1,721,251 research outputs found
The Victor/FRST function for model quality estimation
No full textScoring functions are widely used in the final step of model selection in protein structure prediction. This is of interest both for comparative modeling targets, where it is important to select the best model among a set of many good, "correct" ones, as well as for other (fold recognition or novel fold) targets, where the set may contain many incorrect models. A novel combination of four knowledge-based potentials recognizing different features of native protein structures is introduced and tested. The pairwise, solvation, hydrogen bond, and torsion angle potentials contain largely orthogonal information. Of these, the torsion angle potential is found to show the strongest correlation with model quality. Combining these features with a linear weighting function, it was possible to construct a robust energy function capable of discriminating native-like structures on several benchmarking sets. In a recent blind test (CAFASP-4 MQAP), the scoring function ranked consistently well and was able to reliably distinguish the correct template from an ensemble of high quality decoys in 52 of 70 cases (33 of 34 for comparative modeling). An executable version of the Victor/FRST function for Linux PCs is available for download from the URL http://protein.cribi.unipd.it/frst/
TESE: generating specific protein structure test set ensembles
No full textTESE 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 alpha-helical repeat proteins with more than 120 residues and resolution <2.0 A. 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/
Comparison of protein repeat classifications based on structure and sequence families
No full textTandem repeats (TR) in proteins are common in nature and have several unique functions. They come in various forms that are frequently difficult to recognize from a sequence. A previously proposed structural classification has been recently implemented in the RepeatsDB database. This defines five main classes, mainly based on repeat unit length, with subclasses representing specific folds. Sequence-based classifications, such as Pfam, provide an alternative classification based on evolutionarily conserved repeat families. Here, we discuss a detailed comparison between the structural classes in RepeatsDB and the corresponding Pfam repeat families and clans. Most instances are found to map one-to-one between structure and sequence. Some notable exceptions such as leucine-rich repeats (LRRs) and alpha-solenoids are discussed
Ensembles from Ordered and Disordered Proteins Reveal Similar Structural Constraints during Evolution
Full text linkThe conformations accessible to proteins are determined by the inter-residue interactions between amino acid residues. During evolution, structural constraints that are required for protein function providing biologically relevant information can exist. Here, we studied the proportion of sites evolving under structural constraints in two very different types of ensembles, those coming from ordered and disordered proteins. Using a structurally constrained model of protein evolution, we found that both types of ensembles show comparable, near 40%, number of positions evolving under structural constraints. Among these sites, ~ 68% are in disordered regions and ~ 57% of them show long-range inter-residue contacts. Also, we found that disordered ensembles are redundant in reference to their structurally constrained evolutionary information and could be described on average with ~ 11 conformers. Despite the different complexity of the studied ensembles and proteins, the similar constraints reveal a comparable level of selective pressure to maintain their biological functions. These results highlight the importance of the evolutionary information to recover meaningful biological information to further characterize conformational ensembles.Fil: Marchetti, Julia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Monzón, Alexander. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Università di Padova; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tosatto, Silvio C.E.. Università di Padova; ItaliaFil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fornasari, Maria Silvina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Large-scale prediction of protein structure and function from sequence
No full textThe identification of novel drug targets from genomic data involves the large-scale analysis of many protein sequences. Methods for automated structure and function prediction are an essential tool for this purpose. In this review we concentrate on the recent developments in the field of protein structure prediction and how these can be used to gain hints about the function of proteins. The current state-of-the-art is highlighted through recent community-wide experiments aimed at comparing different approaches. For structure prediction this allows the identification of key improvements to increase the crucial sequence to structure alignment needed for accurate models. Function prediction is a rapidly maturing field that is still being benchmarked. Definitions for protein function are presented and available methods, mostly concentrating on functional site descriptors and structural motifs, presented
Fine-grained statistical torsion angle potentials are effective in discriminating native protein structures.
No full textTAP score: torsion angle propensity normalization applied to local protein structure evaluation
Full text linkAbstract Background Experimentally determined protein structures may contain errors and require validation. Conformational criteria based on the Ramachandran plot are mainly used to distinguish between distorted and adequately refined models. While the readily available criteria are sufficient to detect totally wrong structures, establishing the more subtle differences between plausible structures remains more challenging. Results A new criterion, called TAP score, measuring local sequence to structure fitness based on torsion angle propensities normalized against the global minimum and maximum is introduced. It is shown to be more accurate than previous methods at estimating the validity of a protein model in terms of commonly used experimental quality parameters on two test sets representing the full PDB database and a subset of obsolete PDB structures. Highly selective TAP thresholds are derived to recognize over 90% of the top experimental structures in the absence of experimental information. Both a web server and an executable version of the TAP score are available at http://protein.cribi.unipd.it/tap/. Conclusion A novel procedure for energy normalization (TAP) has significantly improved the possibility to recognize the best experimental structures. It will allow the user to more reliably isolate problematic structures in the context of automated experimental structure determination.</p
Disorder transitions and conformational diversity cooperatively modulate biological function in proteins
Full text linkStructural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered-disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins become more ordered after ligand binding, while 40% more disordered. As protein conformational diversity is inherently connected with protein function our analysis suggests differences in structure-function relationships related to order-disorder transitions.Fil: Zea, Diego Javier. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Monzón, Alexander. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gonzalez, Claudia. Universidad Nacional de Quilmes; ArgentinaFil: Fornasari, Maria Silvina. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tosatto, Silvio C. E.. Università di Padova; ItaliaFil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Diversity and structural‐functional insights of alpha‐solenoid proteins
Full text linkAlpha-solenoids are a significant and diverse subset of structured tandem repeat proteins (STRPs) that are important in various domains of life. This review examines their structural and functional diversity and highlights their role in critical cellular processes such as signaling, apoptosis, and transcriptional regulation. Alpha-solenoids can be classified into three geometric folds: low curvature, high curvature, and corkscrew, as well as eight subfolds: ankyrin repeats; Huntingtin, elongation factor 3, protein phosphatase 2A, and target of rapamycin; armadillo repeats; tetratricopeptide repeats; pentatricopeptide repeats; Pumilio repeats; transcription activator-like; and Sel-1 and Sel-1-like repeats. These subfolds represent distinct protein families with unique structural properties and functions, highlighting the versatility of alpha-solenoids. The review also discusses their association with disease, highlighting their potential as therapeutic targets and their role in protein design. Advances in state-of-the-art structure prediction methods provide new opportunities and challenges in the functional characterization and classification of this kind of fold, emphasizing the need for continued development of methods for their identification and proper data curation and deposition in the main databases.Fil: Arrías, Paula Nazarena. Università di Padova; ItaliaFil: Osmanli, Zarifa. Università di Padova; ItaliaFil: Peralta, Estefanía. Universidad Nacional de La Plata. Facultad de Ciencas Exactas. Laboratorio de Investigación y Desarrollo de Bioactivos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Chinestrad, Patricio Manuel. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaFil: Tosatto, Silvio C. E.. Università di Padova; Itali
Structural in silico dissection of the collagen v interactome to identify genotype-phenotype correlations in classic Ehlers-Danlos Syndrome (EDS)
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