Protein secondary structure is the three dimensional form of local segments of proteins. The two most common secondary structural elements are alpha helices and beta sheets, though beta turns and omega loops occur as well. Secondary structure elements typically spontaneously form as an intermediate before the protein folds into its three dimensional tertiary structure.
Critical Assessment of protein Structure Prediction, or CASP, is a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994. CASP provides research groups with an opportunity to objectively test their structure prediction methods and delivers an independent assessment of the state of the art in protein structure modeling to the research community and software users. Even though the primary goal of CASP is to help advance the methods of identifying protein three-dimensional structure from its amino acid sequence, many view the experiment more as a “world championship” in this field of science. More than 100 research groups from all over the world participate in CASP on a regular basis and it is not uncommon for entire groups to suspend their other research for months while they focus on getting their servers ready for the experiment and on performing the detailed predictions.
Protein threading, also known as fold recognition, is a method of protein modeling which is used to model those proteins which have the same fold as proteins of known structures, but do not have homologous proteins with known structure. It differs from the homology modeling method of structure prediction as it is used for proteins which do not have their homologous protein structures deposited in the Protein Data Bank (PDB), whereas homology modeling is used for those proteins which do. Threading works by using statistical knowledge of the relationship between the structures deposited in the PDB and the sequence of the protein which one wishes to model.
Rosetta@home is a distributed computing project for protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the Baker laboratory at the University of Washington. Rosetta@home aims to predict protein–protein docking and design new proteins with the help of about sixty thousand active volunteered computers processing at over 210 teraFLOPS on average as of July 29, 2016. Foldit, a Rosetta@Home videogame, aims to reach these goals with a crowdsourcing approach. Though much of the project is oriented toward basic research to improve the accuracy and robustness of proteomics methods, Rosetta@home also does applied research on malaria, Alzheimer's disease, and other pathologies.
Modeller, often stylized as MODELLER, is a computer program used for homology modeling to produce models of protein tertiary structures and quaternary structures (rarer). It implements a method inspired by nuclear magnetic resonance spectroscopy of proteins, termed satisfaction of spatial restraints, by which a set of geometrical criteria are used to create a probability density function for the location of each atom in the protein. The method relies on an input sequence alignment between the target amino acid sequence to be modeled and a template protein which structure has been solved.
LiveBench is a continuously running benchmark project for assessing the quality of protein structure prediction and secondary structure prediction methods. LiveBench focuses mainly on homology modeling and protein threading but also includes secondary structure prediction, comparing publicly available webserver output to newly deposited protein structures in the Protein Data Bank. Like the EVA project and unlike the related CASP and CAFASP experiments, LiveBench is intended to study the accuracy of predictions that would be obtained by non-expert users of publicly available prediction methods. A major advantage of LiveBench and EVA over CASP projects, which run once every two years, is their comparatively large data set.
CAFASP, or the Critical Assessment of Fully Automated Structure Prediction, is a large-scale blind experiment in protein structure prediction that studies the performance of automated structure prediction webservers in homology modeling, fold recognition, and ab initio prediction of protein tertiary structures based only on amino acid sequence. The experiment runs once every two years in parallel with CASP, which focuses on predictions that incorporate human intervention and expertise. Compared to related benchmarking techniques LiveBench and EVA, which run weekly against newly solved protein structures deposited in the Protein Data Bank, CAFASP generates much less data, but has the advantage of producing predictions that are directly comparable to those produced by human prediction experts. Recently CAFASP has been run essentially integrated into the CASP results rather than as a separate experiment.
RAPTOR is protein threading software used for protein structure prediction. It has been replaced by RaptorX, which is much more accurate than RAPTOR.
Residue depth (RD) is a solvent exposure measure that describes to what extent a residue is buried in the protein structure space. It complements the information provided by conventional accessible surface area (ASA).
RaptorX for protein structure modeling and function prediction
Discovery Studio is a suite of software for simulating small molecule and macromolecule systems. It is developed and distributed by Accelrys.
SWISS-MODEL is a structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. Homology modeling is currently the most accurate method to generate reliable three-dimensional protein structure models and is routinely used in many practical applications. Homology modelling methods make use of experimental protein structures ("templates") to build models for evolutionary related proteins ("targets").
PredictProtein (PP) is an automatic service that searches up-to-date public sequence databases, creates alignments, and predicts aspects of protein structure and function. Users send a protein sequence and receive a single file with results from database comparisons and prediction methods. PP went online in 1992 at the European Molecular Biology Laboratory; since 1999 it has operated from Columbia University and in 2009 it moved to the Technische Universität München. Although many servers have implemented particular aspects, PP remains the most widely used public server for structure prediction: over 1.5 million requests from users in 104 countries have been handled; over 13000 users submitted 10 or more different queries. PP web pages are mirrored in 17 countries on 4 continents. The system is optimized to meet the demands of experimentalists not experienced in bioinformatics. This implied that we focused on incorporating only high-quality methods, and tried to collate results omitting less reliable or less important ones.
Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).
Continuous Automated Model EvaluatiOn (CAMEO) is a community-wide project to continuously evaluate the accuracy and reliability of protein structure prediction servers in a fully automated manner. CAMEO is a continuous and fully automated complement to the bi-annual CASP experiment. Currently, CAMEO evaluates predictions for predicted three-dimensional protein structures (3D), ligand binding site predictions in proteins (LB), and model quality estimation tools (QE).
CS23D is a web server to generate 3D structural models from NMR chemical shifts. CS23D combines maximal fragment assembly with chemical shift threading, de novo structure generation, chemical shift-based torsion angle prediction, and chemical shift refinement. CS23D makes use of RefDB and ShiftX.
I-TASSER is a bioinformatics method for predicting three-dimensional structure model of protein molecules from amino acid sequences. It detects structure templates from the Protein Data Bank by a technique called fold recognition. The full-length structure models are constructed by reassembling structural fragments from threading templates using replica exchange Monte Carlo simulations. I-TASSER is one of the most successful protein structure prediction methods in the community-wide CASP experiments.
Alfonso Valencia is a Spanish biologist, ICREA Professor, current director of the Life Sciences department at Barcelona Supercomputing Center. and of Spanish National Bioinformatics Institute (INB-ISCIII). From 2015-2018, he was President of the International Society for Computational Biology. His research is focused on the study of biomedical systems with computational biology and bioinformatics approaches.
