Structural Allele-Specific Patterns Adopted by Epitopes in the MHC-I Cleft and Reconstruction of MHC:peptide Complexes to Cross-Reactivity Assessment

The immune system is engaged in a constant antigenic surveillance through the Major Histocompatibility Complex (MHC) class I antigen presentation pathway. This is an efficient mechanism for detection of intracellular infections, especially viral ones. In this work we describe conformational patterns shared by epitopes presented by a given MHC allele and use these features to develop a docking approach that simulates the peptide loading into the MHC cleft. Our strategy, to construct in silico MHC:peptide complexes, was successfully tested by reproducing four different crystal structures of MHC-I molecules available at the Protein Data Bank (PDB). An in silico study of cross-reactivity potential was also performed between the wild-type complex HLA-A2-NS31073 and nine MHC:peptide complexes presenting alanine exchange peptides. This indicates that structural similarities among the complexes can give us important clues about cross reactivity. The approach used in this work allows the selection of epitopes with potential to induce cross-reactive immune responses, providing useful tools for studies in autoimmunity and to the development of more comprehensive vaccines

Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient’s own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide–ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide–MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC “hot-spots” for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications

New insights into the in silico prediction of HIV protease resistance to nelfinavir.

The Human Immunodeficiency Virus type 1 protease enzyme (HIV-1 PR) is one of the most important targets of antiretroviral therapy used in the treatment of AIDS patients. The success of protease-inhibitors (PIs), however, is often limited by the emergence of protease mutations that can confer resistance to a specific drug, or even to multiple PIs. In the present study, we used bioinformatics tools to evaluate the impact of the unusual mutations D30V and V32E over the dynamics of the PR-Nelfinavir complex, considering that codons involved in these mutations were previously related to major drug resistance to Nelfinavir. Both studied mutations presented structural features that indicate resistance to Nelfinavir, each one with a different impact over the interaction with the drug. The D30V mutation triggered a subtle change in the PR structure, which was also observed for the well-known Nelfinavir resistance mutation D30N, while the V32E exchange presented a much more dramatic impact over the PR flap dynamics. Moreover, our in silico approach was also able to describe different binding modes of the drug when bound to different proteases, identifying specific features of HIV-1 subtype B and subtype C proteases

Structural analysis of sB-D30V.

<p>(A) Superposition of the structures of sB-WT PR at 2,500 ps of simulation (grey) and at 50,000 ps (black). (B–C) Superposition of sB-D30N (red) and sB-D30V (green) at 50,000 ps over the respective structures at 2,500 ps (grey). (D–F) Measure of the deviation of ILE50 residue from PR Chain A considering the same structures from A, B and C, indicating the extent of Chain A flap movement. (G) Plot of the variation of the ASP25-ILE50 distance (Chain A) along the simulation. The stipulated threshold for semiopen conformation (1.58 nm) is indicated in blue.</p

Open conformation of the sB-V32E protease.

<p>Comparison between two frames of a molecular dynamics of the sB-V32E PR complexed with NF. Protease structure at 2,500 ps (25 ns) is represented in white (<i>cartoon</i>) with Nelfinavir depicted in purple (<i>sticks</i>). Protease structure at 50,000 ps (50 ns), in an open conformation, is depicted in blue (<i>cartoon</i>).</p

Conformational variability of Nelfinavir.

<p>Structural analysis of Nelfinavir in solution along 100(FES) of this simulation (top) indicates three “islands” of low energy conformations (i1, i2 and i3), from which different structures were recovered (NF-i1, NF-i2, NF-i3). The crystal structure of Nelfinavir (1OHR) was the input conformation, and Root Mean Square Deviation (RMSD) indicates that all conformations sampled during the simulation differ from original structure by at least 0.2 nm (down).</p

Hydrogen bonds between NF and residue 30 of sB-PRs

<p>. Number (above) and average (below) of hydrogen bonds performed between the ligand Nelfinavir and the residue 30 of each subtype B (sB) protease (Chain A) along 50 ns of molecular dynamics simulation. The colors are given in black, red and green for the wild-type (sB-WT), D30N (sB-D30N) and D30V (sB-D30V), respectively.</p

Short replicated simulations of sB-PRs bound to NF.

<p>Average and Standard Deviation of the Root Mean Square Deviation (RMSD) for five independent 10 ns simulations of four different subtype B proteases (sB-PRs) bound to Nelfinavir (NF). Greater divergence is observed for sB-V32E, since two of its replicates presented a change to an open conformation of the flaps. Equilibration stages (before 2,500 ps) are not represented. Independent trajectories of each simulation can be observed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087520#pone.0087520.s002" target="_blank">Figure S2</a>.</p