PepBind: A Comprehensive Database and Computational Tool for Analysis of Protein-peptide Interactions

Protein–peptide interactions, where one partner is a globular protein (domain) and the other is a flexible linear peptide, are key components of cellular processes predominantly in signaling and regulatory networks, hence are prime targets for drug design. To derive the details of the protein–peptide interaction mechanism is often a cumbersome task, though it can be made easier with the availability of specific databases and tools. The Peptide Binding Protein Database (PepBind) is a curated and searchable repository of the structures, sequences and experimental observations of 3100 protein–peptide complexes. The web interface contains a computational tool, protein inter-chain interaction (PICI), for computing several types of weak or strong interactions at the protein–peptide interaction interface and visualizing the identified interactions between residues in Jmol viewer. This initial database release focuses on providing protein–peptide interface information along with structure and sequence information for protein–peptide complexes deposited in the Protein Data Bank (PDB). Structures in PepBind are classified based on their cellular activity. More than 40% of the structures in the database are found to be involved in different regulatory pathways and nearly 20% in the immune system. These data indicate the importance of protein–peptide complexes in the regulation of cellular processes. PepBind is freely accessible at http://pepbind.bicpu.edu.in/.     

Neurotree: A Collaborative,Graphical Database of the Academic Genealogy of Neuroscience

Neurotree is an online database that documents the lineage of academic mentorship in neuroscience. Modeled on the tree format typically used to describe biological genealogies, the Neurotree web site provides a concise summary of the intellectual history of neuroscience and relationships between individuals in the current neuroscience community. The contents of the database are entirely crowd-sourced: any internet user can add information about researchers and the connections between them. As of July 2012, Neurotree has collected information from 10,000 users about 35,000 researchers and 50,000 mentor relationships, and continues to grow. The present report serves to highlight the utility of Neurotree as a resource for academic research and to summarize some basic analysis of its data. The tree structure of the database permits a variety of graphical analyses. We find that the connectivity and graphical distance between researchers entered into Neurotree early has stabilized and thus appears to be mostly complete. The connectivity of more recent entries continues to mature. A ranking of researcher fecundity based on their mentorship reveals a sustained period of influential researchers from 1850–1950, with the most influential individuals active at the later end of that period. Finally, a clustering analysis reveals that some subfields of neuroscience are reflected in tightly interconnected mentor-trainee groups.     

Current Practice in Software Development for Computational Neuroscience and How to Improve It

Almost all research work in computational neuroscience involves software. As researchers try to understand ever more complex systems, there is a continual need for software with new capabilities. Because of the wide range of questions being investigated, new software is often developed rapidly by individuals or small groups. In these cases, it can be hard to demonstrate that the software gives the right results. Software developers are often open about the code they produce and willing to share it, but there is little appreciation among potential users of the great diversity of software development practices and end results, and how this affects the suitability of software tools for use in research projects. To help clarify these issues, we have reviewed a range of software tools and asked how the culture and practice of software development affects their validity and trustworthiness.We identified four key questions that can be used to categorize software projects and correlate them with the type of product that results. The first question addresses what is being produced. The other three concern why, how, and by whom the work is done. The answers to these questions show strong correlations with the nature of the software being produced, and its suitability for particular purposes. Based on our findings, we suggest ways in which current software development practice in computational neuroscience can be improved and propose checklists to help developers, reviewers, and scientists to assess the quality of software and whether particular pieces of software are ready for use in research.     

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.     

U7 snRNAs： A Computational Survey

U7 small nuclear RNA (snRNA) sequences have been described only for a handful of animal species in the past. Here we describe a computational search for func- tional U7 snRNA genes throughout vertebrates including the upstream sequence elements characteristic for snRNAs transcribed by polymerase Ⅱ. Based on the results of this search, we discuss the high variability of U7 snRNAs in both se- quence and structure, and report on an attempt to find U7 snRNA sequences in basal deuterostomes and non-drosophilids insect genomes based on a combination of sequence, structure, and promoter features. Due to the extremely short se- quence and the high variability in both sequence and structure, no unambiguous candidates were found. These results cast doubt on putative U7 homologs in even more distant organisms that are reported in the most recent release of the Rfam database.     

Monitoring Performance Degradation of Cerebellar Functions Using Computational Neuroscience Methods: Implications on Neurological Diseases

Neurodegeneration is a major cause of human disease. Within the cerebellum, neuronal degeneration and/or dysfunction has been associated with many diseases, including several forms of cerebellar ataxia, since normal cerebellar function is paramount for proper motor coordination, balance, and motor learning. The cerebellum represents a well-established neural circuit. Determining the effects of neuronal loss is of great importance for understanding the fundamental workings of the cerebellum and disease-associated dysfunctions. This paper presents computational modeling of cerebellar function in relation to neurodegeneration either affecting a specific cerebellar cell type, such as granule cells or Purkinje cells, or more generally affecting cerebellar cells and the implications on effects in relation to performance degradation throughout the progression of cell death. The results of the models show that the overall number of cells, as a percentage of the total cell number in the model, of a particular type and, primarily, their proximity to the circuit output, and not the neuronal convergence due to the relative number of cells of a particular type, is the main indicator of the gravity of the functional deficit caused by the degradation of that cell type. Specifically, the greater the percentage loss of neurons of a specific type and the closer proximity of those cells to the deep cerebellar neurons, the greater the deficit caused by the neuronal cell loss. These findings contribute to the understanding of the functional consequences of neurodegeneration and the functional importance of specific connectivity within a neuronal circuit.     

Pescador: the PEptides in Solution ConformAtion Database: Online Resource

In recent years a large body of data has been obtained from Nuclear Magnetic Resonance and Circular Dichroism experiments on the influence of the amino acid sequence and various other parameters on the conformational state of peptides in solution. Interpreting the experimental data in terms of the conformational populations of the peptides remains a key problem, for which current solutions leave appreciable room for improvement. Considering that making this body of data available for surveys and analysis should be instrumental in tackling the problem, we undertook the development of Pescador: The `PEptides in Solution ConformAtion Database: Online Resource'. Pescador contains data from NMR and CD spectroscopy on peptides in solution as well as information on the structural parameters derived from these data. It also features specialized Web-based tools for data deposition, and means for readily accessing the stored information for analysis purposes. To illustrate the use of the database in deriving information for the conformational analysis of peptides, we show how the alpha proton -values stored in Pescador and measured by NMR for different peptides in different laboratories can be used to derive a new set of `random coil' chemical shift values. Firstly, we show these values to be very similar to those obtained experimentally for model peptides in water, and their variation with increasing Tri-Fluoro-Ethanol (TFE) concentration is similar to that reported for model peptides. We show, furthermore, that the chemical shift data in Pescador can be used to derive correction factors that take into account effects of neighboring residues. These correction factors compare favorably with those recently derived from a series of model GGXGG peptides Schwarzinger_e-valuesstoredinPescadorandmeasuredbyNMRfordifferentpeptidesindifferentlaboratoriescanbeusedtoderiveanewsetof`randomcoil'chemicalshiftvalues.Firstly,weshowthesevaluestobeverysimilartothoseobtainedexperimentallyformodelpeptidesinwater,andtheirvariationwithincreasingTri-Fluoro-Ethanol(TFE)concentrationissimilartothatreportedformodelpeptides.Weshow,furthermore,thatthechemicalshiftdatainPescadorcanbeusedtoderivecorrectionfactorsthattakeintoaccounteffectsofneighboringresidues.ThesecorrectionfactorscomparefavorablywiththoserecentlyderivedfromaseriesofmodelGGXGGpeptides Schwarzinger _etal. These encouraging results suggest that, as the quantity of NMR data on peptide deposited in Pescador increases, surveys of these data should be a valuable means of deriving key parameters for the analysis of peptide conformation.     

Frontiers of Model Animals for Neuroscience:Two Prosperous Aging Model Animals forPromoting Neuroscience Research

A model animal showing spontaneous onset is a useful tool for investigating the mechanism of disease. Here, I would like to introduce two aging model animals expected to be useful for neuroscience research: the senescence-accelerated mouse (SAM) and the klotho mouse. The SAM was developed as a mouse showing a senescence-related phenotype such as a short lifespan or rapid advancement of senescence. In particular, SAMP8 and SAMP10 show age-related impairment of learning and memory. SAMP8 has spontaneous spongy degeneration in the brain stem and spinal cord with aging, and immunohistochemical studies reveal excess protein expression of amyloid precursor protein and amyloid β in the brain, indicating that SAMP8 is a model for Alzheimer’s disease. SAMP10 also shows age-related impairment of learning and memory, but it does not seem to correspond to Alzheimer’s disease because senile plaques primarily composed of amyloid β or neurofibrillary tangles primarily composed of phosphorylated tau were not observed. However, severe atrophy in the frontal cortex, entorhinal cortex, amygdala, and nucleus accumbens can be seen in this strain in an age-dependent manner, indicating that SAMP10 is a model for normal aging. The klotho mouse shows a phenotype, regulated by only one gene named α-klotho, similar to human progeria. The α-klotho gene is mainly expressed in the kidney and brain, and oxidative stress is involved in the deterioration of cognitive function of the klotho mouse. These animal models are potentially useful for neuroscience research now and in the near future.     

BEID: Database for sequence-structure-function information on antigen-antibody interactions

The B-cell Epitope Interaction Database (BEID; http://datam.i2r.a-star.edu.sg/BEID) is an open-access database describing sequence-structure-function information on immunoglobulin (Ig)-antigen interactions. The current version of the database contains 164 antigens, 126 Ig and 189 Ig-antigen complexes extracted from the Protein Data Bank (PDB). Each entry is manually verified, classified, and analyzed for intermolecular interactions between antigens and the corresponding bound Ig molecules. Ig-antigen interaction information that is stored in BEID includes solvent accessibility, hydrogen bonds, non-hydrogen bonds, gap volume, gap index, interface area and contact residues. The database can be searched with a user-friendly search tool and schematic diagrams for Ig-antigen interactions are available for download in PDF format. The ultimate purpose of BEID is to enhance the understanding of the rules of engagement between antigen and the corresponding bound Ig molecules. It is also a precious data source for developing computational predictors for B-cell epitopes.     

DDTRP: Database of Drug Targets for Resistant Pathogens

Emergence of drug resistance is a major threat to public health. Many pathogens have developed resistance to most of the existing antibiotics, and multidrug-resistant and extensively drug resistant strains are extremely difficult to treat. This has resulted in an urgent need for novel drugs. We describe a database called 'Database of Drug Targets for Resistant Pathogens' (DDTRP). The database contains information on drugs with reported resistance, their respective targets, metabolic pathways involving these targets, and a list of potential alternate targets for seven pathogens. The database can be accessed freely at http://bmi.icmr.org.in/DDTRP.     

Computational framework to model and design surgical meshes for hernia repair

Surgical procedures for hernia surgery are usually performed using prosthetic meshes. In spite of all the improvements in these biomaterials, the perfect match between the prosthesis and the implant site has not been achieved. Thus, new designs of surgical meshes are still being developed. Previous to implantation in humans, the validity of the meshes has to be addressed, and to date experimental studies have been the gold standard in testing and validating new implants. Nevertheless, these procedures involve long periods of time and are expensive. Thus, a computational framework for the simulation of prosthesis and surgical procedures may overcome some disadvantages of the experimental methods. The computational framework includes two computational models for designing and validating the behaviour of new meshes, respectively. Firstly, the beam model, which reproduces the exact geometry of the mesh, is set to design the weave and determine the stiffness of the surgical prosthesis. However, this implies a high computational cost whereas the membrane model, defined within the framework of the large deformation hyperelasticity, is a relatively inexpensive computational tool, which also enables a prosthesis to be included in more complex geometries such as human or animal bodies.