A correlation-coefficient method to predicting protein-structural classes from amino acid compositions.

A protein is usually classified into one of the following four structural classes: all alpha, all beta, (alpha + beta) and alpha/beta. In this paper, based on the maximum correlation-coefficient principle, a new formulation is proposed for predicting the structural class of a protein according to its amino acid composition. Calculations have been made for a development set of proteins from which the amino acid compositions for the standard structural classes were derived, and an independent set of proteins which are outside the development set. The former can test the self consistency of a method and the latter can test its extrapolating effectiveness. In both cases, the results showed that the new method gave a considerably higher rate of correct prediction than any of the previous methods, implying that a significant improvement has been achieved by implementing the maximum-correlation-coefficient principle in the new method.     

A weighting method for predicting protein structural class from amino acid composition.

A protein is generally classified into one of the following four structural classes: all alpha, all beta, alpha+beta and alpha/beta. In this paper, based on the weighting to the 20 constituent amino acids, a new method is proposed for predicting the structural class of a protein according to its amino acid composition. The 20 weighting parameters, which reflect the different properties of the 20 constituent amino acids, have been obtained from a training set of proteins through the linear-programming approach. The rate of correct prediction for a training set of proteins by means of the new method was 100%, whereas the highest rate of previous methods was 82.8%. Furthermore, the results showed that the more numerous training proteins, the more effective the new method.     

A novel method for predicting protein subcellular localization based on pseudo amino acid composition

In this paper, a novel approach, ELM-PCA, is introduced for the first time to predict protein subcellular localization. Firstly, Protein Samples are represented by the pseudo amino acid composition (PseAAC). Secondly, the principal component analysis (PCA) is employed to extract essential features. Finally, the Elman Recurrent Neural Network (RNN) is used as a classifier to identify the protein sequences. The results demonstrate that the proposed approach is effective and practical.     

Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication

The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions) and in structure (structural defects) trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a) sensitive to random errors and (b) restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.     

A fast ab-initio method for predicting miRNA precursors in genomes

miRNAs are small non coding RNA structures which play important roles in biological processes. Finding miRNA precursors in genomes is therefore an important task, where computational methods are required. The goal of these methods is to select potential pre-miRNAs which could be validated by experimental methods. With the new generation of sequencing techniques, it is important to have fast algorithms that are able to treat whole genomes in acceptable times. We developed an algorithm based on an original method where an approximation of miRNA hairpins are first searched, before reconstituting the pre-miRNA structure. The approximation step allows a substantial decrease in the number of possibilities and thus the time required for searching. Our method was tested on different genomic sequences, and was compared with CID-miRNA, miRPara and VMir. It gives in almost all cases better sensitivity and selectivity. It is faster than CID-miRNA, miRPara and VMir: it takes ≈ 30 s to process a 1 MB sequence, when VMir takes 30 min, miRPara takes 20 h and CID-miRNA takes 55 h. We present here a fast ab-initio algorithm for searching for pre-miRNA precursors in genomes, called miRNAFold. miRNAFold is available at http://EvryRNA.ibisc.univ-evry.fr/.     

Tumor suppressors: recessive mutations that lead to cancer

Several lines of evidence point to the involvement of recessive mutations in the predisposition to, and hence initiation of, cancer in vivo. Analyses of the genetic behavior of transformed cells suggest that at least one way to explain these events is to invoke loci which suppress the tumorous phenotype and which are inactivated by mutation. These suppressors are the subject of much speculation, but whether or not they are ultimately determined to be the regulators of differentiation antigens, growth factors, or proto-oncogenes, it is certain that the investigation of such loci will allow yet another glimpse at the inner mysteries of organismal development.     

A high-throughput screening method for amino acid dehydrogenase

A simple and rapid screening method for amino acid dehydrogenase (e.g., leucine dehydrogenase, LDH) has been developed. It relies on a competitive relationship between a non-fluorescent Cu(II)–calcein complex and amino acid (e.g., l-2-aminobutyric acid, l-ABA). When ABA was introduced to a Cu(II)–calcein solution, it bound with the Cu(II) ions and this released calcein from the complex, which was detected as strong fluorescence. The principle of this high-throughput screening method was validated by screening an LDH mutant library. Compared with other methods, this method provided much quicker l-ABA detection and screening for leucine dehydrogenase mutations.     

A search for amino acid substitutions that universally activate response regulators

Two-component regulatory systems, typically composed of a sensor kinase to detect a stimulus and a response regulator to execute a response, are widely used by microorganisms for signal transduction. Response regulators exhibit a high degree of structural similarity and undergo analogous activating conformational changes upon phosphorylation. The activity of particular response regulators can be increased by specific amino acid substitutions, which either prolong the lifetime or mimic key features of the phosphorylated state. We probed the universality of response regulator activation by amino acid substitution. Thirty-six mutations that activate 11 different response regulators were identified from the literature. To determine whether the activated phenotypes would be retained in the context of a different response regulator, we recreated 51 analogous amino acid substitutions at corresponding positions of CheY. About 55% of the tested substitutions completely or partially inactivated CheY, approximately 30% were phenotypically silent, and approximately 15% activated CheY. Three previously uncharacterized activated CheY mutants were found. The 94NS (and presumably 94NT) substitutions resulted in resistance to CheZ-mediated dephosphorylation. The 113AP substitution led to enhanced autophosphorylation and may increase the fraction of non-phosphorylated CheY molecules that populate the activated conformation. The locations of activating substitutions on the response regulator three-dimensional structure are generally consistent with current understanding of the activation mechanism. The best candidates for potentially universal activating substitutions of response regulators identified in this study were 13DK and 113AP.     

Efficient identification of amino acid types for fast protein backbone assignments

We describe a procedure that allows for very efficient identification of amino acid types in proteins by selective ¹⁵N-labeling. The usefulness of selective incorporation of ¹⁵N-labeled amino acids into proteins for the backbone assignment has been recognized for several years. However, widespread use of this method has been hindered by the need to purify each selectively labeled sample and by the relatively high cost of labeling with ¹⁵N-labeled amino acids. Here we demonstrate that purification of the selectively ¹⁵N-labeled samples is not necessary and that background-free HSQC spectra containing only the peaks of the overexpressed heterologous protein can be obtained in crude lysates from as little as 100 ml cultures, thus saving time and money. This method can be used for fast and automated backbone assignment of proteins.     

A method for detecting positive selection at single amino acid sites

A method was developed for detecting the selective force at single amino acid sites given a multiple alignment of protein-coding sequences. The phylogenetic tree was reconstructed using the number of synonymous substitutions. Then, the neutrality was tested for each codon site using the numbers of synonymous and nonsynonymous changes throughout the phylogenetic tree. Computer simulation showed that this method accurately estimated the numbers of synonymous and nonsynonymous substitutions per site, as long as the substitution number on each branch was relatively small. The false-positive rate for detecting the selective force was generally low. On the other hand, the true-positive rate for detecting the selective force depended on the parameter values. Within the range of parameter values used in the simulation, the true-positive rate increased as the strength of the selective force and the total branch length (namely the total number of synonymous substitutions per site) in the phylogenetic tree increased. In particular, with the relative rate of nonsynonymous substitutions to synonymous substitutions being 5.0, most of the positively selected codon sites were correctly detected when the total branch length in the phylogenetic tree was > or = 2.5. When this method was applied to the human leukocyte antigen (HLA) gene, which included antigen recognition sites (ARSs), positive selection was detected mainly on ARSs. This finding confirmed the effectiveness of the present method with actual data. Moreover, two amino acid sites were newly identified as positively selected in non-ARSs. The three-dimensional structure of the HLA molecule indicated that these sites might be involved in antigen recognition. Positively selected amino acid sites were also identified in the envelope protein of human immunodeficiency virus and the influenza virus hemagglutinin protein. This method may be helpful for predicting functions of amino acid sites in proteins, especially in the present situation, in which sequence data are accumulating at an enormous speed.     

A GC-MS method for determination of amino acid uptake by plants

In this study, we present a rapid, robust and sensitive method for quantification of plant amino acid uptake using universally (U) (¹³C, ¹⁵N)-labelled amino acids and gas chromatography-mass spectrometry (GC-MS). Amino acids were analysed as their tert -butyldimethylsilyl (tBDMS) derivatives and displayed detection limits in the range 10–100 fmol on column, depending on the amino acid. The technique allows for simultaneous detection and quantification of both unlabelled and isotopically labelled species of amino acids. This makes simple quantification of plant amino acid uptake from an isotopically labelled source possible. The analytical variation was low, concerning total amino acid concentrations (relative standard deviation, rsd , less than 5.3%) as well as enrichment of U-¹³C, ¹⁵N-labelled glycine (Gly), arginine (Arg) and glutamic acid (Glu) ( rsd <2.1%). An application of the GC-MS method was conducted on non-mycorrhizal Pinus sylvestris roots supplied with U-¹³C, ¹⁵N-labelled amino acids. Intact, labelled amino acids were traced in root extracts. This provided conclusive evidence of plant root uptake of intact amino acids. Uptake rates of the three amino acids Gly, Glu and Arg in the range 0.5–37.9 μmol g⁻¹ dry weight h⁻¹ were recorded. These rates are comparable with those recorded in earlier studies of amino acid uptake, using other methods, as well as uptake rates measured for nitrate and ammonium.     

Characterization of two distinct beta2-microglobulin unfolding intermediates that may lead to amyloid fibrils of different morphology

The self-assembly of beta(2)-microglobulin into fibrils leads to dialysis-related amyloidosis. pH-mediated partial unfolding is required for the formation of the amyloidogenic intermediate that then self-assembles into amyloid fibrils. Two partially folded intermediates of beta(2)-microglobulin have been identified experimentally and linked to the formation of fibrils of distinct morphology, yet it remains difficult to characterize these partially unfolded states at high resolution using experimental approaches. Consequently, we have performed molecular dynamics simulations at neutral and low pH to determine the structures of these partially unfolded amyloidogenic intermediates. In the low-pH simulations, we observed the formation of alpha-sheet structure, which was first proposed by Pauling and Corey. Multiple simulations were performed, and two distinct intermediate state ensembles were identified that may account for the different fibril morphologies. The predominant early unfolding intermediate was nativelike in structure, in agreement with previous NMR studies. The late unfolding intermediate was significantly disordered, but it maintained an extended elongated structure, with hydrophobic clusters and residual alpha-extended chain strands in specific regions of the sequence that map to amyloidogenic peptides. We propose that the formation of alpha-sheet facilitates self-assembly into partially unfolded prefibrillar amyloidogenic intermediates.     

Epitope mapping by a method that requires no amino acid sequence information.

A simple, rapid method of epitope mapping has been developed that avoids the often cumbersome requirement of obtaining amino acid sequence information. The protein antigen is digested with various concentrations of carboxypeptidase into a nearly continuous series of polypeptides of different molecular weights, all containing a common N-terminus. The peptides are separated by polyacrylamide gel electrophoresis and then transferred to nitrocellulose paper. After developing the blot with the antibody to be mapped, a nearly continuous stain is observed extending from the position of the intact antigen to the molecular weight of the smallest N-terminal fragment still containing the antibody's epitope. By noting the molecular weight where the stain terminates, the position of the epitope relative to the N-terminus can be determined. Using this methodology, and taking special precautions to inhibit all endoproteinases in the carboxypeptidase preparation, the previously mapped epitopes of six nonoverlapping antibodies to the erythrocyte anion transporter were confirmed.