Automatic extraction of protein point mutations using a graph bigram association.

Protein point mutations are an essential component of the evolutionary and experimental analysis of protein structure and function. While many manually curated databases attempt to index point mutations, most experimentally generated point mutations and the biological impacts of the changes are described in the peer-reviewed published literature. We describe an application, Mutation GraB (Graph Bigram), that identifies, extracts, and verifies point mutations from biomedical literature.

GRIS: glycoprotein-hormone receptor information system.

The glycoprotein-hormone receptor information system (GRIS) presents a comprehensive view on all available molecular data for the lutropin/choriogonadotropin receptor, follitropin receptor, and thyrotropin receptor G protein-coupled receptors. It features a mutation database presently containing 696 point mutations, combined with all sequences and the associated homology models. The mutation information was automatically extracted from the literature and manually augmented with respect to constitutivity, surface expression, sensitivity to hormones, and binding affinity.

A family-based approach reveals the function of residues in the nuclear receptor ligand-binding domain.

Literature studies, 3D structure data, and a series of sequence analysis techniques were combined to reveal important residues in the structure and function of the ligand-binding domain of nuclear hormone receptors. A structure-based multiple sequence alignment allowed for the seamless combination of data from many different studies on different receptors into one single functional model. It was recently shown that a combined analysis of sequence entropy and variability can divide residues in five classes; (1) the main function or active site, (2) support for the main function, (3) signal transduction, (4) modulator or ligand binding and (5) the rest.

Automated extraction of mutation data from the literature: application of MuteXt to G protein-coupled receptors and nuclear hormone receptors.

Motivation: The amount of genomic and proteomic data that is published daily in the scientific literature is outstripping the ability of experimental scientists to stay current. Reviews, the traditional medium for collating published observations, are also unable to keep pace. For some specific classes of information (e.

NRSAS: Nuclear Receptor Structure Analysis Servers.

We present a coherent series of servers that can perform a large number of structure analyses on nuclear hormone receptors. These servers are part of the NucleaRDB project, which provides a powerful information system for nuclear hormone receptors. The computations performed by the servers include homology modelling, structure validation, calculating contacts, accessibility values, hydrogen bonding patterns, predicting mutations and a host of two- and three-dimensional visualisations.

NRMD: Nuclear Receptor Mutation Database.

The NRMD is a database for nuclear receptor mutation information. It includes mutation information from SWISS-PROT/TrEMBL, several web-based mutation data resources, and data extracted from the literature in a fully automatic manner. Because it is also possible to add mutations manually, a hundred mutations were added for completeness.

GPCRDB information system for G protein-coupled receptors.

The GPCRDB is a molecular class-specific information system that collects, combines, validates and disseminates heterogeneous data on G protein-coupled receptors (GPCRs). The database stores data on sequences, ligand binding constants and mutations. The system also provides computationally derived data such as sequence alignments, homology models, and a series of query and visualization tools.

Phosphorylation and intramolecular stabilization of the ligand binding domain in the nuclear receptor steroidogenic factor 1.

Steroidogenic factor 1 (SF-1) is an orphan nuclear receptor with no known ligand. We showed previously that phosphorylation at serine 203 located N'-terminal to the ligand binding domain (LBD) enhanced cofactor recruitment, analogous to the ligand-mediated recruitment in ligand-dependent receptors. In this study, results of biochemical analyses and an LBD helix assembly assay suggest that the SF-1 LBD adopts an active conformation, with helices 1 and 12 packed against the predicted alpha-helical bundle, in the apparent absence of ligand.