Integrating sequence and structural biology with DAS.

BACKGROUND: The Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence. RESULTS: Here we present several extensions to the current DAS 1.5 protocol. These provide new commands to share alignments, three dimensional molecular structure data, add the possibility for registration and discovery of DAS servers, and provide a convention how to provide different types of data plots. We present examples of web sites and applications that use the new extensions. We operate a public registry of DAS sources, which now includes entries for more than 250 distinct sources. CONCLUSION: Our DAS extensions are essential for the management of the growing number of services and exchange of diverse biological data sets. In addition the extensions allow new types of applications to be developed and scientific questions to be addressed. The registry of DAS sources is available at http://www.dasregistry.org.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A novel method to compare protein structures using local descriptors

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is one of the most widely performed tasks in bioinformatics. However, currently used methods have problems with the so-called "difficult similarities", including considerable shifts and distortions of structure, sequential swaps and circular permutations. There is a demand for efficient and automated systems capable of overcoming these difficulties, which may lead to the discovery of previously unknown structural relationships.</p> <p>Results</p> <p>We present a novel method for protein structure comparison based on the formalism of local descriptors of protein structure - DEscriptor Defined Alignment (DEDAL). Local similarities identified by pairs of similar descriptors are extended into global structural alignments. We demonstrate the method's capability by aligning structures in difficult benchmark sets: curated alignments in the SISYPHUS database, as well as SISY and RIPC sets, including non-sequential and non-rigid-body alignments. On the most difficult RIPC set of sequence alignment pairs the method achieves an accuracy of 77% (the second best method tested achieves 60% accuracy).</p> <p>Conclusions</p> <p>DEDAL is fast enough to be used in whole proteome applications, and by lowering the threshold of detectable structure similarity it may shed additional light on molecular evolution processes. It is well suited to improving automatic classification of structure domains, helping analyze protein fold space, or to improving protein classification schemes. DEDAL is available online at <url>http://bioexploratorium.pl/EP/DEDAL</url>.</p

SISYPHUS—structural alignments for proteins with non-trivial relationships

With the increasing amount of structural data, the number of homologous protein structures bearing topological irregularities is steadily growing. These include proteins with circular permutations, segment-swapping, context-dependent folding or chameleon sequences that can adopt alternative secondary structures. Their non-trivial structural relationships are readily identified during expert analysis but their automatic identification using the existing computational tools still remains difficult or impossible. Such non-trivial cases of protein relationships are known to pose a problem to multiple alignment algorithms and to impede comparative modeling studies. They support a new emerging concept of evolutionary changeable protein fold, which creates practical difficulties for the hierarchical classifications of protein structures.To facilitate the understanding of, and to provide a comprehensive annotation of proteins with such non-trivial structural relationships we have created SISYPHUS ([Σισυϕος]—in Greek crafty), a compendium to the SCOP database. The SISYPHUS database contains a collection of manually curated structural alignments and their inter-relationships. The multiple alignments are constructed for protein structural regions that range from oligomeric biological units, or individual domains to fragments of different size. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations. The database is available from

The Interplay between Chemistry and Mechanics in the Transduction of a Mechanical Signal into a Biochemical Function

There are many processes in biology in which mechanical forces are generated. Force-bearing networks can transduce locally developed mechanical signals very extensively over different parts of the cell or tissues. In this article we conduct an overview of this kind of mechanical transduction, focusing in particular on the multiple layers of complexity displayed by the mechanisms that control and trigger the conversion of a mechanical signal into a biochemical function. Single molecule methodologies, through their capability to introduce the force in studies of biological processes in which mechanical stresses are developed, are unveiling subtle intertwining mechanisms between chemistry and mechanics and in particular are revealing how chemistry can control mechanics. The possibility that chemistry interplays with mechanics should be always considered in biochemical studies.Comment: 50 pages, 18 figure

The impact of AlphaFold2 one year on

The greatly improved prediction of protein 3D structure from sequence achieved by the second version of AlphaFold in 2020 has already had a huge impact on biological research, but challenges remain; the protein folding problem cannot be considered solved. We expect fierce competition to improve the method even further and new applications of machine learning to help illuminate proteomes and their many interactions

Circular Permutation in Proteins

This is a ‘‘Topic Page’ ’ article for PLoS Computational Biology. Circular permutation describes a type of relationship between proteins, whereby the proteins have a changed order of amino acids in their protein sequence, such that the sequence of the first portion of one protein (adjacent to the N-terminus) is related to that of the second portion of the other protein (near its C-terminus), and vice versa (see Figure 1). This is directly analogous to the mathematical notion of a cyclic permutation over the set of residues in a protein. Circular permutation can be the result of evolutionary events, post-translational modifications, or artificially engineered mutations. The result is a protein structure with different connectivity, but overall similar three-dimensional (3D) shape. The homology between portions of the proteins can be established by observing similar sequences between N- and C-terminal portions of the tw

The Significance of the ProtDeform Score for Structure Prediction and Alignment

Background: When a researcher uses a program to align two proteins and gets a score, one of her main concerns is how often the program gives a similar score to pairs that are or are not in the same fold. This issue was analysed in detail recently for the program TM-align with its associated TM-score. It was shown that because the TM-score is length independent, it allows a P-value and a hit probability to be defined depending only on the score. Also, it was found that the TM-scores of gapless alignments closely follow an Extreme Value Distribution (EVD). The program ProtDeform for structural protein alignment was developed recently and is characterised by the ability to propose different transformations of different protein regions. Our goal is to analyse its associated score to allow a researcher to have objective reasons to prefer one aligner over another, and carry out a better interpretation of the output. Results: The study on the ProtDeform score reveals that it is length independent in a wider score range than TM-scores and that PD-scores of gapless (random) alignments also approximately follow an EVD. On the CASP8 predictions, PD-scores and TM-scores, with respect to native structures, are highly correlated (0.95), and show that around a fifth of the predictions have a quality as low as 99.5 % of the random scores. Using the Gold Standard benchmark, ProtDeform has lower probabilities of error than TM-align both at a similar speed. The analysis is extended to homology discrimination showing that, again, ProtDeform offers higher hit probabilities than TM-align. Finally, we suggest using three different P-value

CSA: Comprehensive comparison of pairwise protein structure alignments

htmlabstractCSA is a web server for the computation, evaluation and comprehensive comparison of pairwise protein structure alignments. Its exact alignment engine computes either optimal, top-scoring alignments or heuristic alignments with quality guarantee for the inter-residue distance-based scorings of contact map overlap, PAUL, DALI and MATRAS. These and additional, uploaded alignments are compared using a number of quality measures and intuitive visualizations. CSA brings new insight into the structural relationship of the protein pairs under investigation and is a valuable tool for studying structural similarities. It is available at http://csa.project.cwi.nl