Topic
Phyre
About: Phyre is a research topic. Over the lifetime, 35 publications have been published within this topic receiving 11209 citations. The topic is also known as: Protein Homology/AnalogY Recognition Engine.
Papers
TL;DR: An updated protocol for Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants for a user's protein sequence.
Abstract: Phyre2 is a web-based tool for predicting and analyzing protein structure and function. Phyre2 uses advanced remote homology detection methods to build 3D models, predict ligand binding sites, and analyze amino acid variants in a protein sequence. Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2
. A typical structure prediction will be returned between 30 min and 2 h after submission.
9,855 citations
TL;DR: This protocol provides a guide to interpreting the output of structure prediction servers in general and one such tool in particular, the protein homology/analogy recognition engine (Phyre), which can reliably detect up to twice as many remote homologies as standard sequence-profile searching.
Abstract: Determining the structure and function of a novel protein is a cornerstone of many aspects of modern biology. Over the past decades, a number of computational tools for structure prediction have been developed. It is critical that the biological community is aware of such tools and is able to interpret their results in an informed way. This protocol provides a guide to interpreting the output of structure prediction servers in general and one such tool in particular, the protein homology/analogy recognition engine (Phyre). New profile–profile matching algorithms have improved structure prediction considerably in recent years. Although the performance of Phyre is typical of many structure prediction systems using such algorithms, all these systems can reliably detect up to twice as many remote homologies as standard sequence-profile searching. Phyre is widely used by the biological community, with >150 submissions per day, and provides a simple interface to results. Phyre takes 30 min to predict the structure of a 250-residue protein.
4,685 citations
TL;DR: The main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted, and contains the first official mapping between these two databases.
Abstract: Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).
60 citations
Proceedings Article•
15 Aug 2019TL;DR: The PHYRE benchmark as discussed by the authors is designed to encourage the development of learning algorithms that are sample-efficient and generalize well across puzzles in a 2D physical environment, and has been used to test several modern learning algorithms.
Abstract: Understanding and reasoning about physics is an important ability of intelligent agents. We develop the PHYRE benchmark for physical reasoning that contains a set of simple classical mechanics puzzles in a 2D physical environment. The benchmark is designed to encourage the development of learning algorithms that are sample-efficient and generalize well across puzzles. We test several modern learning algorithms on PHYRE and find that these algorithms fall short in solving the puzzles efficiently. We expect that PHYRE will encourage the development of novel sample-efficient agents that learn efficient but useful models of physics. For code and to play PHYRE for yourself, please visit https://player.phyre.ai.
55 citations
TL;DR: The genome sequence of MERS-CoV was analyzed and a potential B-cell epitope of the E protein was identified, which might significantly improve the current MERS vaccine development strategies.
Abstract: The outbreak of Middle East respiratory syndrome-coronavirus (MERS-CoV) in South Korea in April 2015 led to 186 infections and 37 deaths by the end of October 2015 MERS-CoV was isolated from the imported patient in China The envelope (E) protein, a small structural protein of MERS-CoV, plays an important role in host recognition and infection To identify the conserved epitopes of the E protein, sequence analysis was performed by comparing the E proteins from 42 MERS-CoV strains that triggered severe pandemics and infected humans in the past To predict the potential B cell epitopes of E protein, three most effective online epitope prediction programs, the ABCpred, Bepipred, and Protean programs from the LaserGene software were used All the nucleotides and amino acids sequences were obtained from the NCBI Database One potential epitope with a suitable length (amino acids 58–82) was confirmed and predicted to be highly antigenic This epitope had scores of >080 in ABCpred and level 035 in Bepipred programs Due to the lack of X-ray crystal structure of the E protein in the PDB database, the simulated 3D structure of the E protein were also predicted using PHYRE 2 and Pymol programs In conclusion, using bioinformatics methods, we analyzed the genome sequence of MERS-CoV and identified a potential B-cell epitope of the E protein, which might significantly improve our current MERS vaccine development strategies
33 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 1 |
| 2020 | 6 |
| 2019 | 3 |
| 2018 | 3 |
| 2017 | 1 |
| 2016 | 1 |