PERMOL: restraint-based protein homology modeling using DYANA or CNS

PSCD Domains of Pleuralin-1 from the Diatom Cylindrotheca fusiformis: NMR Structures and Interactions with Other Biosilica-Associated Proteins

Diatoms are eukaryotic unicellular algae characterized by silica cell walls and associated with three unique protein families, the pleuralins, frustulins, and silaffins. The NMR structure of the PSCD4 domain of pleuralin-1 from Cylindrotheca fusiformis contains only three short helical elements and is stabilized by five unique disulfide bridges. PSCD4 contains two binding sites for Ca(2+) ions with millimolar affinity. NMR-based interaction studies show an interaction of the domain with native silaffin-1A as well as with α-frustulins. The interaction sites of the two proteins mapped on the PSCD4 structure are contiguous and show only a small overlap. A plausible functional role of pleuralin could be to bind simultaneously silaffin-1A located inside the cell wall and α-frustulin coating the cell wall, thus connecting the interfaces between hypotheca and epitheca at the girdle bands. Restrained molecular dynamics calculations suggest a bead-chain-like structure of the central part of pleuralin-1.

Human cytomegalovirus major immediate early 1 protein targets host chromosomes by docking to the acidic pocket on the nucleosome surface

The 72-kDa immediate early 1 (IE1) protein encoded by human cytomegalovirus (hCMV) is a nuclearly localized promiscuous regulator of viral and cellular transcription. IE1 has long been known to associate with host mitotic chromatin, yet the mechanisms underlying this interaction have not been specified. In this study, we identify the cellular chromosome receptor for IE1. We demonstrate that the viral protein targets human nucleosomes by directly binding to core histones in a nucleic acid-independent manner. IE1 exhibits two separable histone-interacting regions with differential binding specificities for H2A-H2B and H3-H4. The H2A-H2B binding region was mapped to an evolutionarily conserved 10-amino-acid motif within the chromatin-tethering domain (CTD) of IE1. Results from experimental approaches combined with molecular modeling indicate that the IE1 CTD adopts a β-hairpin structure, docking with the acidic pocket formed by H2A-H2B on the nucleosome surface. IE1 binds to the acidic pocket in a way similar to that of the latency-associated nuclear antigen (LANA) of the Kaposi's sarcoma-associated herpesvirus. Consequently, the IE1 and LANA CTDs compete for binding to nucleosome cores and chromatin. Our work elucidates in detail how a key viral regulator is anchored to human chromosomes and identifies the nucleosomal acidic pocket as a joint target of proteins from distantly related viruses. Based on the striking similarities between the IE1 and LANA CTDs and the fact that nucleosome targeting by IE1 is dispensable for productive replication even in "clinical" strains of hCMV, we speculate that the two viral proteins may serve analogous functions during latency of their respective viruses.

Automated protein NMR structure determination in solution

The main drawback of protein NMR spectroscopy today is still the extensive amount of time required for solving a single structure. The main bottleneck in this respect is the manual evaluation of the experimental spectra. A clear solution to this challenge is the development of automated methods for this purpose. At the current stage of development, this goal has been almost or in a few cases fully reached for favorable cases such as well-behaved, stably folding smaller proteins below the 25 kDa range. For larger and/or more difficult molecules, the input of a human expert is still required. However, even here, automated routines will substantially speed up the structure determination process. In this report, we will summarize recent developments in this field and especially emphasize practical aspects important for a successful automated protein structure determination in solution. An important aspect closely related to structure determination is structure validation. Therefore, we devote a section to automated approaches for this topic.

Use of secondary structural information and C alpha-C alpha distance restraints to model protein structures with MODELLER

Protein secondary structure predictions and amino acid long range contact map predictions from primary sequence of proteins have been explored to aid in modelling protein tertiary structures. In order to evaluate the usefulness of secondary structure and 3D-residue contact prediction methods to model protein structures we have used the known Q3 (alpha-helix,beta-strands and irregular turns/loops) secondary structure information, along with residue-residue contact information as restraints for MODELLER. We present here results of our modelling studies on 30 best resolved single domain protein structures of varied lengths. The results shows that it is very difficult to obtain useful models even with 100% accurate secondary structure predictions and accurate residue contact predictions for up to 30% of residues in a sequence. The best models that we obtained for proteins of lengths 37, 70, 118, 136 and 193 amino acid residues are of RMSDs 4.17, 5.27, 9.12, 7.89 and 9.69,respectively. The results show that one can obtain better models for the proteins which have high percent of alpha-helix content. This analysis further shows that MODELLER restrain optimization program can be useful only if we have truly homologous structure(s) as a template where it derives numerous restraints, almost identical to the templates used. This analysis also clearly indicates that even if we satisfy several true residue-residue contact distances, up to 30%of their sequence length with fully known secondary structural information, we end up predicting model structures much distant from their corresponding native structures.

L11 domain rearrangement upon binding to RNA and thiostrepton studied by NMR spectroscopy

Ribosomal proteins are assumed to stabilize specific RNA structures and promote compact folding of the large rRNA. The conformational dynamics of the protein between the bound and unbound state play an important role in the binding process. We have studied those dynamical changes in detail for the highly conserved complex between the ribosomal protein L11 and the GTPase region of 23S rRNA. The RNA domain is compactly folded into a well defined tertiary structure, which is further stabilized by the association with the C-terminal domain of the L11 protein (L11_ctd). In addition, the N-terminal domain of L11 (L11_ntd) is implicated in the binding of the natural thiazole antibiotic thiostrepton, which disrupts the elongation factor function. We have studied the conformation of the ribosomal protein and its dynamics by NMR in the unbound state, the RNA bound state and in the ternary complex with the RNA and thiostrepton. Our data reveal a rearrangement of the L11_ntd, placing it closer to the RNA after binding of thiostrepton, which may prevent binding of elongation factors. We propose a model for the ternary L11–RNA–thiostrepton complex that is additionally based on interaction data and conformational information of the L11 protein. The model is consistent with earlier findings and provides an explanation for the role of L11_ntd in elongation factor binding.

A general method for the unbiased improvement of solution NMR structures by the use of related X-ray data, the AUREMOL-ISIC algorithm

Background

Rapid and accurate three-dimensional structure determination of biological macromolecules is mandatory to keep up with the vast progress made in the identification of primary sequence information. During the last few years the amount of data deposited in the protein data bank has substantially increased providing additional information for novel structure determination projects. The key question is how to combine the available database information with the experimental data of the current project ensuring that only relevant information is used and a correct structural bias is produced. For this purpose a novel fully automated algorithm based on Bayesian reasoning has been developed. It allows the combination of structural information from different sources in a consistent way to obtain high quality structures with a limited set of experimental data. The new ISIC (Intelligent Structural Information Combination) algorithm is part of the larger AUREMOL software package.

Results

Our new approach was successfully tested on the improvement of the solution NMR structures of the Ras-binding domain of Byr2 from Schizosaccharomyces pombe, the Ras-binding domain of RalGDS from human calculated from a limited set of NMR data, and the immunoglobulin binding domain from protein G from Streptococcus by their corresponding X-ray structures. In all test cases clearly improved structures were obtained. The largest danger in using data from other sources is a possible bias towards the added structure. In the worst case instead of a refined target structure the structure from the additional source is essentially reproduced. We could clearly show that the ISIC algorithm treats these difficulties properly.

Conclusion

In summary, we present a novel fully automated method to combine strongly coupled knowledge from different sources. The combination with validation tools such as the calculation of NMR R-factors strengthens the impact of the method considerably since the improvement of the structures can be assessed quantitatively. The ISIC method can be applied to a large number of similar problems where the quality of the obtained three-dimensional structures is limited by the available experimental data like the improvement of large NMR structures calculated from sparse experimental data or the refinement of low resolution X-ray structures. Also structures may be refined using other available structural information such as homology models.