Andrean Goede

A comprehensive view on proteasomal sequences: implications for the evolution of the proteasome.

Proteasomes are large multimeric self-compartmentizing proteases, which play a crucial role in the clearance of misfolded proteins, breakdown of regulatory proteins, processing of proteins by specific partial proteolysis, cell cycle control as well as preparation of peptides for immune presentation. Two main types can be distinguished by their different tertiary structure: the 20S proteasome and the proteasome-like heat shock protein encoded by heat shock locus V, hslV. Usually, each biological kingdom is characterized by its specific type of proteasome. The 20S proteasomes occur in eukarya and archaea whereas hslV protease is prevalent in bacteria. To verify this rule we applied a genome-wide sequence search to identify proteasomal sequences in data of finished and yet unfinished genome projects. We found several exceptions to this paradigm: (1) Protista: in addition to the 20S proteasome, Leishmania, Trypanosoma and Plasmodium contained hslV, which may have been acquired from an alpha-proteobacterial progenitor of mitochondria. (2) Bacteria: for Magnetospirillum magnetotacticum and Enterococcus faecium we found that each contained two distinct hslVs due to gene duplication or horizontal transfer. Including unassembled data into the analyses we confirmed that a number of bacterial genomes do not contain any proteasomal sequence due to gene loss. (3) High G+C Gram-positives: we confirmed that high G+C Gram-positives possess 20S proteasomes rather than hslV proteases. The core of the 20S proteasome consists of two distinct main types of homologous monomers, alpha and beta, which differentiated into seven subtypes by further gene duplications. By looking at the genome of the intracellular pathogen Encephalitozoon cuniculi we were able to show that differentiation of beta-type subunits into different subtypes occurred earlier than that of alpha-subunits. Additionally, our search strategy had an important methodological consequence: a comprehensive sequence search for a particular protein should also include the raw sequence data when possible because proteins might be missed in the completed assembled genome. The structure-based multiple proteasomal alignment of 433 sequences from 143 organisms can be downloaded from the URL dagger and will be updated regularly.

Voronoi Cell: New Method for Allocation of Space among Atoms: Elimination of Avoidable Errors in Calculation of Atomic Volume and Density

In computing the volume occupied by atoms and the density in proteins, one is faced with the problem of intersecting spheres. To estimate either, the space between the atoms has to be divided according to the location of the atoms relative to each other. Various methods, based on Voronois idea of approximating the atomic space by polyhedra, have been proposed for this purpose. Comparing procedures concerned with the allocation of space among distinct atoms, we observe different partitionings of space, with deviations of more than 100% for particular atoms. Furthermore, we find that the separating planes of different Voronoi procedures do not meet the intersection circles of covalently linked atoms. This leads to a misallocation of space of up to 7% for atom pairs that largely differ in atomic size (e.g., C—H). Several algorithms are negatively affected by small unallocated polyhedra (“vertex error”). These effects are cumulative for a small protein up to a loss of some 60 Å3 of total volume, which would correspond to the deletion of one complete residue. To overcome these errors, instead of using dividing planes between the atoms, we use curved surfaces, defined as the set of those geometrical loci with equal orthogonal distance to the surfaces of the van der Waals spheres under consideration. The proposed dividing surface meets not only the intersection circle of the two van der Waals spheres but also the intersection circle of the two spheres enlarged by an arbitrary value (e.g., radius of water). This hyperbolic surface enveloping the Voronoi cell can be easily constructed and offers the following advantages: no misallocation of volume for atoms of different size, no vertex error, geometrically reasonable allocation of the volume among atoms, avoidance of discontinuities between neighboring atoms, and improved applicability to water‐accessible protein surfaces.

SuperLooper—a prediction server for the modeling of loops in globular and membrane proteins

SuperLooper provides the first online interface for the automatic, quick and interactive search and placement of loops in proteins (LIP). A database containing half a billion segments of water-soluble proteins with lengths up to 35 residues can be screened for candidate loops. A specified database containing 180 000 membrane loops in proteins (LIMP) can be searched, alternatively. Loop candidates are scored based on sequence criteria and the root mean square deviation (RMSD) of the stem atoms. Searching LIP, the average global RMSD of the respective top-ranked loops to the original loops is benchmarked to be <2 Å, for loops up to six residues or <3 Å for loops shorter than 10 residues. Other suitable conformations may be selected and directly visualized on the web server from a top-50 list. For user guidance, the sequence homology between the template and the original sequence, proline or glycine exchanges or close contacts between a loop candidate and the remainder of the protein are denoted. For membrane proteins, the expansions of the lipid bilayer are automatically modeled using the TMDET algorithm. This allows the user to select the optimal membrane protein loop concerning its relative orientation to the lipid bilayer. The server is online since October 2007 and can be freely accessed at URL: http://bioinformatics.charite.de/superlooper/

Voronoia: analyzing packing in protein structures

The packing of protein atoms is an indicator for their stability and functionality, and applied in determining thermostability, in protein design, ligand binding and to identify flexible regions in proteins. Here, we present Voronoia, a database of atomic-scale packing data for protein 3D structures. It is based on an improved Voronoi Cell algorithm using hyperboloid interfaces to construct atomic volumes, and to resolve solvent-accessible and -inaccessible regions of atoms. The database contains atomic volumes, local packing densities and interior cavities calculated for 61 318 biological units from the PDB. A report for each structure summarizes the packing by residue and atom types, and lists the environment of interior cavities. The packing data are compared to a nonredundant set of structures from SCOP superfamilies. Both packing densities and cavities can be visualized in the 3D structures by the Jmol plugin. Additionally, PDB files can be submitted to the Voronoia server for calculation. This service performs calculations for most full-atomic protein structures within a few minutes. For batch jobs, a standalone version of the program with an optional PyMOL plugin is available for download. The database can be freely accessed at: http://bioinformatics.charite.de/voronoia.

SuperPred: update on drug classification and target prediction

The SuperPred web server connects chemical similarity of drug-like compounds with molecular targets and the therapeutic approach based on the similar property principle. Since the first release of this server, the number of known compound–target interactions has increased from 7000 to 665 000, which allows not only a better prediction quality but also the estimation of a confidence. Apart from the addition of quantitative binding data and the statistical consideration of the similarity distribution in all drug classes, new approaches were implemented to improve the target prediction. The 3D similarity as well as the occurrence of fragments and the concordance of physico-chemical properties is also taken into account. In addition, the effect of different fingerprints on the prediction was examined. The retrospective prediction of a drug class (ATC code of the WHO) allows the evaluation of methods and descriptors for a well-characterized set of approved drugs. The prediction is improved by 7.5% to a total accuracy of 75.1%. For query compounds with sufficient structural similarity, the web server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets. SuperPred is publicly available without registration at: http://prediction.charite.de.

Comparison of 2D similarity and 3D superposition. Application to searching a conformational drug database

In a database of about 2000 approved drugs, represented by 10(5) structural conformers, we have performed 2D comparisons (Tanimoto coefficients) and 3D superpositions. For one class of drugs the correlation between structural resemblance and similar action was analyzed in detail. In general Tanimoto coefficients and 3D scores give similar results, but we find that 2D similarity measures neglect important structural/funtional features. Examples for both over- and underestimation of similarity by 2D metrics are discussed. The required additional effort for 3D superpositions is assessed by implementation of a fast algorithm with a processing time below 0.01 s and a more sophisticated approach (0.5 s per superposition). According to the improvement of similarity detection compared to 2D screening and the pleasant rapidity on a desktop PC, full-atom 3D superposition will be an upcoming method of choice for library prioritization or similarity screening approaches.

Structural and kinetic modeling of an activating helix switch in the rhodopsin-transducin interface

Extracellular signals prompt G protein-coupled receptors (GPCRs) to adopt an active conformation (R*) and catalyze GDP/GTP exchange in the α-subunit of intracellular G proteins (Gαβγ). Kinetic analysis of transducin (Gtαβγ) activation shows that an intermediary R*·Gtαβγ·GDP complex is formed that precedes GDP release and formation of the nucleotide-free R*·G protein complex. Based on this reaction sequence, we explore the dynamic interface between the proteins during formation of these complexes. We start from the R* conformation stabilized by a Gtα C-terminal peptide (GαCT) obtained from crystal structures of the GPCR opsin. Molecular modeling allows reconstruction of the fully elongated C-terminal α-helix of Gtα (α5) and shows how α5 can be docked to the open binding site of R*. Two modes of interaction are found. One of them – termed stable or S-interaction – matches the position of the GαCT peptide in the crystal structure and reproduces the hydrogen-bonding networks between the C-terminal reverse turn of GαCT and conserved E(D)RY and NPxxY(x)5,6F regions of the GPCR. The alternative fit – termed intermediary or I-interaction – is distinguished by a tilt (42°) and rotation (90°) of α5 relative to the S-interaction and shows different α5 contacts with the NPxxY(x)5,6F region and the second cytoplasmic loop of R*. From the 2 α5 interactions, we derive a “helix switch” mechanism for the transition of R*·Gtαβγ·GDP to the nucleotide-free R*·G protein complex that illustrates how α5 might act as a transmission rod to propagate the conformational change from the receptor-G protein interface to the nucleotide binding site.

SuperLigands - a database of ligand structures derived from the Protein Data Bank

BackgroundCurrently, the PDB contains approximately 29,000 protein structures comprising over 70,000 experimentally determined three-dimensional structures of over 5,000 different low molecular weight compounds. Information about these PDB ligands can be very helpful in the field of molecular modelling and prediction, particularly for the prediction of protein binding sites and function.DescriptionHere we present an Internet accessible database delivering PDB ligands in the MDL Mol file format which, in contrast to the PDB format, includes information about bond types. Structural similarity of the compounds can be detected by calculation of Tanimoto coefficients and by three-dimensional superposition. Topological similarity of PDB ligands to known drugs can be assessed via Tanimoto coefficients.ConclusionSuperLigands supplements the set of existing resources of information about small molecules bound to PDB structures. Allowing for three-dimensional comparison of the compounds as a novel feature, this database represents a valuable means of analysis and prediction in the field of biological and medical research.

Driving Forces of Proteasome-catalyzed Peptide Splicing in Yeast and Humans

Proteasome-catalyzed peptide splicing (PCPS) represents an additional activity of mammalian 20S proteasomes recently identified in connection with antigen presentation. We show here that PCPS is not restricted to mammalians but that it is also a feature of yeast 20S proteasomes catalyzed by all three active site β subunits. No major differences in splicing efficiency exist between human 20S standard- and immuno-proteasome or yeast 20S proteasome. Using H218O to monitor the splicing reaction we also demonstrate that PCPS occurs via direct transpeptidation that slightly favors the generation of peptides spliced in cis over peptides spliced in trans. Splicing efficiency itself is shown to be controlled by proteasomal cleavage site preference as well as by the sequence characteristics of the spliced peptides. By use of kinetic data and quantitative analyses of PCPS obtained by mass spectrometry we developed a structural model with two PCPS binding sites in the neighborhood of the active Thr1.

Inhomogeneous molecular density: reference packing densities and distribution of cavities within proteins

MOTIVATION There is no consensus in the literature about how the deepest portions of protein structures are packed. Using an improved Voronoi procedure, we calculate reference packing densities for different regions in the protein interior. Furthermore, we want to clarify where cavities are located. RESULTS Sets of reference packing densities are provided for regions in proteins that differ in their distance to the surface and to internal cavities, supplementing previous data. Packing in the protein interior is tight but generally inhomogeneous. There are about 4.4 cavities per 100 amino acids in protein structures, they occur in all regions, most frequently in a depth of 2.5-3.6 A underneath the Connolly surface. However, the deepest protein regions have a lower mean packing density than circumjacent regions, because more contacts to cavities occur in the core. AVAILABILITY/SUPPLEMENTARY INFORMATION Calculation software and detailed packing data are available on request.