Caseinolytic protease P (ClpP) represents a central bacterial degradation machinery that is involved in cell homeostasis and pathogenicity. The functional role of ClpP has been studied by genetic knockouts and through the use of beta-lactones, which remain the only specific inhibitors of ClpP discovered to date. Beta-lactones have served as chemical tools to manipulate ClpP in several organisms, however, their potency, selectivity and stability is limited. Despite detailed structural insights into the composition and conformational flexibility of the ClpP active site, no rational efforts to design specific non-beta-lactone inhibitors have been reported to date. In this work, an unbiased screen of more than 137,000 compounds was used to identify five phenyl ester compounds as highly potent ClpP inhibitors that were selective for bacterial, but not human ClpP.The potency of phenyl esters largely exceeded that of beta-lactones in ClpP peptidase and protease inhibition assays and displayed unique target selectivity in living S. aureus cells.Analytical studies revealed that while phenyl esters are cleaved like native peptide substrates, they remain covalently trapped as acyl-enzyme intermediates in the active site. The synthesis of 36 derivatives and subsequent structure-activity relationship (SAR) studies provided insights into conserved structural elements that are important for inhibition potency and acylation reactivity.Moreover, the stereochemistry of a methyl-substituent at the alpha position to the ester, resembling amino acid side chains in peptide substrates, impacted ClpP complex stability, causing either dissociation into heptamers or retention of the tetradecameric state. Mechanistic insights into this intriguing stereo switch and the phenyl ester binding mode were obtained by molecular docking experiments.

Virus-specific CD8 T cell response seems to play a significant role in the outcome of hepatitis delta virus (HDV) infection. However, the HDV-specific T cell epitope repertoire and mechanisms of CD8 T cell failure in HDV infection have been poorly characterized. We therefore aimed to characterize HDV-specific CD8 T cell epitopes and the impacts of viral mutations on immune escape. In this study, we predicted peptide epitopes binding the most frequent human leukocyte antigen (HLA) types and assessed their HLA binding capacities. These epitopes were characterized in HDV-infected patients by intracellular gamma interferon (IFN-γ) staining. Sequence analysis of large hepatitis delta antigen (L-HDAg) and HLA typing were performed in 104 patients. The impacts of substitutions within epitopes on the CD8 T cell response were evaluated experimentally and by studies. We identified two HLA-B*27-restricted CD8 T cell epitopes within L-HDAg. These novel epitopes are located in a relatively conserved region of L-HDAg. However, we detected molecular footprints within the epitopes in HLA-B*27-positive patients with chronic HDV infections. The variant peptides were not cross-recognized in HLA-B*27-positive patients with resolved HDV infections, indicating that the substitutions represent viral escape mutations. Molecular modeling of HLA-B*27 complexes with the L-HDAg epitope and its potential viral escape mutations indicated that the structural and electrostatic properties of the bound peptides differ considerably at the T cell receptor interface, which provides a possible molecular explanation for the escape mechanism. This viral escape from the HLA-B*27-restricted CD8 T cell response correlates with a chronic outcome of hepatitis D infection. T cell failure resulting from immune escape may contribute to the high chronicity rate in HDV infection. Hepatitis delta virus (HDV) causes severe chronic hepatitis, which affects 20 million people worldwide. Only a small number of patients are able to clear the virus, possibly mediated by a virus-specific T cell response. Here, we performed a systematic screen to define CD8 epitopes and investigated the role of CD8 T cells in the outcome of hepatitis delta and how they fail to eliminate HDV. Overall the number of epitopes identified was very low compared to other hepatotropic viruses. We identified, two HLA-B*27-restricted epitopes in patients with resolved infections. In HLA-B*27-positive patients with chronic HDV infections, however, we detected escape mutations within these identified epitopes that could lead to viral evasion of immune responses. These findings support evidence showing that HLA-B*27 is important for virus-specific CD8 T cell responses, similar to other viral infections. These results have implications for the clinical prognosis of HDV infection and for vaccine development.

Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 84:1390-1407. © 2016 Wiley Periodicals, Inc.