Bluues server, examples and extensive help files are available for non-commercial use at URL: http://protein.bio.unipd.it/bluues/. Contact: [email protected]

RAPHAEL: recognition, periodicity and insertion assignment of solenoid protein structures.

Abstract Motivation: Repeat proteins form a distinct class of structures where folding is greatly simplified. Several classes have been defined, with solenoid repeats of periodicity between ca. 5 and 40 being the most challenging to detect. Such proteins evolve quickly and their periodicity may be rapidly hidden at sequence level. From a structural point of view, finding solenoids may be complicated by the presence of insertions or multiple domains. To the best of our knowledge, no automated methods are available to characterize solenoid repeats from structure. Results: Here we introduce RAPHAEL, a novel method for the detection of solenoids in protein structures. It reliably solves three problems of increasing difficulty: (1) recognition of solenoid domains, (2) determination of their periodicity and (3) assignment of insertions. RAPHAEL uses a geometric approach mimicking manual classification, producing several numeric parameters that are optimized for maximum performance. The resulting method is very accurate, with 89.5% of solenoid proteins and 97.2% of non-solenoid proteins correctly classified. RAPHAEL periodicities have a Spearman correlation coefficient of 0.877 against the manually established ones. A baseline algorithm for insertion detection in identified solenoids has a Q2 value of 79.8%, suggesting room for further improvement. RAPHAEL finds 1931 highly confident repeat structures not previously annotated as solenoids in the Protein Data Bank records. Availability: The RAPHAEL web server is available with additional data at http://protein.bio.unipd.it/raphael/ Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin