Oleanolic acid and ursolic acid affect peptidoglycan metabolism in <Emphasis Type="Italic">Listeria monocytogenes</Emphasis>

The plant pentacyclic triterpenoids, oleanolic and ursolic acids, inhibit the growth and survival of many bacteria, particularly Gram-positive species, including pathogenic ones. The effect of these compounds on the facultative human pathogen Listeria monocytogenes was examined. Both acids affected cell morphology and enhanced autolysis of the bacterial cells. Autolysis of isolated cell walls was inhibited by oleanolic acid, but the inhibitory activity of ursolic acid was less pronounced. Both compounds inhibited peptidoglycan turnover and quantitatively affected the profile of muropeptides obtained after digestion of peptidoglycan with mutanolysin. These results suggest that peptidoglycan metabolism is a cellular target of oleanolic and ursolic acids.     

Biosynthesis of salvinorin A proceeds via the deoxyxylulose phosphate pathway

Salvinorin A, a neoclerodane diterpenoid, isolated from the Mexican hallucinogenic plant Salvia divinorum, is a potent kappa-opioid receptor agonist. Its biosynthetic route was studied by NMR and HR-ESI-MS analysis of the products of the incorporation of [1-(13)C]-glucose, [Me-(13)C]-methionine, and [1-(13)C;3,4-(2)H2]-1-deoxy-D-xylulose into its structure. While the use of cuttings and direct-stem injection were unsuccessful, incorporation of (13)C into salvinorin A was achieved using in vitro sterile culture of microshoots. NMR spectroscopic analysis of salvinorin A (2.7 mg) isolated from 200 microshoots grown in the presence of [1-(13)C]-glucose established that this pharmacologically important diterpene is biosynthesized via the 1-deoxy-D-xylulose-5-phosphate pathway, instead of the classic mevalonic acid pathway. This was confirmed further in plants grown in the presence of [1-(13)C;3,4-(2)H2]-1-deoxy-D-xylulose. In addition, analysis of salvinorin A produced by plants grown in the presence of [Me-(13)C]-methionine indicates that methylation of the C-4 carboxyl group is catalyzed by a type III S-adenosyl-L-methionine-dependent O-methyltransferase.     

Regulatory role of cathepsin D in apoptosis

Cathepsin D (CTSD, EC 3.4.23.5) is well known aspartyl protease. Among different role in cell physiology, a new function of this enzyme is examined. Cathepsin D is an important regulator of apoptotic pathways in cells. It acts at different stage of intrinsic and extrinsic pathway of apoptosis. Cathepsin D can either induce apoptosis in presence of cytotoxic factors, but in certain studies an inhibitory role in apoptosis was also reviewed. Detailed review of involvement of cathepsin D in cell apoptosis is a purpose of this paper.     

Toward rational protein crystallization: A Web server for the design of crystallizable protein variants

Growing well-diffracting crystals constitutes a serious bottleneck in structural biology. A recently proposed crystallization methodology for "stubborn crystallizers" is to engineer surface sequence variants designed to form intermolecular contacts that could support a crystal lattice. This approach relies on the concept of surface entropy reduction (SER), i.e., the replacement of clusters of flexible, solvent-exposed residues with residues with lower conformational entropy. This strategy minimizes the loss of conformational entropy upon crystallization and renders crystallization thermodynamically favorable. The method has been successfully used to crystallize more than 15 novel proteins, all stubborn crystallizers. But the choice of suitable sites for mutagenesis is not trivial. Herein, we announce a Web server, the surface entropy reduction prediction server (SERp server), designed to identify mutations that may facilitate crystallization. Suggested mutations are predicted based on an algorithm incorporating a conformational entropy profile, a secondary structure prediction, and sequence conservation. Minor considerations include the nature of flanking residues and gaps between mutation candidates. While designed to be used with default values, the server has many user-controlled parameters allowing for considerable flexibility. Within, we discuss (1) the methodology of the server, (2) how to interpret the results, and (3) factors that must be considered when selecting mutations. We also attempt to benchmark the server by comparing the server's predictions with successful SER structures. In most cases, the structure yielding mutations were easily identified by the SERp server. The server can be accessed at http://www.doe-mbi.ucla.edu/Services/SER.     

The minimum information required for reporting a molecular interaction experiment (MIMIx)

A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the experiment. Here we propose MIMIx, the minimum information required for reporting a molecular interaction experiment. Adherence to these reporting guidelines will result in publications of increased clarity and usefulness to the scientific community and will support the rapid, systematic capture of molecular interaction data in public databases, thereby improving access to valuable interaction data.     

The MiSink Plugin: Cytoscape as a graphical interface to the Database of Interacting Proteins

The MiSink Plugin converts Cytoscape, an open-source bioinformatics platform for network visualization, to a graphical interface for the database of interacting proteins (DIP: http://dip.doe-mbi.ucla.edu). Seamless integration is possible by providing bi-directional communication between Cytoscape and any Web site supplying data in XML or tab-delimited format. Availability: MiSink is freely available for download at http://dip.doe-mbi.ucla.edu/Software.cgi.     

PFRES: protein fold classification by using evolutionary information and predicted secondary structure

MOTIVATION: The number of protein families has been estimated to be as small as 1000. Recent study shows that the growth in discovery of novel structures that are deposited into PDB and the related rate of increase of SCOP categories are slowing down. This indicates that the protein structure space will be soon covered and thus we may be able to derive most of remaining structures by using the known folding patterns. Present tertiary structure prediction methods behave well when a homologous structure is predicted, but give poorer results when no homologous templates are available. At the same time, some proteins that share twilight-zone sequence identity can form similar folds. Therefore, determination of structural similarity without sequence similarity would be beneficial for prediction of tertiary structures. RESULTS: The proposed PFRES method for automated protein fold classification from low identity (<35%) sequences obtains 66.4% and 68.4% accuracy for two test sets, respectively. PFRES obtains 6.3-12.4% higher accuracy than the existing methods. The prediction accuracy of PFRES is shown to be statistically significantly better than the accuracy of competing methods. Our method adopts a carefully designed, ensemble-based classifier, and a novel, compact and custom-designed feature representation that includes nearly 90% less features than the representation of the most accurate competing method (36 versus 283). The proposed representation combines evolutionary information by using the PSI-BLAST profile-based composition vector and information extracted from the secondary structure predicted with PSI-PRED. AVAILABILITY: The method is freely available from the authors upon request.     

Prediction of protein secondary structure content for the twilight zone sequences

Secondary protein structure carries information about local structural arrangements, which include three major conformations: alpha-helices, beta-strands, and coils. Significant majority of successful methods for prediction of the secondary structure is based on multiple sequence alignment. However, multiple alignment fails to provide accurate results when a sequence comes from the twilight zone, that is, it is characterized by low (<30%) homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation, called PSSC-core. The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands for sequences from the twilight zone. The PSSC-core method was tested and compared with two other state-of-the-art prediction methods on a set of 2187 twilight zone sequences. The results indicate that our method provides better predictions for both helix and strand content. The PSSC-core is shown to provide statistically significantly better results when compared with the competing methods, reducing the prediction error by 5-7% for helix and 7-9% for strand content predictions. The proposed feature-based sequence representation uses a comprehensive set of physicochemical properties that are custom-designed for each of the helix and strand content predictions. It includes composition and composition moment vectors, frequency of tetra-peptides associated with helical and strand conformations, various property-based groups like exchange groups, chemical groups of the side chains and hydrophobic group, auto-correlations based on hydrophobicity, side-chain masses, hydropathy, and conformational patterns for beta-sheets. The PSSC-core method provides an alternative for predicting the secondary structure content that can be used to validate and constrain results of other structure prediction methods. At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure.