Functional arginine-containing amino acid sequences in peptides and proteins

L-arginine is a source of nitrogen oxide and plays a great role in a number of other biochemical processes. Functions and prospects for practical application of five groups of arginine-containing amino acid sequences and synthetic polyarginine sequences are considered. The physiological characteristics of well-known arginine-containing peptides, such as RGD peptides, kyotorphin, and tuftsin, are described in detail. The English version of the paper: Russian Journal of Bioorganic Chemistry, 2008, vol. 34, no. 2; see also http://www.maik.ru     

Functional arginine-containing amino acid sequences in peptides and proteins

L-Arginine is a source of nitrogen oxide and plays a great role in a number of other biochemical processes. Functions and prospects for practical application of five groups of arginine-containing amino acid sequences and synthetic polyarginine sequences are considered. The physiological characteristics of well-known arginine-containing peptides, such as RGD containing, kyotorphin, and tuftsin, are described in detail.     

Phylogeny reconstruction for protein sequences based on amino acid properties

This paper presents an essentially new method used to construct phylogenetic trees from related amino acid sequences. The method is based on a new distance measure which describes sequence relationships by means of typical steric and physicochemical properties of the amino acids and is advantageous in some essential points. The method was applied to different sets of protein sequences and the results were compared with other well-established methods.     

Detection of proteins based on amino acid sequences by multiple aptamers against tripeptides

A number of different ligands have been tested in the course of the development of protein array technology. The most extensively studied example of protein ligands has been based on antibody-antigen interaction. Other examples include protein-protein, protein-nucleic acid, and protein-small molecule interactions. All these ligands can recognize and specifically bind to protein epitopes. In this study, we have developed a novel technology using DNA-based aptamers to detect proteins based on their amino acid sequences. Mouse cathepsin D was used for the proof of principle experiment. Four tripeptides, Leu-Ala-Ser, Asp-Gly-Ile, Gly-Glu-Leu, and Lys-Ala-Ile, were selected based on the published amino acid sequence of mouse cathepsin D. DNA aptamers against the tripeptides were isolated using the systematic evolution of ligands of exponential enrichment method. We have demonstrated that the aptamers specifically interacted with mouse cathepsin D using the structure-switch method. We further performed a proximity-dependent ligation assay to demonstrate that multiple aptamers could specifically detect the protein from cell extracts. In principle, one library containing 8000 aptamers should be enough to detect almost all proteins in the whole proteome in all organisms. This technology could be applied to generate a new generation of protein arrays.     

Evolution of EF-hand calcium-modulated proteins. I. Relationships based on amino acid sequences

Summary The relationships among 153 EF-hand (calcium-modulated) proteins of known amino acid sequence were determined using the method of maximum parsimony. These proteins can be ordered into 12 distinct subfamilies-calmodulin, troponin C, essential light chain of myosin, regulatory light chain, sarcoplasmic calcium binding protein, calpain, aequorin,Strongylocentrotus purpuratus ectodermal protein, calbindin 28 kd, parvalbumin, -actinin, and S100/intestinal calcium-binding protein. Eight individual proteins-calcineurin B fromBos, troponin C fromAstacus, calcium vector protein fromBranchiostoma, caltractin fromChlamydomonas, cell-division-cycle 31 gene product fromSaccharomyces, 10-kd calcium-binding protein fromTetrahymena, LPS1 eight-domain protein fromLytechinus, and calcium-binding protein fromStreptomyces—are tentatively identified as unique; that is, each may be the sole representative of another subfamily. We present dendrograms showing the relationships among the subfamilies and uniques as well as dendrograms showing relationships within each subfamily.The EF-hand proteins have been characterized from a broad range of organismal sources, and they have an enormous range of function. This is reflected in the complexity of the dendrograms. At this time we urge caution in assigning a simple scheme of gene duplications to account for the evolution of the 600 EF-hand domains of known sequence.     

Availability of short amino acid sequences in proteins

Much attention is being paid to protein databases as an important information source for proteome research. Although used extensively for similarity searches, protein databases themselves have not fully been characterized. In a systematic attempt to reveal protein-database characters that could contribute to revealing how protein chains are constructed, frequency distributions of all possible combinatorial sets of three, four, and five amino acids ("triplets," "quartets," and "pentats"; collectively called constituent sequences) have been examined in the nonredundant (nr) protein database, demonstrating the existence of nonrandom bias in their "availability" at the population level. Nonexistent short sequences of pentats were found that showed low availability in biological proteins against their expected probabilities of occurrence. Among them, six representative ones were successfully synthesized as peptides with reasonably high yields in a conventional Fmoc method, excluding the possibility that a putative physicochemical energy barrier in forming them could be a direct cause for the low availability. They were also expressed as soluble fusion proteins in a conventional Escherichia coli BL21Star(DE3) system with reasonably high yield, again excluding a possible difficulty in their biological synthesis. Together, these results suggest that information on three-dimensional structures and functions of proteins exists in the context of connections of short constituent sequences, and that proteins are composed of evolutionarily selected constituent sequences, which are reflected in their availability differences in the database. These results may have biological implications for protein structural studies.     

DomCut: prediction of inter-domain linker regions in amino acid sequences

DomCut is a program to predict inter-domain linker regions solely by amino acid sequence information. The prediction is made by using linker index deduced from a data set of domain/linker segments. The linker preference profile, which is the averaged linker index along a sequence, can be visualized in the graphical interface.     

Neisseria pili proteins: amino-terminal amino acid sequences and identification of an unusual amino acid.

The amino-terminal amino acid sequences of the pili proteins from four antigenically dissimilar strains of Neisseria gonorrhoeae, from Neisseria meningiditis, and from Escherichia coli were determined. Although antibodies raised to the pili protein from a given strain of gonococcus cross-reacted poorly or not at all with each of the other strains tested, the amino-terminal sequences were all identical. The meningococcal protein sequence was also identical with the gonococcal sequence through 29 residues, and this sequence was highly homologous to the sequence of the pili protein of Moraxella nonliquifaciens determined by other workers. However, the sequence of the pili protein from E. coli showed no similarity to the other sequences. The gonococcal and meningococcal proteins have an unusual amino acid at the amino termini, N-methylphenylalanine. In addition, the first 24 residues of these proteins have only two hydrophilic residues (at positions 2 and 5) with the rest being predominantly aliphatic hydrophobic amino acids. The preservation of this highly unusual sequence among five antigenically dissimilar Neisseria pili proteins implies a role for the amino-terminal structure in pilus function. The amino terminus may be directly or indirectly (through preservation of tertiary structure) important for the pilus function of facilitating attachment of bacteria to human cells.     

N-terminal N-myristoylation of proteins: prediction of substrate proteins from amino acid sequence

Myristoylation by the myristoyl-CoA:protein N-myristoyltransferase (NMT) is an important lipid anchor modification of eukaryotic and viral proteins. Automated prediction of N-terminal N-myristoylation from the substrate protein sequence alone is necessary for large-scale sequence annotation projects but it requires a low rate of false positive hits in addition to a sufficient sensitivity.Our previous analysis of substrate protein sequence variability, NMT sequences and 3D structures has revealed motif properties in addition to the known PROSITE motif that are utilized in a new predictor described here. The composite prediction function (with separate ad hoc parameterization (a) for queries from non-fungal eukaryotes and their viruses and (b) for sequences from fungal species) consists of terms evaluating amino acid type preferences at sequences positions close to the N terminus as well as terms penalizing deviations from the physical property pattern of amino acid side-chains encoded in multi-residue correlation within the motif sequence. The algorithm has been validated with a self-consistency and two jack-knife tests for the learning set as well as with kinetic data for model substrates. The sensitivity in recognizing documented NMT substrates is above 95 % for both taxon-specific versions. The corresponding rate of false positive prediction (for sequences with an N-terminal glycine residue) is close to 0.5 %; thus, the technique is applicable for large-scale automated sequence database annotation. The predictor is available as public WWW-server with the URL http://mendel.imp.univie.ac.at/myristate/. Additionally, we propose a version of the predictor that identifies a number of proteolytic protein processing sites at internal glycine residues and that evaluates possible N-terminal myristoylation of the protein fragments.A scan of public protein databases revealed new potential NMT targets for which the myristoyl modification may be of critical importance for biological function. Among others, the list includes kinases, phosphatases, proteasomal regulatory subunit 4, kinase interacting proteins KIP1/KIP2, protozoan flagellar proteins, homologues of mitochondrial translocase TOM40, of the neuronal calcium sensor NCS-1 and of the cytochrome c-type heme lyase CCHL. Analyses of complete eukaryote genomes indicate that about 0.5 % of all encoded proteins are apparent NMT substrates except for a higher fraction in Arabidopsis thaliana ( approximately 0.8 %).     

A neural network model for the prediction of membrane-spanning amino acid sequences

The architecture and weights of an artificial neural network model that predicts putative transmembrane sequences have been developed and optimized by the algorithm of structure evolution. The resulting filter is able to classify membrane/nonmembrane transition regions in sequences of integral human membrane proteins with high accuracy. Similar results have been obtained for both training and test set data, indicating that the network has focused on general features of transmembrane sequences rather than specializing on the training data. Seven physicochemical amino acid properties have been used for sequence encoding. The predictions are compared to hydrophobicity plots.     

AAIndexLoc: predicting subcellular localization of proteins based on a new representation of sequences using amino acid indices

Identifying a protein's subcellular localization is an important step to understand its function. However, the involved experimental work is usually laborious, time consuming and costly. Computational prediction hence becomes valuable to reduce the inefficiency. Here we provide a method to predict protein subcellular localization by using amino acid composition and physicochemical properties. The method concatenates the information extracted from a protein's N-terminal, middle and full sequence. Each part is represented by amino acid composition, weighted amino acid composition, five-level grouping composition and five-level dipeptide composition. We divided our dataset into training and testing set. The training set is used to determine the best performing amino acid index by using five-fold cross validation, whereas the testing set acts as the independent dataset to evaluate the performance of our model. With the novel representation method, we achieve an accuracy of approximately 75% on independent dataset. We conclude that this new representation indeed performs well and is able to extract the protein sequence information. We have developed a web server for predicting protein subcellular localization. The web server is available at http://aaindexloc.bii.a-star.edu.sg .     

Functional dissection of cdc37: characterization of domain structure and amino acid residues critical for protein kinase binding

Hsp90 and its co-chaperone Cdc37 facilitate the folding and activation of numerous protein kinases. In this report, we examine the structure-function relationships that regulate the interaction of Cdc37 with Hsp90 and with an Hsp90-dependent kinase, the heme-regulated eIF2alpha kinase (HRI). Limited proteolysis of native and recombinant Cdc37, in conjunction with MALDI-TOF mass spectrometry analysis of peptide fragments and peptide microsequencing, indicates that Cdc37 is comprised of three discrete domains. The N-terminal domain (residues 1-126) interacts with client HRI molecules. Cdc37's middle domain (residues 128-282) interacts with Hsp90, but does not bind to HRI. The C-terminal domain of Cdc37 (residues 283-378) does not bind Hsp90 or kinase, and no functions were ascribable to this domain. Functional assays did, however, suggest that residues S127-G163 of Cdc37 serve as an interdomain switch that modulates the ability of Cdc37 to sense Hsp90's conformation and thereby mediate Hsp90's regulation of Cdc37's kinase-binding activity. Additionally, scanning alanine mutagenesis identified four amino acid residues at the N-terminus of Cdc37 that are critical for high-affinity binding of Cdc37 to client HRI molecules. One mutation, Cdc37/W7A, also implicated this region as an interpreter of Hsp90's conformation. Results illuminate the specific Cdc37 motifs underlying the allosteric interactions that regulate binding of Hsp90-Cdc37 to immature kinase molecules.     

Neuro-fuzzy structural classification of proteins for improved protein secondary structure prediction

Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins.     

Functional classification of membrane transporters and channels based on filtered TM/non-TM amino acid composition

Membrane transporters catalyze the transport of small solute molecules across biological barriers such as lipid bilayer membranes. As the experimental annotation of which proteins transport which substrates is incomplete it is highly desirable to develop computational methods that can assist in the classification and substrate annotation of putative membrane transport proteins. Here, we determined the similarity of membrane transporter sequences annotated in the Transport Classification Database (Saier et al., Nucleic Acids Res 2006, 34, D181-D186) and Arabidopsis thaliana membrane transporters annotated in the database Aramemnon (Schwacke et al., Plant Physiol 2003, 131, 16-26). The similarity measure was based on the amino acid composition either considering the full sequences or separately in the transmembrane (TM) and external parts of the sequences. We considered four different substrate sets and three different subfamilies and tried to classify the given proteins into these classes. Family or substrate prediction based on the simple amino acid frequency had an average accuracy of 76%. The differentiation between TM and non-TM regions led to an improved accuracy of 80% on average.     

MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition

MOTIVATION: Functional annotation of unknown proteins is a major goal in proteomics. A key annotation is the prediction of a protein's subcellular localization. Numerous prediction techniques have been developed, typically focusing on a single underlying biological aspect or predicting a subset of all possible localizations. An important step is taken towards emulating the protein sorting process by capturing and bringing together biologically relevant information, and addressing the clear need to improve prediction accuracy and localization coverage. RESULTS: Here we present a novel SVM-based approach for predicting subcellular localization, which integrates N-terminal targeting sequences, amino acid composition and protein sequence motifs. We show how this approach improves the prediction based on N-terminal targeting sequences, by comparing our method TargetLoc against existing methods. Furthermore, MultiLoc performs considerably better than comparable methods predicting all major eukaryotic subcellular localizations, and shows better or comparable results to methods that are specialized on fewer localizations or for one organism. AVAILABILITY: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/