Supplementary data are available at Bioinformatics online.

Summary: Protein disorder is characterized by a lack of a stable 3D structure, and is considered to be involved in a number of important protein functions such as regulatory and signalling events. We developed a web application, the POODLE-S, which predicts the disordered region from amino acid sequences by using physicochemical features and reduced amino acid set of a position-specific scoring matrix. Availability: POODLE-S is available from http://mbs.cbrc.jp/poodle/ poodle-s.html and can be used by both academic and commercial users.

Polyelectrolyte multilayer thin films were prepared by an alternate deposition of poly(allylamine hydrochloride) (PAH) and anionic polysaccharides {carboxymethylcellulose (CMC) and alginic acid (AGA)} on the surface of a gold (Au) disk electrode, and the binding of ferricyanide [Fe(CN)(6)](3)(-) and hexaammine ruthenium ions [Ru(NH(3))(6)](3+) to the films was evaluated. Poly(acrylic acid) (PAA) was also employed as a reference polyanion bearing carboxylate side chains. A quartz-crystal microbalance study showed that PAH-CMC and PAH-AGA multilayer films grow exponentially as the number of depositions increases. The thicknesses of five bilayers of (PAH-CMC)(5) and (PAH-AGA)(5) films were estimated to be 150 +/- 20 and 90 +/- 15 nm, respectively, in the dry state. The PAH/polysaccharide multilayer film-coated Au electrodes exhibited a redox response to the [Fe(CN)(6)](3)(-) ion dissolved in solution, irrespective of the sign of the surface charge of the film, suggesting the high permeability of the films to the [Fe(CN)(6)](3)(-) ion. In contrast, the PAH-PAA film-coated Au electrodes exhibited a redox response only when the outermost surface of the film was covered with a positively charged PAH layer. However, the permeation of the [Ru(NH(3))(6)](3+) cation was severely suppressed for all of the multilayer films. It was possible to confine the [Fe(CN)(6)](3)(-) ion in the films by immersing the film-coated electrodes in a 1 mM [Fe(CN)(6)](3)(-) solution for 15 min. Thus, the [Fe(CN)(6)](3)(-)-confined electrodes exhibited a cyclic voltammetric response in the [Fe(CN)(6)](3)(-) ion-free buffer solution. The loading of the [Fe(CN)(6)](3)(-) ion in the films was higher when the surface charge of the film was positive and increased with increasing film thickness. It was also found that the [Fe(CN)(6)](3)(-) ion confined in the films serves as an electrocatalyst that oxidizes ascorbic acid in solution.

Background: Predicting intrinsically disordered proteins is important in structural biology because they are thought to carry out various cellular functions even though they have no stable three-dimensional structure. We know the structures of far more ordered proteins than disordered proteins. The structural distribution of proteins in nature can therefore be inferred to differ from that of proteins whose structures have been determined experimentally. We know many more protein sequences than we do protein structures, and many of the known sequences can be expected to be those of disordered proteins. Thus it would be efficient to use the information of structure-unknown proteins in order to avoid training data sparseness. We propose a novel method for predicting which proteins are mostly disordered by using spectral graph transducer and training with a huge amount of structure-unknown sequences as well as structure-known sequences.

BackgroundMolecular recognition features (MoRFs) are short binding regions located in longer intrinsically disordered protein regions. Although these short regions lack a stable structure in the natural state, they readily undergo disorder-to-order transitions upon binding to their partner molecules. MoRFs play critical roles in the molecular interaction network of a cell, and are associated with many human genetic diseases. Therefore, identification of MoRFs is an important step in understanding functional aspects of these proteins and in finding applications in drug design.ResultsHere, we propose a novel method for identifying MoRFs, named as MFSPSSMpred (Masked, Filtered and Smoothed Position-Specific Scoring Matrix-based Predictor). Firstly, a masking method is used to calculate the average local conservation scores of residues within a masking-window length in the position-specific scoring matrix (PSSM). Then, the scores below the average are filtered out. Finally, a smoothing method is used to incorporate the features of flanking regions for each residue to prepare the feature sets for prediction. Our method employs no predicted results from other classifiers as input, i.e., all features used in this method are extracted from the PSSM of sequence only. Experimental results show that, comparing with other methods tested on the same datasets, our method achieves the best performance: achieving 0.004~0.079 higher AUC than other methods when tested on TEST419, and achieving 0.045~0.212 higher AUC than other methods when tested on TEST2012. In addition, when tested on an independent membrane proteins-related dataset, MFSPSSMpred significantly outperformed the existing predictor MoRFpred.ConclusionsThis study suggests that: 1) amino acid composition and physicochemical properties in the flanking regions of MoRFs are very different from those in the general non-MoRF regions; 2) MoRFs contain both highly conserved residues and highly variable residues and, on the whole, are highly locally conserved; and 3) combining contextual information with local conservation information of residues facilitates the prediction of MoRFs.

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). Started at the Real World Computing Partnership (RWCP) in August 1997, it developed to the present system of PDB-REPRDB. In April 2001, the system was moved to the Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) (http://www.cbrc.jp/); it is available at http://www.cbrc.jp/pdbreprdb/. The current database includes 33 368 protein chains from 16 682 PDB entries (1 September, 2002), from which are excluded (a) DNA and RNA data, (b) theoretically modeled data, (c) short chains (1<40 residues), or (d) data with non-standard amino acid residues at all residues. The number of entries including membrane protein structures in the PDB has increased rapidly with determination of numbers of membrane protein structures because of improved X-ray crystallography, NMR, and electron microscopic experimental techniques. Since many protein structure studies must address globular and membrane proteins separately, this new elimination factor, which excludes membrane protein chains, is introduced in the PDB-REPRDB system. Moreover, the PDB-REPRDB system for membrane protein chains begins at the same URL. The current membrane database includes 551 protein chains, including membrane domains in the SCOP database of release 1.59 (15 May, 2002).

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). The previous version of PDB-REPRDB provided 48 representative sets, whose similarity criteria were predetermined, on the WWW. The current version is designed so that the user may obtain a quick selection of representative chains from PDB. The selection of representative chains can be dynamically configured according to the user's requirement. The WWW interface provides a large degree of freedom in setting parameters, such as cut-off scores of sequence and structural similarity. One can obtain a representative list and classification data of protein chains from the system. The current database includes 20 457 protein chains from PDB entries (August 6, 2000). The system for PDB-REPRDB is available at the Parallel Protein Information Analysis system (PAPIA) WWW server (http://www.rwcp.or.jp/papia/).

No abstract