Structural domain detection software tools | Protein data analysis
Protein structures are comprised of modular elements known as domains. These units are used and re-used over and over in nature, and usually serve some particular function in the structure. Thus it is useful to be able to break up a protein of interest into its component domains, prior to similarity searching for example.
Predicts 3D structure of a protein sequence. Phyre is a web application that investigates known homologues, builds a hidden Markov model (HMM) of the targeted sequence based on the detected homologues and scans it against a database of HMMs of known protein structures. It also provides advanced features such as a batch submission of a large number of protein sequences for modelling or Phyre Investigator, that allows users to analyze model quality, function and effects of mutations.
Aggregates a number of protein annotation tools and provides services or software to allow users to perform truly scalable biological analyses. PSIPRED offers to the user the possibility to choose the method wanted to conduct the analysis. It proposes the following sequence and structure annotation methods: PSIPRED, GenTHREADER, pGenTHREADER, pDomTHREADER, MEMSAT-SVM/MEMSAT3, MEMPACK, BioSerf, MetSite, HSPred, DISOPRED2, DomPred and FFPred. The tool permits to select any number of appropriate simultaneous analyses across all the applicable methods and easily explore results.
An independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance.
A program for automatic identification of domains in protein three-dimensional structures. PDP performance was assessed by three different benchmarks: (i) by comparison with the expert-curated SCOP database of structural domains; (ii) by comparison with a collection of manual domain assignments; and (iii) by comparison with a set of 55 proteins, frequently used as a benchmark for automatic domain assignment. In all these benchmarks PDP identified domains correctly in more than 80% of proteins.
Enables users of the CDD (conserved domain database) resource to examine curated hierarchies. CDD and CDTree used in concert, serve as a powerful tool in protein classification, as they allow users to analyze protein sequences in the context of domain family hierarchies.
Predicts two-class b-turns and the individual b-turn types. To proceed, NetTurnP uses evolutionary information and predicted protein sequence features. It was tested on a dataset of 426 non-homologous protein chains. The tool has obtained Matthews correlation coefficients values of 0.36 and 0.31 for the type specific b-turn predictions, type I and II, respectively. It can predict if an amino acid is located in a Beta-turn or not.