Anisotropic Charge Distribution and Anisotropic van der Waals Radius Leading to Intriguing Anisotropic Noncovalent Interactions

Although group (IV-VII) nonmetallic elements do not favor interacting with anionic species, there are counterexamples including the halogen bond. Such binding is known to be related to the charge deficiency because of the adjacent atom's electron withdrawing effect, which creates s/p-holes at the bond-ends. However, a completely opposite behavior is exhibited by N-2 and O-2, which have electrostatically positive/negative character around cylindrical-bond-surface/bond-ends. Inspired by this, here we elucidate the unusual features and origin of the anisotropic noncovalent interactions in the ground and excited states of the 2nd and 3rd row elements belonging to groups IV-VII. The anisotropy in charge distributions and van der Waals radii of atoms in such molecular systems are scrutinized. This provides an understanding of their unusual molecular configuration, binding and recognition modes involved in new types of molecular assembling and engineering. This work would lead to the design of intriguing molecular systems exploiting anisotropic noncovalent interactions.open

ElliPro: a new structure-based tool for the prediction of antibody epitopes

<p>Abstract</p> <p>Background</p> <p>Reliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.</p> <p>Results</p> <p>Here we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at <url>http://tools.immuneepitope.org/tools/ElliPro</url>.</p> <p>Conclusion</p> <p>The results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.</p

Curation of complex, context-dependent immunological data

BACKGROUND: The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data . DESCRIPTION: To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation. CONCLUSION: Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise

Physiological Effects of Superoxide Dismutase on Altered Visual Function of Retinal Ganglion Cells in db/db Mice

Background: The C57BLKS/J db/db (db/db) mouse is a widely used type 2 diabetic animal model, and this model develops early inner retinal neuronal dysfunction beginning at 24 weeks. The neural mechanisms that mediate early stage retinal dysfunction in this model are unknown. We evaluated visual response properties of retinal ganglion cells (RGCs) during the early stage of diabetic insult (8, 12, and 20 wk) in db/db mice and determined if increased oxidative stress plays a role in impaired visual functions of RGCs in 20 wk old db/db mice. Methodology/Principal Findings: In vitro extracellular single-unit recordings from RGCs in wholemount retinas were performed. The receptive field size, luminance threshold, and contrast gain of the RGCs were investigated. Although ONand OFF-RGCs showed a different time course of RF size reduction, by 20 wk, the RF of ON- and OFF-RGCs were similarly affected. The LT of ON-RGCs was significantly elevated in 12 and 20 wk db/db mice compared to the LT of OFF-RGCs. The diabetic injury also affected contrast gains of ON- and OFF-RGCs differently. The generation of reactive oxidative species (ROS) in fresh retina was estimated by dihydroethidium. Superoxide dismutase (SOD) (300 unit/ml) was applied in Ames medium to the retina, and visual responses of RGCs were recorded for five hours. ROS generation in the retinas of db/db mice increased at 8wk and continued to progress at 20 wk of ages. In vitro application of SOD improved visual functions in 20 wk db/db mice but the SOD treatment affected ON- and OFF-RGCs differently in db/m retina

Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions

Development of Immune-Specific Interaction Potentials and Their Application in the Multi-Agent-System VaccImm

Peptide vaccination in cancer therapy is a promising alternative to conventional methods. However, the parameters for this personalized treatment are difficult to access experimentally. In this respect, in silico models can help to narrow down the parameter space or to explain certain phenomena at a systems level. Herein, we develop two empirical interaction potentials specific to B-cell and T-cell receptor complexes and validate their applicability in comparison to a more general potential. The interaction potentials are applied to the model VaccImm which simulates the immune response against solid tumors under peptide vaccination therapy. This multi-agent system is derived from another immune system simulator (C-ImmSim) and now includes a module that enables the amino acid sequence of immune receptors and their ligands to be taken into account. The multi-agent approach is combined with approved methods for prediction of major histocompatibility complex (MHC)-binding peptides and the newly developed interaction potentials. In the analysis, we critically assess the impact of the different modules on the simulation with VaccImm and how they influence each other. In addition, we explore the reasons for failures in inducing an immune response by examining the activation states of the immune cell populations in detail

A Meta-Analysis of the Existing Knowledge of Immunoreactivity against Hepatitis C Virus (HCV)

Approximately 3% of the world population is infected by HCV, which represents a major global health challenge. Almost 400 different scientific reports present immunological data related to T cell and antibody epitopes derived from HCV literature. Analysis of all HCV-related epitope hosted in the Immune Epitope Database (IEDB), a repository of freely accessible immune epitope data, revealed more than 1500 and 1900 distinct T cell and antibody epitopes, respectively. The inventory of all data revealed specific trends in terms of the host and the HCV genotypes from which sequences were derived. Upon further analysis we found that this large number of epitopes reflects overlapping structures, and homologous sequences derived from different HCV isolates. To access and visualize this information we developed a novel strategy that assembles large sets of epitope data, maps them onto reference genomes and displays the frequency of positive responses. Compilation of the HCV immune reactivity from hundreds of different studies, revealed a complex and thorough picture of HCV immune epitope data to date. The results pinpoint areas of more intense reactivity or research activities at the level of antibody, CD4 and CD8 responses for each of the individual HCV proteins. In general, the areas targeted by the different effector immune functions were distinct and antibody reactivity was positively correlated with hydrophilicity, while T cell reactivity correlated with hydrophobicity. At the sequence level, epitopes frequently recognized by both T cell and B cell correlated with low variability, and our analysis thus highlighted areas of potential interest for practical applications. The human reactivity was further analyzed to pinpoint differential patterns of reactivity associated with acute versus chronic infection, to reveal the apparent impact of glycosylation on T cell, but not antibody responses, and to highlight a paucity of studies involved antibody epitopes associated with virus neutralization