Mitsuo Iwadate

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Community‐wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community‐wide assessment of methods to predict the effects of mutations on protein–protein interactions. Twenty‐two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side‐chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large‐scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies. Proteins 2013; 81:1980–1987.

Structural analysis of silk with 13C NMR chemical shift contour plots.

The polymorphic structures of silk fibroins in the solid state were examined on the basis of a quantitative relationship between the 13C chemical shift and local structure in proteins. To determine this relationship, 13C chemical shift contour plots for C alpha and C beta carbons of Ala and Ser residues, and the C alpha chemical shift plot for Gly residues were prepared using atomic co-ordinates from the Protein Data Bank and 13C NMR chemical shift data in aqueous solution reported for 40 proteins. The 13C CP/MAS NMR chemical shifts of Ala, Ser and Gly residues of Bombyx mori silk fibroin in silk I and silk II forms were used along with 13C CP/MAS NMR chemical shifts of Ala residues of Samia cynthia ricini silk fibroin in beta-sheet and alpha-helix forms for the structure analyses of silk fibroins. The allowed regions in the 13C chemical shift contour plots for C alpha and C beta carbons of Ala and Ser residues for the structures in silk fibroins, i.e. Silk II, Silk I and alpha-helix, were determined using their 13C isotropic NMR chemical shifts in the solid state. There are two area of the phi,psi map which satisfy the observed Silk I chemical shift data for both the C alpha and C beta carbons of Ala and Ser residues in the 13C chemical shift contour plots.

TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer

BackgroundNon-small cell lung cancer (NSCLC) remains lethal despite the development of numerous drug therapy technologies. About 85% to 90% of lung cancers are NSCLC and the 5-year survival rate is at best still below 50%. Thus, it is important to find drugable target genes for NSCLC to develop an effective therapy for NSCLC.ResultsIntegrated analysis of publically available gene expression and promoter methylation patterns of two highly aggressive NSCLC cell lines generated by in vivo selection was performed. We selected eleven critical genes that may mediate metastasis using recently proposed principal component analysis based unsupervised feature extraction. The eleven selected genes were significantly related to cancer diagnosis. The tertiary protein structure of the selected genes was inferred by Full Automatic Modeling System, a profile-based protein structure inference software, to determine protein functions and to specify genes that could be potential drug targets.ConclusionsWe identified eleven potentially critical genes that may mediate NSCLC metastasis using bioinformatic analysis of publically available data sets. These genes are potential target genes for the therapy of NSCLC. Among the eleven genes, TINAGL1 and B3GALNT1 are possible candidates for drug compounds that inhibit their gene expression.

Genes associated with genotype-specific DNA methylation in squamous cell carcinoma as candidate drug targets

BackgroundAberrant DNA methylation is often associated with cancers. Thus, screening genes with cancer-associated aberrant DNA methylation is a useful method to identify candidate cancer-causing genes. Aberrant DNA methylation is also genotype dependent. Thus, the selection of genes with genotype-specific aberrant DNA methylation in cancers is potentially important for tailor-made medicine. The selected genes are important candidate drug targets.ResultsThe recently proposed principal component analysis based selection of genes with aberrant DNA methylation was applied to genotype and DNA methylation patterns in squamous cell carcinoma measured using single nucleotide polymorphism (SNP) arrays. SNPs that are frequently found in cancers are usually highly methylated, and the genes that were selected using this method were reported previously to be related to cancers. Thus, genes with genotype-specific DNA methylation patterns will be good therapeutic candidates. The tertiary structures of the proteins encoded by the selected genes were successfully inferred using two profile-based protein structure servers, FAMS and Phyre2. Candidate drugs for three of these proteins, tyrosine kinase receptor (ALK), EGLN3 protein, and NUAK family SNF1-like kinase 1 (NUAK1), were identified by ChooseLD.ConclusionsWe detected genes with genotype-specific DNA methylation in squamous cell carcinoma that are candidate drug targets. Using in silico drug discovery, we successfully identified several candidate drugs for the ALK, EGLN3 and NUAK1 genes that displayed genotype-specific DNA methylation.

Bioinformatic screening of autoimmune disease genes and protein structure prediction with FAMS for drug discovery.

Autoimmune diseases are often intractable because their causes are unknown. Identifying which genes contribute to these diseases may allow us to understand the pathogenesis, but it is difficult to determine which genes contribute to disease. Recently, epigenetic information has been considered to activate/deactivate disease-related genes. Thus, it may also be useful to study epigenetic information that differs between healthy controls and patients with autoimmune disease. Among several types of epigenetic information, promoter methylation is believed to be one of the most important factors. Here, we propose that principal component analysis is useful to identify specific gene promoters that are differently methylated between the normal healthy controls and patients with autoimmune disease. Full Automatic Modeling System (FAMS) was used to predict the three-dimensional structures of selected proteins and successfully inferred relatively confident structures. Several possibilities of the application to the drug discovery based on obtained structures are discussed.

Fams-ace: a combined method to select the best model after remodeling all server models.

During Critical Assessment of Protein Structure Prediction (CASP7, Pacific Grove, CA, 2006), fams‐ace was entered in the 3D coordinate prediction category as a human expert group. The procedure can be summarized by the following three steps. (1) All the server models were refined and rebuilt utilizing our homology modeling method. (2) Representative structures were selected from each server, according to a model quality evaluation, based on a 3D1D profile score (like Verify3D). (3) The top five models were selected and submitted in the order of the consensus‐based score (like 3D‐Jury). Fams‐ace is a fully automated server and does not require human intervention. In this article, we introduce the methodology of fams‐ace and discuss the successes and failures of this approach during CASP7. In addition, we discuss possible improvements for the next CASP. Proteins 2007.

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

Enlarged FAMSBASE is a relational database of comparative protein structure models for the whole genome of 41 species, presented in the GTOP database. The models are calculated by Full Automatic Modeling System (FAMS). Enlarged FAMSBASE provides a wide range of query keys, such as name of ORF (open reading frame), ORF keywords, Protein Data Bank (PDB) ID, PDB heterogen atoms and sequence similarity. Heterogen atoms in PDB include cofactors, ligands and other factors that interact with proteins, and are a good starting point for analyzing interactions between proteins and other molecules. The data may also work as a template for drug design. The present number of ORFs with protein 3D models in FAMSBASE is 183 805, and the database includes an average of three models for each ORF. FAMSBASE is available at http://famsbase.bio.nagoya-u.ac.jp/famsbase/.

Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease

BackgroundFeature extraction (FE) is difficult, particularly if there are more features than samples, as small sample numbers often result in biased outcomes or overfitting. Furthermore, multiple sample classes often complicate FE because evaluating performance, which is usual in supervised FE, is generally harder than the two-class problem. Developing sample classification independent unsupervised methods would solve many of these problems.ResultsTwo principal component analysis (PCA)-based FE, specifically, variational Bayes PCA (VBPCA) was extended to perform unsupervised FE, and together with conventional PCA (CPCA)-based unsupervised FE, were tested as sample classification independent unsupervised FE methods. VBPCA- and CPCA-based unsupervised FE both performed well when applied to simulated data, and a posttraumatic stress disorder (PTSD)-mediated heart disease data set that had multiple categorical class observations in mRNA/microRNA expression of stressed mouse heart. A critical set of PTSD miRNAs/mRNAs were identified that show aberrant expression between treatment and control samples, and significant, negative correlation with one another. Moreover, greater stability and biological feasibility than conventional supervised FE was also demonstrated. Based on the results obtained, in silico drug discovery was performed as translational validation of the methods.ConclusionsOur two proposed unsupervised FE methods (CPCA- and VBPCA-based) worked well on simulated data, and outperformed two conventional supervised FE methods on a real data set. Thus, these two methods have suggested equivalence for FE on categorical multiclass data sets, with potential translational utility for in silico drug discovery.

The SKE-DOCK server and human teams based on a combined method of shape complementarity and free energy estimation.

We participated in rounds 6–12 of the critical assessment of predicted interaction (CAPRI) contest as the SKE‐DOCK server and human teams. The SKE‐DOCK server is based on simple geometry docking and a knowledge base scoring function. The procedure is summarized in the following three steps: (1) protein docking according to shape complementarity, (2) evaluating complex models, and (3) repacking side‐chain of models. The SKE‐DOCK server did not make use of biological information. On the other hand, the human team tried various intervention approaches. In this article, we describe in detail the processes of the SKE‐DOCK server, together with results and reasons for success and failure. Good predicted models were obtained for target 25 by both the SKE‐DOCK server and human teams. When the modeled receptor proteins were superimposed on the experimental structures, the smallest Ligand‐rmsd values corresponding to the rmsd between the model and experimental structures were 3.307 and 3.324 Å, respectively. Moreover, the two teams obtained 4 and 2 acceptable models for target 25. The overall result for both the SKE‐DOCK server and human teams was medium accuracy for one (Target 25) out of nine targets. Proteins 2007.

Solid phase synthesis and biological activities of [Arg8]-vasopressin methylenedithioether

Solid phase synthesis of [Arg8]-vasopressin methylenedithioether, an analog of vasopressin which contains an extra methylene group between the two sulfur atoms of Cys1 and Cys6, is described. Methylene insertion occurred easily when the thiol free peptide on a solid support was treated with tetrabutylammonium fluoride in dichloromethane at room temperature for 3 h. The uterotonic in vitro, pressor, and antidiuretic activities of the compound were reduced in comparison to [Arg8]-vasopressin by one order of magnitude.