Discriminative modelling of context-specific amino acid substitution probabilities.

Motivation: Protein sequence searching and alignment are fundamental tools of modern biology. Alignments are assessed using their similarity scores, essentially the sum of substitution matrix scores over all pairs of aligned amino acids. We previously proposed a generative probabilistic method that yields scores that take the sequence context around each aligned residue into account.

HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment.

Sequence-based protein function and structure prediction depends crucially on sequence-search sensitivity and accuracy of the resulting sequence alignments. We present an open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM-based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.

A galaxy of folds.

Many protein classification systems capture homologous relationships by grouping domains into families and superfamilies on the basis of sequence similarity. Superfamilies with similar 3D structures are further grouped into folds. In the absence of discernable sequence similarity, these structural similarities were long thought to have originated independently, by convergent evolution.

Fast and accurate automatic structure prediction with HHpred.

Automated protein structure prediction is becoming a mainstream tool for biological research. This has been fueled by steady improvements of publicly available automated servers over the last decade, in particular their ability to build good homology models for an increasing number of targets by reliably detecting and aligning more and more remotely homologous templates. Here, we describe the three fully automated versions of the HHpred server that participated in the community-wide blind protein structure prediction competition CASP8.

PDBalert: automatic, recurrent remote homology tracking and protein structure prediction.

Background: During the last years, methods for remote homology detection have grown more and more sensitive and reliable. Automatic structure prediction servers relying on these methods can generate useful 3D models even below 20% sequence identity between the protein of interest and the known structure (template). When no homologs can be found in the protein structure database (PDB), the user would need to rerun the same search at regular intervals in order to make timely use of a template once it becomes available.

Phospholipid scramblases and Tubby-like proteins belong to a new superfamily of membrane tethered transcription factors.

Motivation: Phospholipid scramblases (PLSCRs) constitute a family of cytoplasmic membrane-associated proteins that were identified based upon their capacity to mediate a Ca(2+)-dependent bidirectional movement of phospholipids across membrane bilayers, thereby collapsing the normally asymmetric distribution of such lipids in cell membranes. The exact function and mechanism(s) of these proteins nevertheless remains obscure: data from several laboratories now suggest that in addition to their putative role in mediating transbilayer flip/flop of membrane lipids, the PLSCRs may also function to regulate diverse processes including signaling, apoptosis, cell proliferation and transcription. A major impediment to deducing the molecular details underlying the seemingly disparate biology of these proteins is the current absence of any representative molecular structures to provide guidance to the experimental investigation of their function.

HHsenser: exhaustive transitive profile search using HMM-HMM comparison.

HHsenser is the first server to offer exhaustive intermediate profile searches, which it combines with pairwise comparison of hidden Markov models. Starting from a single protein sequence or a multiple alignment, it can iteratively explore whole superfamilies, producing few or no false positives. The output is a multiple alignment of all detected homologs.

The MPI Bioinformatics Toolkit for protein sequence analysis.

The MPI Bioinformatics Toolkit is an interactive web service which offers access to a great variety of public and in-house bioinformatics tools. They are grouped into different sections that support sequence searches, multiple alignment, secondary and tertiary structure prediction and classification. Several public tools are offered in customized versions that extend their functionality.

HHrep: de novo protein repeat detection and the origin of TIM barrels.

HHrep is a web server for the de novo identification of repeats in protein sequences, which is based on the pairwise comparison of profile hidden Markov models (HMMs). Its main strength is its sensitivity, allowing it to detect highly divergent repeat units in protein sequences whose repeats could as yet only be detected from their structures. Examples include sequences with beta-propellor fold, ferredoxin-like fold, double psi barrels or (betaalpha)8 (TIM) barrels.

The HHpred interactive server for protein homology detection and structure prediction.

HHpred is a fast server for remote protein homology detection and structure prediction and is the first to implement pairwise comparison of profile hidden Markov models (HMMs). It allows to search a wide choice of databases, such as the PDB, SCOP, Pfam, SMART, COGs and CDD. It accepts a single query sequence or a multiple alignment as input.