Cornelius Frömmel

An Effective Solvation Term Based on Atomic Occupancies for Use in Protein Simulations

Abstract Several approaches to the treatment of solvent effects based on continuum models are reviewed and a new method based on occupied atomic volumes (occupancies) is proposed and tested. The new method describes protein-water interactions in terms of atomic solvation parameters, which represent the solvation free energy per unit of volume. These parameters were determined for six different atoms types, using experimental free energies of solvation. The method was implemented in the GROMOS and PRESTO molecular simulation program suites. Simulations with the solvation term require 20-50% more CPU time than the corresponding vacuum simulations and are approximately 20 times faster than explicit water simulations. The method and parameters were tested by carrying out 200 ps simulations of BPTI in water, in vacuo, and with the solvation term. The performance of the solvation term was assessed by comparing the structures and energies from the solvation simulations with the equivalent quantities derived from...

STRAP: editor for STRuctural Alignments of Proteins

STRAP is a comfortable and extensible tool for the generation and refinement of multiple alignments of protein sequences. Various sequence ordered input file formats are supported. These are the SwissProt-,GenBank-, EMBL-, DSSP- PDB-, MSF-, and plain ASCII text format. The special feature of STRAP is the simple visualization of spatial distances C(alpha)-atoms within the alignment. Thus structural information can easily be incorporated into the sequence alignment and can guide the alignment process in cases of low sequence similarities. Further STRAP is able to manage huge alignments comprising a lot of sequences. The protein viewers and modeling programs INSIGHT, RASMOL and WEBMOL are embedded into STRAP. STRAP is written in JAVA: The well-documented source code can be adapted easily to special requirements. STRAP may become the basis for complex alignment tools in the future.

Analysis of mammalian 20S proteasome biogenesis: the maturation of beta-subunits is an ordered two-step mechanism involving autocatalysis.

Maturation of eukaryotic 20S proteasomes involves the processing of beta‐subunits by limited proteolysis. To study the processing mechanism we analysed different point mutations of the beta‐subunit LMP2 in transfected human T2 cells. Here we show that the presence of the intact Gly‐1Thr1 consensus motif and Lys33 are essential for correct processing. Mutation of Thr1, the active site residue in mature subunits, or of Lys33, results in complete inhibition of processing at the consensus site. In addition, proprotein processing in vitro of wild‐type LMP2, incorporated in immature 16S precursor complexes, can be blocked by a proteasome‐specific inhibitor. While the processing of inhibitor‐treated wild‐type proprotein was completely prevented, the site‐directed mutagenesis of LMP2 results in processing intermediates carrying an extension of 8–10 residues preceding Thr1, suggesting an additional cleavage event within the prosequence. Furthermore, exchange of mammalian prosequences interferes with processing efficiency and suggests subunit specificity. Based on our data we propose a model for self‐activation of proteasomal beta‐subunits in which residue Thr1 serves as nucleophile and Lys33 as proton donor/acceptor. We provide evidence that subunit processing of mammalian beta‐subunits proceeds via a novel ordered two‐step mechanism involving autocatalysis.

Complete primary structure of thermitase from Thermoactinomyces vulgaris and its structural features related to the subtilisin-type proteinases

Thermitase, a thermostable alkaline proteinase, consists of a single polypeptide chain, containing 279 amino acid residues (M r = 28 369). The enzyme shows remarkable structural features of proteinases of the subtilisin type as shown by pronounced sequential homologies. The amino acid replacements, insertions and deletions observed when the amino acid sequence of the enzyme is compared with the sequences of several subtilisins are discussed with respect to substrate specificity and expected tertiary structure. The existence of a cysteinecontaining subgroup of subtilisin‐like proteinases is postulated.

PREDICTION OF SECONDARY STRUCTURAL CONTENT OF PROTEINS FROM THEIR AMINO ACID COMPOSITION ALONE. I. NEW ANALYTIC VECTOR DECOMPOSITION METHODS

The predictive limits of the amino acid composition for the secondary structural content (percentage of residues in the secondary structural states helix, sheet, and coil) in proteins are assessed quantitatively.

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.

Prediction of secondary structural content of proteins from their amino acid composition alone. II. The paradox with secondary structural class

The success rates reported for secondary structural class prediction with different methods are contradictory. On one side, the problem of recognizing the secondary structural class of a protein knowing only its amino acid composition appears completely solved by simply applying jury decision with an elliptically scaled distance function. Chou and coworkers repeatedly (see Crit. Rev. Biochem. Mol. Biol. 30:275–349, 1995) published prediction accuracies near 100%. On the other hand, traditional secondary structure prediction techniques achieve success rates of about 70% for the secondary structural state per residue and about 75% for structural class only with extensive input information (full sequence of the query protein, its amino acid composition and length, multiple alignments with homologous sequences).

Novel curcumin- and emodin-related compounds identified by in silico 2D/3D conformer screening induce apoptosis in tumor cells

BackgroundInhibition of the COP9 signalosome (CSN) associated kinases CK2 and PKD by curcumin causes stabilization of the tumor suppressor p53. It has been shown that curcumin induces tumor cell death and apoptosis. Curcumin and emodin block the CSN-directed c-Jun signaling pathway, which results in diminished c-Jun steady state levels in HeLa cells. The aim of this work was to search for new CSN kinase inhibitors analogue to curcumin and emodin by means of an in silico screening method.MethodsHere we present a novel method to identify efficient inhibitors of CSN-associated kinases. Using curcumin and emodin as lead structures an in silico screening with our in-house database containing more than 106 structures was carried out. Thirty-five compounds were identified and further evaluated by the Lipinskis rule-of-five. Two groups of compounds can be clearly discriminated according to their structures: the curcumin-group and the emodin-group. The compounds were evaluated in in vitro kinase assays and in cell culture experiments.ResultsThe data revealed 3 compounds of the curcumin-group (e.g. piceatannol) and 4 of the emodin-group (e.g. anthrachinone) as potent inhibitors of CSN-associated kinases. Identified agents increased p53 levels and induced apoptosis in tumor cells as determined by annexin V-FITC binding, DNA fragmentation and caspase activity assays.ConclusionOur data demonstrate that the new in silico screening method is highly efficient for identifying potential anti-tumor drugs.

Docking without docking: ISEARCH--prediction of interactions using known interfaces.

The increasing number of solved protein structures provides a solid number of interfaces, if protein–protein interactions, domain–domain contacts, and contacts between biological units are taken into account. An interface library gives us the opportunity to identify surface regions on a target molecule that are similar by local structure and residue composition. If both unbound components of a possible protein complex exhibit structural similarities to a known interface, the unbound structures can be superposed onto the known interfaces. The approach is accompanied by two mathematical problems. Protein surfaces have to be quickly screened by thousands of patches, and similarity has to be evaluated by a suitable scoring scheme. The used algorithm (NeedleHaystack) identifies similar patches within minutes. Structurally related sites are recognized even if only parts of the template patches are structurally related to the interface region. A successful prediction of the protein complex depends on a suitable template of the library. However, the performed tests indicate that interaction sites are identified even if the similarity is very low. The approach complements existing ab initio methods and provides valuable results on standard benchmark sets. Proteins 2007.