162 research outputs found
Evolutionary Trace Annotation Server: automated enzyme function prediction in protein structures using 3D templates
Summary:The Evolutionary Trace Annotation (ETA) Server predicts enzymatic activity. ETA starts with a structure of unknown function, such as those from structural genomics, and with no prior knowledge of its mechanism uses the phylogenetic Evolutionary Trace (ET) method to extract key functional residues and propose a function-associated 3D motif, called a 3D template. ETA then searches previously annotated structures for geometric template matches that suggest molecular and thus functional mimicry. In order to maximize the predictive value of these matches, ETA next applies distinctive specificity filtersβevolutionary similarity, function plurality and match reciprocity. In large scale controls on enzymes, prediction coverage is 43% but the positive predictive value rises to 92%, thus minimizing false annotations. Users may modify any search parameter, including the template. ETA thus expands the ET suite for protein structure annotation, and can contribute to the annotation efforts of metaservers
Evolutionary action and structural basis of the allosteric switch controlling Ξ²(2)AR functional selectivity
Functional selectivity of G-protein-coupled receptors is believed to originate from ligand-specific conformations that activate only subsets of signaling effectors. In this study, to identify molecular motifs playing important roles in transducing ligand binding into distinct signaling responses, we combined in silico evolutionary lineage analysis and structure-guided site-directed mutagenesis with large-scale functional signaling characterization and non-negative matrix factorization clustering of signaling profiles. Clustering based on the signaling profiles of 28 variants of the Ξ²(2)-adrenergic receptor reveals three clearly distinct phenotypical clusters, showing selective impairments of either the Gi or Ξ²arrestin/endocytosis pathways with no effect on Gs activation. Robustness of the results is confirmed using simulation-based error propagation. The structural changes resulting from functionally biasing mutations centered around the DRY, NPxxY, and PIF motifs, selectively linking these micro-switches to unique signaling profiles. Our data identify different receptor regions that are important for the stabilization of distinct conformations underlying functional selectivity
Background frequencies for residue variability estimates: BLOSUM revisited
<p>Abstract</p> <p>Background</p> <p>Shannon entropy applied to columns of multiple sequence alignments as a score of residue conservation has proven one of the most fruitful ideas in bioinformatics. This straightforward and intuitively appealing measure clearly shows the regions of a protein under increased evolutionary pressure, highlighting their functional importance. The inability of the column entropy to differentiate between residue types, however, limits its resolution power.</p> <p>Results</p> <p>In this work we suggest generalizing Shannon's expression to a function with similar mathematical properties, that, at the same time, includes observed propensities of residue types to mutate to each other. To do that, we revisit the original construction of BLOSUM matrices, and re-interpret them as mutation probability matrices. These probabilities are then used as background frequencies in the revised residue conservation measure.</p> <p>Conclusion</p> <p>We show that joint entropy with BLOSUM-proportional probabilities as a reference distribution enables detection of protein functional sites comparable in quality to a time-costly maximum-likelihood evolution simulation method (rate4site), and offers greater resolution than the Shannon entropy alone, in particular in the cases when the available sequences are of narrow evolutionary scope.</p
Alignment of Biological Sequences with Jalview
In this chapter, we introduce core functionality of the Jalview interactive platform for the creation, analysis, and publication of multiple sequence alignments. A workflow is described based on Jalview's core functions: from data import to figure generation, including import of alignment reliability scores from T-Coffee and use of Jalview from the command line. The accompanying notes provide background information on the underlying methods and discuss additional options for working with Jalview to perform multiple sequence alignment, functional site analysis, and publication of alignments on the web
Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling
The Joint Evolutionary Trees (JET) method detects protein interfaces, the core
residues involved in the folding process, and residues susceptible to
site-directed mutagenesis and relevant to molecular recognition. The approach,
based on the Evolutionary Trace (ET) method, introduces a novel way to treat
evolutionary information. Families of homologous sequences are analyzed through
a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple
alignment and impacts of weakly homologous sequences on distance tree
construction. The sampling method makes sequence analysis more sensitive to
functional and structural importance of individual residues by avoiding effects
of the overrepresentation of highly homologous sequences and improves
computational efficiency. A carefully designed clustering method is parametrized
on the target structure to detect and extend patches on protein surfaces into
predicted interaction sites. Clustering takes into account residues'
physical-chemical properties as well as conservation. Large-scale application of
JET requires the system to be adjustable for different datasets and to guarantee
predictions even if the signal is low. Flexibility was achieved by a careful
treatment of the number of retrieved sequences, the amino acid distance between
sequences, and the selective thresholds for cluster identification. An iterative
version of JET (iJET) that guarantees finding the most likely interface residues
is proposed as the appropriate tool for large-scale predictions. Tests are
carried out on the Huang database of 62 heterodimer, homodimer, and transient
complexes and on 265 interfaces belonging to signal transduction proteins,
enzymes, inhibitors, antibodies, antigens, and others. A specific set of
proteins chosen for their special functional and structural properties
illustrate JET behavior on a large variety of interactions covering proteins,
ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf,
Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant
improvement in performance and computational efficiency is shown
Computation of protein geometry and its applications: Packing and function prediction
This chapter discusses geometric models of biomolecules and geometric
constructs, including the union of ball model, the weigthed Voronoi diagram,
the weighted Delaunay triangulation, and the alpha shapes. These geometric
constructs enable fast and analytical computaton of shapes of biomoleculres
(including features such as voids and pockets) and metric properties (such as
area and volume). The algorithms of Delaunay triangulation, computation of
voids and pockets, as well volume/area computation are also described. In
addition, applications in packing analysis of protein structures and protein
function prediction are also discussed.Comment: 32 pages, 9 figure
Π Π½Π΅ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈΡ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ Π½Π° Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΠΊΠ°Π»Π΅
Π ΡΠΎΠ±ΠΎΡi Π½Π°Π²Π΅Π΄Π΅Π½ΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈ Π°Π½Π°Π»iΠ·Ρ Π½Π΅ΡΡiΠΉΠΊΠΎΡΡi Π΄ΠΈΠ½Π°ΠΌiΡΠ½ΠΈΡ
ΡiΠ²Π½ΡΠ½Ρ Π½Π° ΡΠ°ΡΠΎΠ²iΠΉ ΡΠΊΠ°Π»i. ΠΠ°ΡΡΠΎΡΠΎΠ²Π½iΡΡΡ ΠΎΡΡΠΈΠΌΠ°Π½ΠΎΠ³ΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ iΠ»ΡΡΡΡΡΡΡΡΡΡ Π½Π° ΠΏΡΠΈΠΊΠ»Π°Π΄i ΡΠΈΡΡΠ΅ΠΌΠΈ Π΄ΡΡΠ³ΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΡ.We present new results on the instability for dynamic equations on time scales. To demonstrate the applicability, we use some examples of dynamic equations of the second order
Accurate Protein Structure Annotation through Competitive Diffusion of Enzymatic Functions over a Network of Local Evolutionary Similarities
High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks
Separation of Recombination and SOS Response in Escherichia coli RecA Suggests LexA Interaction Sites
RecA plays a key role in homologous recombination, the induction of the DNA damage response through LexA cleavage and the activity of error-prone polymerase in Escherichia coli. RecA interacts with multiple partners to achieve this pleiotropic role, but the structural location and sequence determinants involved in these multiple interactions remain mostly unknown. Here, in a first application to prokaryotes, Evolutionary Trace (ET) analysis identifies clusters of evolutionarily important surface amino acids involved in RecA functions. Some of these clusters match the known ATP binding, DNA binding, and RecA-RecA homo-dimerization sites, but others are novel. Mutation analysis at these sites disrupted either recombination or LexA cleavage. This highlights distinct functional sites specific for recombination and DNA damage response induction. Finally, our analysis reveals a composite site for LexA binding and cleavage, which is formed only on the active RecA filament. These new sites can provide new drug targets to modulate one or more RecA functions, with the potential to address the problem of evolution of antibiotic resistance at its root
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