Assembly of Influenza Hemagglutinin Fusion Peptides in a Phospholipid Bilayer by Coarse-grained Computer Simulations

Membrane fusion is critical to eukaryotic cellular function and crucial to the entry of enveloped viruses such as influenza and human immunodeficiency virus. Influenza viral entry in the host cell is mediated by a 20-23 amino acid long sequence, called the fusion peptide (FP). Recently, possible structures for the fusion peptide (ranging from an inverted V shaped α-helical structure to an α-helical hairpin, or to a complete α-helix) and their implication in the membrane fusion initiation have been proposed. Despite the large number of studies devoted to the structure of the FP, the mechanism of action of this peptide remains unclear with several mechanisms having been suggested, including the induction of local disorder, promoting membrane curvature, and/or altering local membrane composition. In recent years, several research groups have employed atomistic and/or coarse-grained molecular dynamics (MD) simulations to investigate the matter. In all previous works, the behavior of a single FP monomer was studied, while in this manuscript, we use a simplified model of a tripeptide (TP) monomer of FP (TFP) instead of a single FP monomer because each Influenza Hemagglutinin contains three FP molecules in the biological system. In this manuscript we report findings targeted at understanding the fusogenic properties and the collective behavior of these trimers of FP peptides on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine model membrane. Here we show how the TFP monomers self-assemble into differently sized oligomers in the presence of the membrane. We measure the perturbation to the structure of the phospholipid membrane caused by the presence of these TFP oligomers. Our work (i) shows how self-assembly of TFP in the presence of the membrane induces non negligible deformation to the membrane and (ii) could be a useful starting point to stimulate discussion and further work targeted to fusion pore formation.</p

Transitional B Cells in Early Human B Cell Development – Time to Revisit the Paradigm?

The B cell repertoire is generated in the adult bone marrow by an ordered series of gene rearrangement processes that result in massive diversity of immunoglobulin (Ig) genes, and consequently an equally large number of potential specificities for antigen. As the process is essentially random, then cells exhibiting excess reactivity with self-antigens are generated and need to be removed from the repertoire before the cells are fully mature. Some of the cells are deleted, and some will undergo receptor editing to see if changing the light chain can rescue an autoreactive antibody. As a consequence, the binding properties of the B cell receptor are changed as development progresses through pre- B>>immature>>transitional>>naïve phenotypes. Using long-read, high-throughput, sequencing we have produced a unique set of sequences from these four cell types in human bone marrow and matched peripheral blood and our results describe the effects of tolerance selection on the B cell repertoire at the Ig gene level. Most strong effects of selection are seen within the heavy chain repertoire, and can be seen both in gene usage and in CDR-H3 characteristics. Age-related changes are small and only the size of the CDR-H3 shows constant and significant change in these data. The paucity of significant changes in either kappa or lambda light chain repertoires implies that either the heavy chain has more influence over autoreactivity than light chain and/or that switching between kappa and lambda light chains, as opposed to switching within the light chain loci, may effect a more successful autoreactive rescue by receptor editing. Our results show that the transitional cell population contains cells other than those that are part of the pre-B>>immature>>transitional>>naïve development pathway, since the population often shows a repertoire that is outside the trajectory of gene loss/gain between pre-B and naïve stages

TITINdb:A computational tool to assess titin's role as a disease gene

Large numbers of rare and unique titin missense variants have been discovered in both healthy and disease cohorts, thus the correct classification of variants as pathogenic or non-pathogenic has become imperative. Due to titin's large size (363 coding exons), current web applications are unable to map titin variants to domain structures. Here, we present a web application, TITINdb, which integrates titin structure, variant, sequence and isoform information, along with pre-computed predictions of the impact of non-synonymous single nucleotide variants, to facilitate the correct classification of titin variants

Predicting class switch recombination in B-cells from antibody repertoire data

Statistical and machine learning methods have proved useful in many areas of immunology. In this paper, we address for the first time the problem of predicting the occurrence of class switch recombination (CSR) in B-cells, a problem of interest in understanding antibody response under immunological challenges. We propose a framework to analyze antibody repertoire data, based on clonal (CG) group representation in a way that allows us to predict CSR events using CG level features as input. We assess and compare the performance of several predicting models (logistic regression, LASSO logistic regression, random forest, and support vector machine) in carrying out this task. The proposed approach can obtain an unweighted average recall of (Formula presented.) with models based on variable region descriptors and measures of CG diversity during an immune challenge and, most notably, before an immune challenge

Predicting class switch recombination in B-cells from antibody repertoire data

Statistical and machine learning methods have proved useful in many areas of immunology. In this paper, we address for the first time the problem of predicting the occurrence of class switch recombination (CSR) in B-cells, a problem of interest in understanding antibody response under immunological challenges. We propose a framework to analyze antibody repertoire data, based on clonal (CG) group representation in a way that allows us to predict CSR events using CG level features as input. We assess and compare the performance of several predicting models (logistic regression, LASSO logistic regression, random forest, and support vector machine) in carrying out this task. The proposed approach can obtain an unweighted average recall of with models based on variable region descriptors and measures of CG diversity during an immune challenge and, most notably, before an immune challenge

Structural Properties of Green Tea Catechins

Green tea catechins are polyphenols which are believed to provide health benefits; they are marketed as health supplements and are studied for their potential effects on a variety of medical conditions. However, their mechanisms of action and interaction with the environment at the molecular level are still not well-understood. Here, by means of atomistic simulations, we explore the structural properties of four green tea catechins, in the gas phase and water solution: specifically, (-)-epigallocatechin-3-gallate, which is the most abundant, (-)-epicatechin-3-gallate, (-)-epigallocatechin-3-O-(3-O-methyl)-gallate, and (-)-epigallocatechin. We characterize the free energy conformational landscapes of these catechins at ambient conditions, as a function of the torsional degrees of freedom of the pholyphenolic rings, determining the stable conformers and their connections. We show that these free energy landscapes are only subtly influenced by the interactions with the solvent and by the structural details of the polyphenolic rings. However, the number and position of the hydroxyl groups (or their sustituents) and the presence/absence of the galloyl moiety have significant impact on the selected catechin solvation shells and hydrogen bond capabilities, which are ultimately linked to their ability to interact with and affect the biological environment.</p

Characterisation of HOIP RBR E3 ligase conformational dynamics using integrative modelling

Multidomain proteins composed of individual domains connected by flexible linkers pose a challenge for structural studies due to their intrinsic conformational dynamics. Integrated modelling approaches provide a means to characterise protein flexibility by combining experimental measurements with molecular simulations. In this study, we characterise the conformational dynamics of the catalytic RBR domain of the E3 ubiquitin ligase HOIP, which regulates immune and inflammatory signalling pathways. Specifically, we combine small angle X-ray scattering experiments and molecular dynamics simulations to generate weighted conformational ensembles of the HOIP RBR domain using two different approaches based on maximum parsimony and maximum entropy principles. Both methods provide optimised ensembles that are instrumental in rationalising observed differences between SAXS-based solution studies and available crystal structures and highlight the importance of interdomain linker flexibility

A New Crystal Form of the SARS-CoV-2 Receptor Binding Domain:CR3022 Complex—An Ideal Target for In-Crystal Fragment Screening of the ACE2 Binding Site Surface

In-crystal fragment screening is a powerful tool to chemically probe the surfaces used by proteins to interact, and identify the chemical space worth exploring to design protein-protein inhibitors. A crucial prerequisite is the identification of a crystal form where the target area is exposed and accessible to be probed by fragments. Here we report a crystal form of the SARS-CoV-2 Receptor Binding Domain in complex with the CR3022 antibody where the ACE2 binding site on the Receptor Binding Domain is exposed and accessible. This crystal form of the complex is a valuable tool to develop antiviral molecules that could act by blocking the virus entry in cells.</p