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CASP
Critical Assessment of Structure Prediction (CASP), sometimes called Critical Assessment of Protein Structure Prediction, 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 predic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaFold
AlphaFold is an artificial intelligence (AI) program developed by DeepMind, a subsidiary of Alphabet Inc., Alphabet, which performs Protein structure prediction, predictions of protein structure. The program is designed as a deep learning system. AlphaFold AI software has had two major versions. A team of researchers that used AlphaFold 1 (2018) placed first in the overall rankings of the 13th Critical Assessment of protein Structure Prediction (CASP) in December 2018. The program was particularly successful at predicting the most accurate structure for targets rated as the most difficult by the competition organisers, where no existing Threading (protein sequence), template structures were available from proteins with a partially similar sequence. A team that used AlphaFold 2 (2020) repeated the placement in the CASP competition in November 2020. The team achieved a level of accuracy much higher than any other group. It scored above 90 for around two-thirds of the proteins in C ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Global Distance Test
The global distance test (GDT), also written as GDT_TS to represent "total score", is a measure of similarity between two protein structures with known amino acid correspondences (e.g. identical amino acid sequences) but different tertiary structures. It is most commonly used to compare the results of protein structure prediction to the experimentally determined structure as measured by X-ray crystallography, protein NMR, or, increasingly, cryoelectron microscopy. The metric was developed by Adam Zemla at Lawrence Livermore National Laboratory and originally implemented in the Local-Global Alignment (LGA) program. It is intended as a more accurate measurement than the common root-mean-square deviation (RMSD) metric - which is sensitive to outlier regions created, for example, by poor modeling of individual loop regions in a structure that is otherwise reasonably accurate. The conventional GDT_TS score is computed over the alpha carbon atoms and is reported as a percentage, rangin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Protein Structure Prediction
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes). Starting in 1994, the performance of current methods is assessed biannually in the CASP experiment (Critical Assessment of Techniques for Protein Structure Prediction). A continuous evaluation of protein structure prediction web servers is performed by the community project CAMEO3D. Protein structure and terminology Proteins are chains of amino acids joined together by peptide bonds. Many conformations of this chain are possible due to the rotation of the main chain abou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Protein Structure Prediction
Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes). Starting in 1994, the performance of current methods is assessed biannually in the CASP experiment (Critical Assessment of Techniques for Protein Structure Prediction). A continuous evaluation of protein structure prediction web servers is performed by the community project CAMEO3D. Protein structure and terminology Proteins are chains of amino acids joined together by peptide bonds. Many conformations of this chain are possible due to the rotation of the main chain abou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homology Modeling
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "''target''" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (the "''template''"). Homology modeling relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence. It has been seen that protein structures are more conserved than protein sequences amongst homologues, but sequences falling below a 20% sequence identity can have very different structure. Evolutionarily related proteins have similar sequences and naturally occurring homologous proteins have similar protein structure. It has been shown that three-dimensional protein structure is evolutionarily more conserved than would be expected on the basis of sequence ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
HHpred / HHsearch
The HH-suite is an open-source software package for sensitive protein sequence searching. It contains programs that can search for similar protein sequences in protein sequence databases. Sequence searches are a standard tool in modern biology with which the function of unknown proteins can be inferred from the functions of proteins with similar sequences. HHsearch and HHblits are two main programs in the package and the entry point to its search function, the latter being a faster iteration. HHpred is an online server for protein structure prediction that uses homology information from HH-suite. The HH-suite searches for sequences using hidden Markov models (HMMs). The name comes from the fact that it performs HMM-HMM alignments. Among the most popular methods for protein sequence matching, the programs have been cited more than 5000 times total according to Google Scholar. Background Proteins are central players in all of life's processes. Understanding them is central to un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
De Novo Protein Structure Prediction
In computational biology, ''de novo'' protein structure prediction refers to an algorithmic process by which protein tertiary structure is predicted from its amino acid primary sequence. The problem itself has occupied leading scientists for decades while still remaining unsolved. According to Science, the problem remains one of the top 125 outstanding issues in modern science. At present, some of the most successful methods have a reasonable probability of predicting the folds of small, single-domain proteins within 1.5 angstroms over the entire structure. ''De novo'' methods tend to require vast computational resources, and have thus only been carried out for relatively small proteins. De novo protein structure modeling is distinguished from Template-based modeling (TBM) by the fact that no solved homologue to the protein of interest is used, making efforts to predict protein structure from amino acid sequence exceedingly difficult. Prediction of protein structure ''de novo'' for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Protein Structure Initiative
The Protein Structure Initiative (PSI) was a USA based project that aimed at accelerating discovery in structural genomics and contribute to understanding biological function. Funded by the U.S. National Institute of General Medical Sciences (NIGMS) between 2000 and 2015, its aim was to reduce the cost and time required to determine three-dimensional protein structures and to develop techniques for solving challenging problems in structural biology, including membrane proteins. Over a dozen research centers have been supported by the PSI for work in building and maintaining high-throughput structural genomics pipelines, developing computational protein structure prediction methods, organizing and disseminating information generated by the PSI, and applying high-throughput structure determination to study a broad range of important biological and biomedical problems. The project has been organized into three separate phases. The first phase of the Protein Structure Initiative (PSI- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Critical Assessment Of Function Annotation
The Critical Assessment of Functional Annotation (CAFA) is an experiment designed to provide a large-scale assessment of computational methods dedicated to predicting protein function. Different algorithms are evaluated by their ability to predict the Gene Ontology (GO) terms in the categories of Molecular Function, Biological Process, and Cellular Component. The experiment consists of two tracks: (i) the eukaryotic track, (ii) the prokaryotic track. In each track, a set of targets is provided by the organizers. Participants are expected to submit their predictions by the submission deadline, after which they are assessed according to a set of specific metrics. Motivation The genome of an organism may consist of hundreds to tens of thousands of genes, which encode for hundreds of thousands of different protein sequences. Due to the relatively low cost of genome sequencing, determining gene and protein sequences is fast and inexpensive. Thousands of species have been sequenced s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DeepMind
DeepMind Technologies is a British artificial intelligence subsidiary of Alphabet Inc. and research laboratory founded in 2010. DeepMind was List of mergers and acquisitions by Google, acquired by Google in 2014 and became a wholly owned subsidiary of Alphabet Inc., Alphabet Inc, after Google's restructuring in 2015. The company is based in London, with research centres in Canada, France, and the United States. DeepMind has created a neural network that learns how to play video games in a fashion similar to that of humans, as well as a Neural Turing machine, or a neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain. DeepMind made headlines in 2016 after its AlphaGo program beat a human professional Go (game), Go player Lee Sedol, a world champion, in AlphaGo versus Lee Sedol, a five-game match, which was the subject of a documentary film. A more general progr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LiveBench
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 Critical Assessment of Structure Prediction (CASP), sometimes called Critical Assessment of Protein Structure Prediction, is a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994. CASP prov ... 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. Reference ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
EVA (benchmark)
EVA was a continuously running Benchmark (computing), benchmark project for assessing the quality and value of protein structure prediction and Protein structure prediction#Secondary structure, secondary structure prediction methods. Methods for predicting both secondary structure and tertiary structure - including homology modeling, protein threading, and contact order prediction - were compared to results from each week's newly solved protein structures deposited in the Protein Data Bank. The project aimed to determine the prediction accuracy that would be expected for non-expert users of common, publicly available prediction webservers; this is similar to the related LiveBench project and stands in contrast to the bi-yearly benchmark CASP, which aims to identify the maximum accuracy achievable by prediction experts. References * Rost B, Eyrich VA. (2001). EVA: large-scale analysis of secondary structure prediction. ''Proteins'' Suppl 5:192-9. * Eyrich VA, Marti-Renom MA, Przybyl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
