Geometry of proline-containing alpha-helices in proteins

Crystal structure analysis of proline-containing alpha-helices in proteins has been carried out. High resolution crystal structures were selected from the Protein Data Bank. Apart from the standard internal parameters, some parameters which are specifically related to the bend in the helix due to proline have been developed and analyzed. Finally the position and nature of these helices and their interactions with the rest of the protein have been analyzed.

Characterization of substrate UpA binding to RNase A--computer modelling and energetics approach.

In the past two decades RNase A has been the focus of diverse investigations in order to understand the nature of substrate binding and to know the mechanism of enzyme action. Although this system is reasonably well characterized from the view point of some of the binding sites, the details of interactions in the second base binding (B2) site is insufficient. Further, the nature of ligand-protein interaction is elucidated generally by studies on RNase A-substrate analog complexes (mainly with the help of X-ray crystallography). Hence, the details of interactions at atomic level arising due to substrates are inferred indirectly. In the present paper, the dinucleotide substrate UpA is fitted into the active site of RNase A Several possible substrate conformations are investigated and the binding modes have been selected based on Contact Criteria. Thus identified RNase A-UpA complexes are energy minimized in coordinate space and are analysed in terms of conformations, energetics and interactions. The best possible ligand conformations for binding to RNase A are identified by experimentally known interactions and by the energetics. Upon binding of UpA to RNase A the changes associated,with protein back bone, Side chains in general and at the binding sites in particular are described. Further, the detailed interactions between UpA and RNase A are characterized in terms of hydrogen bonds and energetics. An extensive study has helped in interpreting the diverse results obtained from a number of experiments and also in evaluating the extent of changes the protein and the substrate undergo in order to maximize their interactions.

DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins

Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight < 1.5 KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of similar to 0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

Beta-structure of polypeptides in non-aqueous solutions. I. Spectral characteristics of the polypeptide backbone

The optical rotatory features of the beta-structure of the polypeptides in non-aqueous solutions and films cast from these solutions have been investigated. The beta-structure of poly-S-benzyl-L-cysteine, poly-S-carbobenzoxy-L-cysteine and poly-S-benzyl-L-cysteine, poly-S-carbobenzoxy-L-cysteine and poly-O-carbo-bands of their films. The optical rotatory dispersion (ORD) and circular dichroism (CD) spectra of these polypeptides are found to be very similar in both film and solution. In solvents promoting the beta-structure, the polypeptides are characterized by CD troughs in the n-pi* transition region of the peptide chromophore. The ORD spectra are found to be positive in sign throughout the visible and accessible ultraviolet regions and are interpreted in terms of the possible existence of a relatively much larger positive pi-pi* CD bands as compared with the negative n-pi* band. The rotatory data obtained in the non-aqueous solution are compared with those obtained for other poly peptides in aqueous solutions, with respect to the type and extent of beta-structure present.

Beta-structure of polypeptides in non-aqueous solutions. II. Side-chain orientation

The specific side-chain orientations of the phenyl group in the polypeptides poly-S-benzyl-L-cysteine, poly-S-carbobenzoxy-L-cysteine and poly-O-carbobenzoxy-L-serine in the beta-structure have been studied by spectral measurements in solutions. All the three polypeptides exhibit aromatic CD bands, indicating the asymmetric placement of the side-chain phenyl rings when the polypeptide backbone takes up the antiparallel beta-structure. Supporting evidence for this is derived from n.m.r. spectra of the polypeptides, which show upfield shift of the phenyl protons due to the stacking of the aromatic rings. Molecular model building studies reveal the stacking of alternate phenyl groups along the polypeptide chain.

Systems biology of tuberculosis

Systems biology seeks to study biological systems as a whole, by adopting an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to various perturbations. In this article, we focus on the Indian efforts towards systems-level studies of Mycobacterium tuberculosis and its interaction with the host. Availability of a variety of genome-scale experimental data, providing first level `omics' descriptions of the pathogen, render it feasible to study it at a systems level. Various aspects of the pathogen, from metabolic pathways to protein-protein interaction networks have been modelled and simulated, while host-pathogen interactions have been studied experimentally using siRNA-based techniques. These studies have been useful in obtaining a global perspective of the pathogen and its interactions with the host in many ways. For example, significant insights have been gained about different aspects such as proteins essential for bacterial survival, proteins that are highly influential in the network, pathways that are highly connected, host factors responsible for maintaining the TB infection and key factors involved in autophagy and pathogenesis. A rational pipeline developed for drug target identification incorporating analyses of the interactome, reactome, genome, pocketome and the transcriptome is discussed. Finally, exploring host factors as drug targets and insights about the emergence of drug resistance are also discussed. (C) 2011 Elsevier Ltd. All rights reserved.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Mining large-scale response networks reveals `topmost activities' in Mycobacterium tuberculosis infection

Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.

A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis

Background: The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis. Results: The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration. Conclusions: The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Competing views on cancer

Despite intense research efforts that have provided enormous insight, cancer continues to be a poorly understood disease. There has been much debate over whether the cancerous state can be said to originate in a single cell or whether it is a reflection of aberrant behaviour on the part of a `society of cells'. This article presents, in the form of a debate conducted among the authors, three views of how the problem might be addressed. We do not claim that the views exhaust all possibilities. These views are (a) the tissue organization field theory (TUFT) that is based on a breakdown of tissue organization involving many cells from different embryological layers, (b) the cancer stem cell (CSC) hypothesis that focuses on genetic and epigenetic changes that take place within single cells, and (c) the proposition that rewiring of the cell's protein interaction networks mediated by intrinsically disordered proteins (IDPs) drives the tumorigenic process. The views are based on different philosophical approaches. In detail, they differ on some points and agree on others. It is left to the reader to decide whether one approach to understanding cancer appears more promising than the other.

CINCINNATA in Antirrhinum majus directly modulates genes involved in cytokinin and auxin signaling

Mutations in the CINCINNATA (CIN) gene in Antirrhinum majus and its orthologs in Arabidopsis result in crinkly leaves as a result of excess growth towards the leaf margin. CIN homologs code for TCP (TEOSINTE-BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTOR 1 AND 2) transcription factors and are expressed in a broad zone in a growing leaf distal to the proliferation zone where they accelerate cell maturation. Although a few TCP targets are known, the functional basis of CIN-mediated leaf morphogenesis remains unclear. We compared the global transcription profiles of wild-type and the cin mutant of A. majus to identify the targets of CIN. We cloned and studied the direct targets using RNA in situ hybridization, DNA-protein interaction, chromatin immunoprecipitation and reporter gene analysis. Many of the genes involved in the auxin and cytokinin signaling pathways showed altered expression in the cin mutant. Further, we showed that CIN binds to genomic regions and directly promotes the transcription of a cytokinin receptor homolog HISTIDINE KINASE 4 (AmHK4) and an IAA3/SHY2 (INDOLE-3-ACETIC ACID INDUCIBLE 3/SHORT HYPOCOTYL 2) homolog in A. majus. Our results suggest that CIN limits excess cell proliferation and maintains the flatness of the leaf surface by directly modulating the hormone pathways involved in patterning cell proliferation and differentiation during leaf growth. 10.1111/(ISSN)1469-8137

Metallophosphoesterases: structural fidelity with functional promiscuity

Calcineurin-like metallophosphoesterases (MPEs) form a large superfamily of binuclear metal-ion-centre-containing enzymes that hydrolyse phosphomono-, phosphodi-or phosphotri-esters in a metal-dependent manner. The MPE domain is found in Mre11/SbcD DNA-repair enzymes, mammalian phosphoprotein phosphatases, acid sphingomyelinases, purple acid phosphatases, nucleotidases and bacterial cyclic nucleotide phosphodiesterases. Despite this functional diversity, MPEs show a remarkably similar structural fold and active-site architecture. In the present review, we summarize the available structural, biochemical and functional information on these proteins. We also describe how diversification and specialization of the core MPE fold in various MPEs is achieved by amino acid substitution in their active sites, metal ions and regulatory effects of accessory domains. Finally, we discuss emerging roles of these proteins as non-catalytic protein-interaction scaffolds. Thus we view the MPE superfamily as a set of proteins with a highly conserved structural core that allows embellishment to result in dramatic and niche-specific diversification of function.

Biosensor with Total Internal reflection Imaging Ellipsometry

In order to monitor multiple protein reaction processes simultaneously, a biosensor based on imaging ellipsometry operated in the total internal reflection mode is proposed. It could be realised as an automatic analysis for protein interaction processes with real-time label-free method. Its principle and methodology as well as a demonstration for its applications are presented.

Development Of Biosensor Based On Imaging Ellipsometry

The concept of biosensor based on imaging ellipsometry was proposed ten years ago. Its principle and the methodology as well as some solutions to problems which have to be faced during the development are mentioned. Its properties of phase sensitive, high throughput and fast sampling, as well as label-free, sensitivity better than 1 ng/ml for Immunoglobulin G, and real-time analysis for protein interaction process, etc. provide a potential for applications in biomedicine field. The recent biosensing development with total internal reflection imaging ellipsometry is presented also. [GRAPHICS] An example of 48 protein arrays in matrix. (C) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.