Enlarged FAMSBASE: protein 3D structure models of genome sequences for 41 species

Moyamoya disease-associated protein mysterin/RNF213 is a novel AAA+ ATPase, which dynamically changes its oligomeric state

Moyamoya disease is an idiopathic human cerebrovascular disorder that is characterized by progressive stenosis and abnormal collateral vessels. We recently identified mysterin/RNF213 as its first susceptibility gene, which encodes a 591-kDa protein containing enzymatically active P-loop ATPase and ubiquitin ligase domains and is involved in proper vascular development in zebrafish. Here we demonstrate that mysterin further contains two tandem AAA+ ATPase modules and forms huge ring-shaped oligomeric complex. AAA+ ATPases are known to generally mediate various biophysical and mechanical processes with the characteristic ring-shaped structure. Fluorescence correlation spectroscopy and biochemical evaluation suggested that mysterin dynamically changes its oligomeric forms through ATP/ADP binding and hydrolysis cycles. Thus, the moyamoya disease-associated gene product is a unique protein that functions as ubiquitin ligase and AAA+ ATPase, which possibly contributes to vascular development through mechanical processes in the cell.

Docking and scoring protein interactions: CAPRI 2009

Protein docking algorithms are assessed by evaluating blind predictions performed during 2007-2009 in Rounds 13-19 of the community-wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G-protein signal processing, and enzyme inhibition and function. One target involved protein-RNA interactions not previously considered in CAPRI, several others were hetero-oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web-servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high- and medium-accuracy models for two to six targets. Forty-one groups including four web-servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use.

HUMAN FAMSD-BASE: high quality protein structure model database for the human genome using the FAMSD homology modeling method

Almost all proteins express their biological functions through the structural conformation of their specific amino acid sequences. Therefore, acquiring the three-dimensional structures of proteins is very important to elucidate the role of a particular protein. We had built protein structure model databases, which is called RIKEN FAMSBASE (http://famshelp.gsc.riken.jp/famsbase/). The RIKEN FAMSBASE is a genome-wide protein structure model database that contains a large number of protein models from many organisms. The HUMAN FAMSBASE that is one part of the RIKEN FAMSBASE contains many protein models for human genes, which are significant in the pharmaceutical and medicinal fields. We have now implemented an update of the human protein modeling database consisting of 242918 constructed models against the number of 20743 human protein sequences with an improved modeling method called Full Automatic protein Modeling System Developed (FAMSD). The results of our benchmark test of the FAMSD method indicated that it has an excellent capability to pack amino acid side-chains with correct torsion angles in addition to the main-chain, while avoiding the formation of atom-atom collisions that are not found in experimental structures. This new protein structure model database for human genes, which is named HUMAN FAMSD-BASE, is open to the public as a component part of the RIKEN FAMSBASE at http://mammalia.gsc.riken.jp/human_famsd/. A significant improvement of the HUMAN FAMSD-BASE in comparison with the preceding HUMAN FAMSBASE was verified in the benchmark test of this paper. The HUMAN FAMSD-BASE will have an important impact on the progress of biological science.

The TDRD9-MIWI2 complex is essential for piRNA-mediated retrotransposon silencing in the mouse male germline

Host-defense mechanisms against transposable elements are critical to protect the genome information. Here we show that tudor-domain containing 9 (Tdrd9) is essential for silencing Line-1 retrotransposon in the mouse male germline. Tdrd9 encodes an ATPase/DExH-type helicase, and its mutation causes male sterility showing meiotic failure. In Tdrd9 mutants, Line-1 was highly activated and piwi-interacting small RNAs (piRNAs) corresponding to Line-1 were increased, suggesting that feedforward amplification operates in the mutant. In fetal testes, Tdrd9 mutation causes Line-1 desilencing and an aberrant piRNA profile in prospermatogonia, followed by cognate DNA demethylation. TDRD9 complexes with MIWI2 with distinct compartmentalization in processing bodies, and this TDRD9-MIWI2 localization is regulated by MILI and TDRD1 residing at intermitochondrial cement. Our results identify TDRD9 as a functional partner of MIWI2 and indicate that the tudor-piwi association is a conserved feature, while two separate axes, TDRD9-MIWI2 and TDRD1-MILI, cooperate nonredundantly in the piwi-small RNA pathway in the mouse male germline.

FINDSITE: a combined evolution/structure-based approach to protein function prediction

A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the approximately 50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein models are used.

[Trial to predict interactions between proteins and biomolecules based on their three-dimensional structures]

A vast amount of DNA sequence data, protein three-dimensional (3D) structure data, and RNA expression data have been produced by the efforts of genome sequencing, structural genomics, and omics projects, and we are at the stage where comprehensive views of cell activity and molecular mechanisms of life can be deduced. But in reality, we are inundated with massive amounts of data and are still in the process of finding ways to fully utilize the data. In this report, I would like to present our observations on the growth of protein 3D structure data and our effort to deduce the functions from the 3D structures. We found that the 3D structure of quite a high proportion of proteins derived from genome sequences can be now predicted and methods to predict the functions from 3D structures are in high demand. The methods we have developed can be used to predict some functions, namely RNA and ligand interfaces, based on those 3D structures and DNA sequences with relatively high accuracy. The methods enable predictions that are accurate enough to help with deducing the atomic structures of the complexes.

FAMS and FAMSBASE for protein structure

The computer program FAMS (Full Automatic Modeling System) performs homology modeling of protein structures by means of an algorithm consisting of database searches and simulated annealing. FAMS produces a model in which the torsion angles of the backbone and sidechains are highly accurate. The operations of the FAMS algorithm are fully automated, and, therefore, special knowledge, techniques or experience are not required in order to obtain a biologically worthwhile protein structure.

Evaluation of 3D-Jury on CASP7 models

BACKGROUND

3D-Jury, the structure prediction consensus method publicly available in the Meta Server http://meta.bioinfo.pl/, was evaluated using models gathered in the 7th round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers.

RESULTS

The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models.

CONCLUSION

The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature http://meta.bioinfo.pl/compare_your_model_example.pl available in the Meta Server.

Coverage of whole proteome by structural genomics observed through protein homology modeling database

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE ( http://daisy.nagahama-i-bio.ac.jp/Famsbase/ ), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics.

Microbial genomes have over 72% structure assignment by the threading algorithm PROSPECTOR_Q

The genome scale threading of five complete microbial genomes is revisited using our state-of-the-art threading algorithm, PROSPECTOR_Q. Considering that structure assignment to an ORF could be useful for predicting biochemical function as well as for analyzing pathways, it is important to assess the current status of genome scale threading. The fraction of ORFs to which we could assign protein structures with a reasonably good confidence level to each genome sequences is over 72%, which is significantly higher than earlier studies. Using the assigned structures, we have predicted the function of several ORFs through "single-function" template structures, obtained from an analysis of the relationship between protein fold and function. The fold distribution of the genomes and the effect of the number of homologous sequences on structure assignment are also discussed.

Protein informatics towards function identification

The study of structural genomics and structural proteomics has determined the tertiary structures of many hypothetical proteins, whose molecular functions could not be understood using conventional methods. In order to infer the geometrical location of the functional site, the biochemical function and the biological function of the hypothetical protein, much effort has been made in protein informatics. The importance of heterogeneous databases and various descriptors of amino acid sequences, tertiary structures and pathways on the proteome scale has been emphasised.