Structure and orientation of antibiotic peptide alamethicin in phospholipid bilayers as revealed by chemical shift oscillation analysis of solid state nuclear magnetic resonance and molecular dynamics simulation.

The structure, topology and orientation of membrane-bound antibiotic alamethicin were studied using solid state nuclear magnetic resonance (NMR) spectroscopy. (13)C chemical shift interaction was observed in [1-(13)C]-labeled alamethicin. The isotropic chemical shift values indicated that alamethicin forms a helical structure in the entire region. The chemical shift anisotropy of the carbonyl carbon of isotopically labeled alamethicin was also analyzed with the assumption that alamethicin molecules rotate rapidly about the bilayer normal of the phospholipid bilayers. It is considered that the adjacent peptide planes form an angle of 100° or 120° when it forms α-helix or 310-helix, respectively. These properties lead to an oscillation of the chemical shift anisotropy with respect to the phase angle of the peptide plane. Anisotropic data were acquired for the 4 and 7 sites of the N- and C-termini, respectively. The results indicated that the helical axes for the N- and C-termini were tilted 17° and 32° to the bilayer normal, respectively. The chemical shift oscillation curves indicate that the N- and C-termini form the α-helix and 310-helix, respectively. The C-terminal 310-helix of alamethicin in the bilayer was experimentally observed and the unique bending structure of alamethicin was further confirmed by measuring the internuclear distances of [1-(13)C] and [(15)N] doubly-labeled alamethicin. Molecular dynamics simulation of alamethicin embedded into dimyristoyl phophatidylcholine (DMPC) bilayers indicates that the helical axes for α-helical N- and 310-helical C-termini are tilted 12° and 32° to the bilayer normal, respectively, which is in good agreement with the solid state NMR results.

EzCatDB: the enzyme reaction database, 2015 update.

The EzCatDB database (http://ezcatdb.cbrc.jp/EzCatDB/) has emphasized manual classification of enzyme reactions from the viewpoints of enzyme active-site structures and their catalytic mechanisms based on literature information, amino acid sequences of enzymes (UniProtKB) and the corresponding tertiary structures from the Protein Data Bank (PDB). Reaction types such as hydrolysis, transfer, addition, elimination, isomerization, hydride transfer and electron transfer have been included in the reaction classification, RLCP. This database includes information related to ligand molecules on the enzyme structures in the PDB data, classified in terms of cofactors, substrates, products and intermediates, which are also necessary to elucidate the catalytic mechanisms. Recently, the database system was updated. The 3D structures of active sites for each PDB entry can be viewed using Jmol or Rasmol software. Moreover, sequence search systems of two types were developed for the EzCatDB database: EzCat-BLAST and EzCat-FORTE. EzCat-BLAST is suitable for quick searches, adopting the BLAST algorithm, whereas EzCat-FORTE is more suitable for detecting remote homologues, adopting the algorithm for FORTE protein structure prediction software. Another system, EzMetAct, is also available to searching for major active-site structures in EzCatDB, for which PDB-formatted queries can be searched.

Pro-inflammatory/Th1 gene expression shift in high glucose stimulated mesangial cells and tubular epithelial cells.

Diabetic nephropathy (DN) is a major cause of end stage kidney disease and a strong risk factor for cardiovascular diseases. Growing data show chronic inflammation plays an important role for the progression of DN. As for the immune cells, anti-inflammatory leukocytes as well as pro-inflammatory leukocytes play an important role in DN. In addition to leukocytes, renal resident cells contribute to the inflammatory process of DN. However, precise functions, phenotypes and immune balance of renal resident cells remain to be explored. Therefore, we hypothesized that the aberrant immune balance of renal resident cells contributes to the pathogenesis of DN. To explore this possibility, we performed genome-wide transcriptome profiling in mesangial cells and tubular epithelial cells (TECs), which were stimulated by high glucose (HG) and detected the expression of inflammation associated genes. HG increased the mRNA expression of oxidative stress, inflammasome and mammalian target of rapamycin (mTOR) related genes in mesangial cells. Pro-inflammatory/Th1 gene expression was upregulated, but Th2 related gene expression was downregulated in mesangial cells. In TECs, HG stimulation increased pro-inflammatory/Th1/Th2 gene expression. Phosphorylation of signaling proteins shifted towards pro-inflammatory phenotype with suppressed phosphorylation of Th2 related signaling in TECs. The data taken together indicate that HG shifts the immune balance toward pro-inflammatory/Th1 phenotype in mesangial cells and TECs, which might initiate and/or prolong inflammation, thereby resulting in diabetic nephropathy.

Evolutionary relationship and structural characterization of the EPF/EPFL gene family.

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 EPF/EPFL family genes. Phylogenetic analyses showed that AtEPFL9/Stomagen-like genes are conserved only in vascular plants and are closely related to AtEPF1/EPF2-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 EPF/EPFL family genes.

Statistical analysis of features associated with protein expression/solubility in an in vivo Escherichia coli expression system and a wheat germ cell-free expression system.

Recombinant protein technology is an important tool in many industrial and pharmacological applications. Although the success rate of obtaining soluble proteins is relatively low, knowledge of protein expression/solubility under 'standard' conditions may increase the efficiency and reduce the cost of proteomics studies. In this study, we conducted a genome-scale experiment to assess the overexpression and the solubility of human full-length cDNA in an in vivo Escherichia coli expression system and a wheat germ cell-free expression system. We evaluated the influences of sequence and structural features on protein expression/solubility in each system and estimated a minimal set of features associated with them. A comparison of the feature sets related to protein expression/solubility in the in vivo Escherichia coli expression system revealed that the structural information was strongly associated with protein expression, rather than protein solubility. Moreover, a significant difference was found in the number of features associated with protein solubility in the two expression systems.

Development and evaluation of data-driven designed tags (DDTs) for controlling protein solubility.

Production of proteins is an important issue in protein science and pharmaceutical studies. Numerous protein expression systems using living cells and cell-free methods have been developed to date. In these systems, a promising strategy for improving the success rate of obtaining soluble proteins is the attachment of various tags into target proteins based on empirical rules. This paper presents a method for the production of data-driven designed tags (DDTs) based on highly frequent sequence property patterns in an experimentally assessed protein solubility dataset in a wheat germ cell-free system. We constructed seven proteins combined with 12 kinds of DDTs (six for enhancing solubility and six for insolubility) at the N-terminal region as tags. Then we investigated their behavior using SDS-PAGE. Results show that three and four proteins respectively showed a trend toward solubilization and insolubilization, which indicates the possibility that the theoretically designed sequence can control protein solubility.

Understanding the recognition mechanism of protein-RNA complexes using energy based approach.

Protein-RNA interactions perform diverse functions within the cell. Understanding the recognition mechanism of protein-RNA complexes is a challenging task in molecular and computational biology. In this work, we have developed an energy based approach for identifying the binding sites and important residues for binding in protein-RNA complexes. The new approach considers the repulsive interactions as well as the effect of distance between the atoms in protein and RNA in terms of interaction energy, which are not considered in traditional distance based methods to identify the binding sites. We found that the positively charged, polar and aromatic residues are important for binding. These residues influence to form electrostatic, hydrogen bonding and stacking interactions. Our observation has been verified with the experimental binding specificity of protein-RNA complexes and found good agreement with experiments. Further, the propensities of residues/nucleotides in the binding sites of proteins/RNA and their atomic contributions have been derived. Based on these results we have proposed a novel mechanism for the recognition of protein-RNA complexes: the charged and polar residues in proteins initiate recognition with RNA by making electrostatic and hydrogen bonding interactions between them; the aromatic side chains tend to form aromatic-aromatic interactions and the hydrophobic residues aid to stabilize the complex.

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.

Sequence and structural analysis of binding site residues in protein-protein complexes.

The binding sites in protein-protein complexes have been identified with different methods including atomic contacts, reduction in solvent accessibility and interaction energy between the interacting partners. In our earlier work, we have developed an energy-based criteria for identifying the binding sites in protein-protein complexes, which showed that the interacting residues are different from that obtained with distance-based methods. In this work, we analyzed the binding site residues based on sequence and structural properties, such as, neighboring residues, secondary structure, solvent accessibility, conservation of residues, medium and long-range contacts and surrounding hydrophobicity. Our results showed that the neighboring residues of binding sites in proteins and ligands are different from each other although the interacting pairs of residues have a common behavior. The analysis on surrounding hydrophobicity reveals that the binding residues are less hydrophobic than non-binding sites, which suggests that the hydrophobic core are important for folding and stability whereas the surface seeking residues play a critical role in binding. This tendency has been verified with the number of contacts in binding sites. In addition, the binding site residues are highly conserved compared with non-binding residues. We suggest that the incorporation of sequence and structure-based features may improve the prediction accuracy of binding sites in protein-protein complexes.

Energy based approach for understanding the recognition mechanism in protein-protein complexes.

Protein-protein interactions play an essential role in the regulation of various cellular processes. Understanding the recognition mechanism of protein-protein complexes is a challenging task in molecular and computational biology. In this work, we have developed an energy based approach for identifying the binding sites and important residues for binding in protein-protein complexes. The new approach is different from the traditional distance based contacts in which the repulsive interactions are treated as binding sites as well as the contacts within a specific cutoff have been treated in the same way. We found that the residues and residue-pairs with charged and aromatic side chains are important for binding. These residues influence to form cation-, electrostatic and aromatic interactions. Our observation has been verified with the experimental binding specificity of protein-protein complexes and found good agreement with experiments. Based on these results we have proposed a novel mechanism for the recognition of protein-protein complexes: the charged and aromatic residues in receptor and ligand initiate recognition by making suitable interactions between them; the neighboring hydrophobic residues assist the stability of complex along with other hydrogen bonding partners by the polar residues. Further, the propensity of residues in the binding sites of receptors and ligands, atomic contributions and the influence on secondary structure will be discussed.

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

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.

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.

Mutational effects on O(6)-methylguanine-DNA methyltransferase from hyperthermophile: contribution of ion-pair network to protein thermostability.

Ion pairs have been considered to be general stabilizing factors in hyperthermophilic proteins, but the present experimental data cannot fully explain how ion pairs and ion-pair networks contribute to the stability. In this paper, we show experimental evidence that not all of the internal ion pairs contribute to the thermal and thermodynamic stability, using O(6)-methylguanine-DNA methyltransferase from Thermococcus kodakaraensis KOD1 (Tk-MGMT) as a model protein. Of three mutants in which an inter-helical ion pair was disrupted, only one mutant (E93A) was shown to be destabilized. Delta G of E93A was lower by approximately 4 kJ mol(-1) than that of the wild type, and E93A unfolded one order of magnitude faster than did the wild type and other variants. Glu 93 has unique properties in forming an ion-pair network that bridges the N- and C-terminal domains and connects three helices in the protein interior.

Electrostatic role of aromatic ring stacking in the pH-sensitive modulation of a chymotrypsin-type serine protease, Achromobacter protease I.

Achromobacter protease I (API) has a unique region of aromatic ring stacking with Trp169-His210 in close proximity to the catalytic triad. This paper reveals the electrostatic role of aromatic stacking in the shift in optimum pH to the alkaline region, which is the highest pH range (8.5-10) among chymotrypsin-type serine proteases. The pH-activity profile of API showed a sigmoidal distribution that appears at pH 8-10, with a shoulder at pH 6-8. Variants with smaller amino acid residues substituted for Trp169 had lower pH optima on the acidic side by 0-0.9 units. On the other hand, replacement of His210 by Ala or Ser lowered the acidic rim by 1.9 pH units, which is essentially identical to that of chymotrypsin and trypsin. Energy minimization for the mutant structures suggested that the side-chain of Trp169 stacked with His210 was responsible for isolation of the electrostatic interaction between His210 and the catalytic Asp113 from solvent. The aromatic stacking regulates the low activity at neutral pH and the high activity at alkaline pH due to the interference of the hydrogen bonded network in the catalytic triad residues.