QHELIX: A Computational Tool for the Improved Measurement of Inter-Helical Angles in Proteins

Knowledge about the assembled structures of the secondary elements in proteins is essential to understanding protein folding and functionality. In particular, the analysis of helix geometry is required to study helix packing with the rest of the protein and formation of super secondary structures, such as, coiled coils and helix bundles, formed by packing of two or more helices. Here we present an improved computational method, QHELIX, for the calculation of the orientation angles between helices. Since a large number of helices are known to be in curved shapes, an appropriate definition of helical axes is a prerequisite for calculating the orientation angle between helices. The present method provides a quantitative measure on the irregularity of helical shape, resulting in discriminating irregular-shaped helices from helices with an ideal geometry in a large-scale analysis of helix geometry. It is also capable of straightforwardly assigning the direction of orientation angles in a consistent way. These improvements will find applications in finding a new insight on the assembly of protein secondary structure. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

pepgrep: A Tool for Peptide MS/MS Pattern Matching

Typically, detection of protein sequences in collision-induced dissociation (CID) tandem MS (MS2) dataset is performed by mapping identified peptide ions back to protein sequence by using the protein database search (PDS) engine. Finding a particular peptide sequence of interest in CID MS2 records very often requires manual evaluation of the spectrum, regardless of whether the peptide-associated MS2 scan is identified by PDS algorithm or not. We have developed a compact cross-platform database-free command-line utility, pepgrep, which helps to find an MS2 fingerprint for a selected peptide sequence by pattern-matching of modelled MS2 data using Peptide-to-MS2 scoring algorithm. pepgrep can incorporate dozens of mass offsets corresponding to a variety of post-translational modifications (PTMs) into the algorithm. Decoy peptide sequences are used with the tested peptide sequence to reduce false-positive results. The engine is capable of screening an MS2 data file at a high rate when using a cluster computing environment. The matched MS2 spectrum can be displayed by using built-in graphical application programming interface (API) or optionally recorded to file. Using this algorithm, we were able to find extra peptide sequences in studied CID spectra that were missed by PDS identification. Also we found pepgrep especially useful for examining a CID of small fractions of peptides resulting from, for example, affinity purification techniques. The peptide sequences in such samples are less likely to be positively identified by using routine protein-centric algorithm implemented in PDS. The software is freely available at http://bsproteomics.essex.ac.uk:8080/data/download/pepgrep-1.4.tgz.     

Interactions of lens proteins. Ultrafiltration is unsuitable to detect self- or mixed-association

Crystallins from calf lens were subjected to ultrafiltration through an Amicon XM-300 membrane to determine whether specific interactions between identical proteins (self-association) or different proteins (mixed-association) could be detected and quantified. Single crystallins at different concentrations, simple mixtures and total lens extracts were studied separately. alpha-Crystallin (Mr 800 000) is nearly fully retained (greater than 95%) by XM-300. Retention of beta-crystallins (Mr 50 000-200 000) is found to be much higher than expected from their molecular weights. Ultrafiltration of gamma-crystallin (Mr 20 000) solutions of 1.0-22.6 g/l shows that retention increases as a function of protein concentration. In solutions of single crystallins, self-association effects could not be separated from concentration polarization effects at the membrane surface. In mixtures of crystallins, mixed-association could not be separated from self-association, concentration polarization and excluded volume effects on self-association.     

Local Perturbation Analysis: A Computational Tool for Biophysical Reaction-Diffusion Models

Diffusion and interaction of molecular regulators in cells is often modeled using reaction-diffusion partial differential equations. Analysis of such models and exploration of their parameter space is challenging, particularly for systems of high dimensionality. Here, we present a relatively simple and straightforward analysis, the local perturbation analysis, that reveals how parameter variations affect model behavior. This computational tool, which greatly aids exploration of the behavior of a model, exploits a structural feature common to many cellular regulatory systems: regulators are typically either bound to a membrane or freely diffusing in the interior of the cell. Using well-documented, readily available bifurcation software, the local perturbation analysis tracks the approximate early evolution of an arbitrarily large perturbation of a homogeneous steady state. In doing so, it provides a bifurcation diagram that concisely describes various regimes of the model’s behavior, reducing the need for exhaustive simulations to explore parameter space. We explain the method and provide detailed step-by-step guides to its use and application.     

Structure-based systems biology: a zoom lens for the cell

Systems biology seeks to explain complex biological systems, such as the cell, through the integration of many different types of information. Here, we discuss how the incorporation of high-resolution structural data can provide key molecular details often necessary to understand the complex connection between individual molecules and cell behavior. We suggest a process of zooming on the cell, from global networks through pathways to the precise atomic contacts at the interfaces of interacting proteins.     

CCGD-ESCC: A Comprehensive Database for Genetic Variants Associated with Esophageal Squamous Cell Carcinoma in Chinese Population

Esophageal squamous-cell carcinoma (ESCC) is one of the most lethal malignancies in the world and occurs at particularly higher frequency in China. While several genome-wide association studies (GWAS) of germline variants and whole-genome or whole-exome sequencing studies of somatic mutations in ESCC have been published, there is no comprehensive database publically available for this cancer. Here, we developed the Chinese Cancer Genomic Database-Esophageal Squamous Cell Carcinoma (CCGD-ESCC) database, which contains the associations of 69,593 single nucleotide polymorphisms (SNPs) with ESCC risk in 2022 cases and 2039 controls, survival time of 1006 ESCC patients (survival GWAS) and gene expression (expression quantitative trait loci, eQTL) in 94 ESCC patients. Moreover, this database also provides the associations between 8833 somatic mutations and survival time in 675 ESCC patients. Our user-friendly database is a resource useful for biologists and oncologists not only in identifying the associations of genetic variants or somatic mutations with the development and progression of ESCC but also in studying the underlying mechanisms for tumorigenesis of the cancer. CCGD-ESCC is freely accessible at http://db.cbi.pku.edu.cn/ccgd/ESCCdb.     

MyDEP: A New Computational Tool for Dielectric Modeling of Particles and Cells

Dielectrophoresis (DEP) and electrorotation (ROT) are two electrokinetic phenomena exploiting nonuniform electric fields to exert a force or torque on biological particles suspended in liquid media. They are widely used in lab-on-chip devices for the manipulation, trapping, separation, and characterization of cells, microorganisms, and other particles. The DEP force and ROT torque depend on the respective polarizabilities of the particle and medium, which in turn depend on their dielectric properties and on the field frequency. In this work, we present a new software, MyDEP, which implements several particle models based on concentric shells with adjustable dielectric properties. This tool enables the study of the variation in DEP and ROT spectra according to different parameters, such as the field frequency and medium conductivity. Such predictions of particle behavior are very useful for choosing appropriate parameters in DEP experiments. The software also enables the study of the homogenized properties of spherical or ellipsoidal multishell particles and provides a database containing published cell properties. Equivalent electrical conductivity and relative permittivity of the cell alone and in suspension can be calculated. The software also offers the ability to create graphs of the evolution of the crossover frequencies with the electric field frequency. These graphs can be directly exported from the software.     

Membrane-SPINE: A Biochemical Tool to Identify Protein-protein Interactions of Membrane Proteins In Vivo

Membrane proteins are essential for cell viability and are therefore important therapeutic targets^1-3. Since they function in complexes⁴, methods to identify and characterize their interactions are necessary⁵. To this end, we developed the Membrane Strep-protein interaction experiment, called Membrane-SPINE⁶. This technique combines in vivo cross-linking using the reversible cross-linker formaldehyde with affinity purification of a Strep-tagged membrane bait protein. During the procedure, cross-linked prey proteins are co-purified with the membrane bait protein and subsequently separated by boiling. Hence, two major tasks can be executed when analyzing protein-protein interactions (PPIs) of membrane proteins using Membrane-SPINE: first, the confirmation of a proposed interaction partner by immunoblotting, and second, the identification of new interaction partners by mass spectrometry analysis. Moreover, even low affinity, transient PPIs are detectable by this technique. Finally, Membrane-SPINE is adaptable to almost any cell type, making it applicable as a powerful screening tool to identify PPIs of membrane proteins.     

Rice Proteome Database: A Step toward Functional Analysis of the Rice Genome

The technique of proteome analysis using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this study, the proteins of rice were cataloged, a rice proteome database was constructed, and a functional characterization of some of the identified proteins was undertaken. Proteins extracted from various tissues and subcellular compartments in rice were separated by 2D-PAGE and an image analyzer was used to construct a display of the proteins. The Rice Proteome Database contains 23 reference maps based on 2D-PAGE of proteins from various rice tissues and subcellular compartments. These reference maps comprise 13129 identified proteins, and the amino acid sequences of 5092 proteins are entered in the database. Major proteins involved in growth or stress responses were identified using the proteome approach. Some of these proteins, including a β-tubulin, calreticulin, and ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have unexpected functions. The information obtained from the Rice Proteome Database will aid in cloning the genes for and predicting the function of unknown proteins.     

FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses

The immune response is a concerted dynamic multi-cellular process. Upon infection, the dynamics of lymphocyte populations are an aggregate of molecular processes that determine the activation, division, and longevity of individual cells. The timing of these single-cell processes is remarkably widely distributed with some cells undergoing their third division while others undergo their first. High cell-to-cell variability and technical noise pose challenges for interpreting popular dye-dilution experiments objectively. It remains an unresolved challenge to avoid under- or over-interpretation of such data when phenotyping gene-targeted mouse models or patient samples. Here we develop and characterize a computational methodology to parameterize a cell population model in the context of noisy dye-dilution data. To enable objective interpretation of model fits, our method estimates fit sensitivity and redundancy by stochastically sampling the solution landscape, calculating parameter sensitivities, and clustering to determine the maximum-likelihood solution ranges. Our methodology accounts for both technical and biological variability by using a cell fluorescence model as an adaptor during population model fitting, resulting in improved fit accuracy without the need for ad hoc objective functions. We have incorporated our methodology into an integrated phenotyping tool, FlowMax, and used it to analyze B cells from two NFκB knockout mice with distinct phenotypes; we not only confirm previously published findings at a fraction of the expended effort and cost, but reveal a novel phenotype of nfkb1/p105/50 in limiting the proliferative capacity of B cells following B-cell receptor stimulation. In addition to complementing experimental work, FlowMax is suitable for high throughput analysis of dye dilution studies within clinical and pharmacological screens with objective and quantitative conclusions.     

Interaction of ERp57 with calreticulin: Analysis of complex formation and effects of vancomycin

The protein ERp57 (also known as PDIA3) is a widely distributed protein, mainly localized in the endoplasmic reticulum, where it acts as disulfide isomerase, oxidoreductase and chaperone, in concert with the lectins calreticulin (CRT) and calnexin. The ERp57/CRT complex has been detected on the cell surface and previous studies have suggested its involvement in programmed cell death. Although the ERp57-CRT complex has been characterized, little is known about its role in different cellular compartments as well as inhibitors of this interaction.We focused on the kinetic, extent and stability of the ERp57-CRT complex, using the surface plasmon resonance spectroscopy, investigating the possible role as inhibitor of the antibiotic vancomycin. Equilibrium thermodynamic data suggested that vancomycin may hinder the interaction between the two proteins and could interfere with the ERp57 conformational changes that stabilize the complex. Furthermore, by means of confocal microscopy, we evaluated the effect of the in vivo administration of vancomycin on the ERp57/CRT complex on the surface of HeLa cells.The model presented here could be used for the search of other specific inhibitors/interactors of ERp57, which can be extremely helpful to understand the biological pathways where the protein is involved and to modulate its activity.     

BioCluster:Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is laborintensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface(GUI) tool named Bio Cluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering(HC) and the Improved Hierarchical Clustering(IHC), a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that Bio Cluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.     

InDiaMed: A Comprehensive Database of Indian Medicinal plants for Diabetes

According to International Diabetes Federation (IDF), India has 62.4 million people with diabetes and by 2030 it is predicted that the number will rise to 100 million. Studies claim that there are around 410 experimentally proven Indian medicinal plants which have anti-diabetic activity, of which the mechanism of action of 109 plants has been elucidated or reported. So, the need of the hour is to explore the claims of Indian medicinal flora and open up the facets of many Indian plants which are being examined for their beneficial role in diabetes. So, we created a database (InDiaMed) of Indian medicinal plants that captures their role in anti-diabetic activity. InDiaMed''s features include chemical, pharmacological, biochemical and geographical information of the medicinal plant, scientifically relevant information of the plant, and the coherent research done on it in the field of diabetes. The database also includes the list of poly-herbal formulations which are used for treatment of diabetes in India.

Availability

http://www.indiamed.info     

A Computational Analysis on the Specificity of Interactions Between Histidine Kinases and Response Regulators

Abstract

Bacteria process and transmit signals simultaneously through several two-component/phos-phorelay networks using closely related proteins. Therefore discrimination against mismatches and discrete recognition between protein partners is an absolute requirement for producing the correct responses. We tried to address this issue by comparing and analyzing sequences from the helix-bundle regions of histidine kinases of Bacillus subtilis. Our analysis shows how conservation and variability in the sequences give rise to selective association and unique recognition. The observed pattern suggests that the chances for cross talk between non-partner proteins are extremely low, but cross talk could take place in special cases.     

GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains (TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.     

Saposin Lipid Nanoparticles: A Highly Versatile and Modular Tool for Membrane Protein Research

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Relationship between intramolecular hydrogen bonding and solvent accessibility of side-chain donors and acceptors in proteins

This study shows that intramolecular hydrogen bonding in proteins depends on the accessibility of donors and acceptors to water molecules. The frequency of occurrence of H-bonded side chains in proteins is inversely proportional to the solvent accessibility of their donors and acceptors. Estimates of the notional free energy of hydrogen bonding suggest that intramolecular hydrogen-bonding interactions of buried and half-buried donors and acceptors can contribute favorably to the stability of a protein, whereas those of solvent-exposed polar atoms become less favorable or unfavorable.     

PFDB: A Protein Families DataBase for Macintosh Computers. The Effectiveness of Its Organization in Searching for Protein Similarity

A protein sequence database (PFDB) containing about 11,000 entries is available for Macintosh computers. The PFDB can be easily updated by importing sequences from the PIR collection through the internet. The most important feature of the database is its organization in families of closely related sequences, each family being characterized by its average dipeptide composition [Petrilli (1993), Comput. Appl. Biosci. 2, 89–93]. This allows one to perform a rapid and sensitive protein similarity search by comparing the precalculated family dipeptide composition with that of the query sequence by a linear correlation coefficient. An example of an application in which a new protein was classsified by using a sequence of a fragment just 19 residues long is reported.