Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants.

Molecular chaperones are essential elements of the protein quality control machinery that governs translocation and folding of nascent polypeptides, refolding and degradation of misfolded proteins, and activation of a wide range of client proteins. The prokaryotic heat-shock protein DnaK is the E. coli representative of the ubiquitous Hsp70 family, which specializes in the binding of exposed hydrophobic regions in unfolded polypeptides. Accurate prediction of DnaK binding sites in E. coli proteins is an essential prerequisite to understand the precise function of this chaperone and the properties of its substrate proteins. In order to map DnaK binding sites in protein sequences, we have developed an algorithm that combines sequence information from peptide binding experiments and structural parameters from homology modelling. We show that this combination significantly outperforms either single approach. The final predictor had a Matthews correlation coefficient (MCC) of 0.819 when assessed over the 144 tested peptide sequences to detect true positives and true negatives. To test the robustness of the learning set, we have conducted a simulated cross-validation, where we omit sequences from the learning sets and calculate the rate of repredicting them. This resulted in a surprisingly good MCC of 0.703. The algorithm was also able to perform equally well on a blind test set of binders and non-binders, of which there was no prior knowledge in the learning sets. The algorithm is freely available at http://limbo.vib.be.

Accurate prediction of amyloid-forming amino acid sequences remains an important challenge. We here present an online database that provides open access to the largest set of experimentally characterized amyloid forming hexapeptides. To this end, we expanded our previous set of 280 hexapeptides used to develop the Waltz algorithm with 89 peptides from literature review and by systematic experimental characterisation of the aggregation of 720 hexapeptides by transmission electron microscopy, dye binding and Fourier transform infrared spectroscopy. This brings the total number of experimentally characterized hexapeptides in the WALTZ-DB database to 1089, of which 244 are annotated as positive for amyloid formation.

Recently, three naturally occurring mutations in the serpentine region of the FSH receptor (FSHr) (D567N and T449I/A) have been identified in three families with spontaneous ovarian hyperstimulation syndrome (OHSS). All mutant receptors displayed abnormally high sensitivity to human chorionic gonadotropin and, in addition, D567N and T449A displayed concomitant increase in sensitivity to TSH and detectable constitutive activity. In the present study, we have used a combination of site-directed mutagenesis experiments and molecular modeling to explore the mechanisms responsible for the phenotype of the three OHSS FSHr mutants. Our results suggest that all mutations lead to weakening of interhelical locks between transmembrane helix (TM)-VI and TM-III, or TM-VI and TM-VII, which contributes to maintaining the receptor in the inactive state. They also indicate that broadening of the functional specificity of the mutant FSHr constructs is correlated to their increase in constitutive activity. This relation between basal activity and functional specificity is a characteristic of the FSHr, which is not shared by the other glycoprotein hormone receptors. It leads to the interesting suggestion that different pathways have been followed during primate evolution to avoid promiscuous stimulation of the TSHr and FSHr by human chorionic gonadotropin. In the hFSHr, specificity would be exerted both by the ectodomain and the serpentine portion.

Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4 965 073 regulatory as well as 133 505 coding human SNPs and 14 935 disease mutations, and phenotypic descriptions of 43 797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/.

The Solubis method presented here automates the process of carefully selecting point mutations that minimize the intrinsic aggregation propensity while improving local protein stability.

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. At present, the NRMD contains information about 893 mutations in 54 nuclear receptors. A common numbering scheme for all nuclear receptors eases the use of the information for many kinds of studies. The NRMD is freely available to academia and industry as a stand-alone version at: www.receptors.org/NR/.