Prediction of protein motions from amino acid sequence and its application to protein-protein interaction

BACKGROUND: Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA) can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information. RESULTS: In this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors. CONCLUSIONS: Finally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the predicted high internal motion regions and the observed conformational change regions

The development of an affinity evaluation and prediction system by using protein–protein docking simulations and parameter tuning

Koki Tsukamoto1, Tatsuya Yoshikawa1,2, Kiyonobu Yokota1, Yuichiro Hourai1, Kazuhiko Fukui11Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; 2Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Toyonaka, Osaka, JapanAbstract: A system was developed to evaluate and predict the interaction between protein pairs by using the widely used shape complementarity search method as the algorithm for docking simulations between the proteins. We used this system, which we call the affinity evaluation and prediction (AEP) system, to evaluate the interaction between 20 protein pairs. The system first executes a “round robin” shape complementarity search of the target protein group, and evaluates the interaction between the complex structures obtained by the search. These complex structures are selected by using a statistical procedure that we developed called ‘grouping’. At a prevalence of 5.0%, our AEP system predicted protein–protein interactions with a 50.0% recall, 55.6% precision, 95.5% accuracy, and an F-measure of 0.526. By optimizing the grouping process, our AEP system successfully predicted 10 protein pairs (among 20 pairs) that were biologically relevant combinations. Our ultimate goal is to construct an affinity database that will provide cell biologists and drug designers with crucial information obtained using our AEP system.Keywords: protein–protein interaction, affinity analysis, protein–protein docking, FFT, massive parallel computin

A Second Lysine-Specific Serine Protease from Lysobacter sp. Strain IB-9374

A second lysyl endopeptidase gene (lepB) was found immediately upstream of the previously isolated lepA gene encoding a highly active lysyl endopeptidase in Lysobacter genomic DNA. The lepB gene consists of 2,034 nucleotides coding for a protein of 678 amino acids. Amino acid sequence alignment between the lepA and lepB gene products (LepA and LepB) revealed that the LepB precursor protein is composed of a prepeptide (20 amino acids [aa]), a propeptide (184 aa), a mature enzyme (274 aa), and a C-terminal extension peptide (200 aa). The mature enzyme region exhibited 72% sequence identity to its LepA counterpart and conserved all essential amino acids constituting the catalytic triad and the primary determining site for lysine specificity. The lepB gene encoding the propeptide and mature-enzyme portions was overexpressed in Escherichia coli, and the inclusion body produced generated active LepB through appropriate refolding and processing. The purified enzyme, a mature 274-aa lysine-specific endopeptidase, was less active and more sensitive to both temperature and denaturation with urea, guanidine hydrochloride, or sodium dodecyl sulfate than LepA. LepA-based modeling implies that LepB can fold into essentially the same three-dimensional structure as LepA by placing a peptide segment, composed of several inserted amino acids found only in LepB, outside the molecule and that the Tyr169 side chain occupies the site in which the indole ring of Trp169, a built-in modulator for unique peptidase functions of LepA, resides. The results suggest that LepB is an isozyme of LepA and probably has a tertiary structure quite similar to it

Evolutionary Relationship and Structural Characterization of the <i>EPF/EPFL</i> Gene Family

<div><p>EPF1-EPF2 and EPFL9/Stomagen act antagonistically in regulating leaf stomatal density. The aim of this study was to elucidate the evolutionary functional divergence of <i>EPF/EPFL</i> family genes. Phylogenetic analyses showed that <i>AtEPFL9</i>/<i>Stomagen</i>-like genes are conserved only in vascular plants and are closely related to <i>AtEPF1</i>/<i>EPF2</i>-like genes. Modeling showed that EPF/EPFL peptides share a common 3D structure that is constituted of a scaffold and loop. Molecular dynamics simulation suggested that AtEPF1/EPF2-like peptides form an additional disulfide bond in their loop regions and show greater flexibility in these regions than AtEPFL9/Stomagen-like peptides. This study uncovered the evolutionary relationship and the conformational divergence of proteins encoded by the <i>EPF/EPFL</i> family genes.</p></div