Identification of antiparasitic drug targets using a multi-omics workflow in the acanthocephalan model.

BACKGROUND: With the expansion of animal production, parasitic helminths are gaining increasing economic importance. However, application of several established deworming agents can harm treated hosts and environment due to their low specificity. Furthermore, the number of parasite strains showing resistance is growing, while hardly any new anthelminthics are being developed. Here, we present a bioinformatics workflow designed to reduce the time and cost in the development of new strategies against parasites. The workflow includes quantitative transcriptomics and proteomics, 3D structure modeling, binding site prediction, and virtual ligand screening. Its use is demonstrated for Acanthocephala (thorny-headed worms) which are an emerging pest in fish aquaculture. We included three acanthocephalans (Pomphorhynchus laevis, Neoechinorhynchus agilis, Neoechinorhynchus buttnerae) from four fish species (common barbel, European eel, thinlip mullet, tambaqui). RESULTS: The workflow led to eleven highly specific candidate targets in acanthocephalans. The candidate targets showed constant and elevated transcript abundances across definitive and accidental hosts, suggestive of constitutive expression and functional importance. Hence, the impairment of the corresponding proteins should enable specific and effective killing of acanthocephalans. Candidate targets were also highly abundant in the acanthocephalan body wall, through which these gutless parasites take up nutrients. Thus, the candidate targets are likely to be accessible to compounds that are orally administered to fish. Virtual ligand screening led to ten compounds, of which five appeared to be especially promising according to ADMET, GHS, and RO5 criteria: tadalafil, pranazepide, piketoprofen, heliomycin, and the nematicide derquantel. CONCLUSIONS: The combination of genomics, transcriptomics, and proteomics led to a broadly applicable procedure for the cost- and time-saving identification of candidate target proteins in parasites. The ligands predicted to bind can now be further evaluated for their suitability in the control of acanthocephalans. The workflow has been deposited at the Galaxy workflow server under the URL tinyurl.com/yx72rda7 .

Simulation of the Positive Inotropic Peptide S100A1ct in Aqueous Environment by Gaussian Accelerated Molecular Dynamics.

The S100A1ct peptide, consisting of the C-terminal 20 residues of the S100A1 protein fused to an N-terminal 6-residue hydrophilic tag, has been found to exert a positive inotropic effect, resulting in improved contractile performance of failing cardiac and skeletal muscle without arrhythmic side-effects. The S100A1ct peptide thus has high potential for the treatment of acute heart failure. As a step toward understanding its molecular mechanism of action, and to provide a basis for peptidomimetic design to optimize its properties, we here describe de novo structure predictions and molecular dynamics simulations to characterize the conformational landscape of S100A1ct in aqueous environment. In S100A1, the C-terminal 20 residues form an α-helix, but de novo peptide structure predictions indicate that other conformations are also possible. Conventional molecular dynamics simulations in implicit and explicit solvent corroborated this finding. To ensure adequate sampling, we performed simulations of a tagged 10-residue segment of S100A1ct, and we carried out Gaussian accelerated molecular dynamics simulations of the peptides. These simulations showed that although the helical conformation of S100A1ct was the most energetically stable, the peptide can adopt a range of kinked conformations, suggesting that its activity may be related to its ability to act as a conformational switch.

Simulation-based evaluation of operating room management policies.

BACKGROUND: Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg. METHODS: Based on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries. RESULTS: We identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators. CONCLUSIONS: Our simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner.

Key Features Relevant to Select Antigens and TCR From the MHC-Mismatched Repertoire to Treat Cancer.

Adoptive transfer of T cells transgenic for tumor-reactive T-cell receptors (TCR) is an attractive immunotherapeutic approach. However, clinical translation is so far limited due to challenges in the identification of suitable target antigens as well as TCRs that are concurrent safe and efficient. Definition of key characteristics relevant for effective and specific tumor rejection is essential to improve current TCR-based adoptive T-cell immunotherapies. We here characterized in-depth two TCRs derived from the human leukocyte antigen (HLA)-mismatched allogeneic repertoire targeting two different myeloperoxidase (MPO)-derived peptides presented by the same HLA-restriction element side by side comprising state of the art biochemical and cellular in vitro, in vivo, and in silico experiments. In vitro experiments reveal comparable functional avidities, off-rates, and cytotoxic activities for both TCRs. However, we observed differences especially with respect to cytokine secretion and cross-reactivity as well as in vivo activity. Biochemical and in silico analyses demonstrate different binding qualities of MPO-peptides to the HLA-complex determining TCR qualities. We conclude from our biochemical and in silico analyses of peptide-HLA-binding that rigid and high-affinity binding of peptides is one of the most important factors for isolation of TCRs with high specificity and tumor rejection capacity from the MHC-mismatched repertoire. Based on our results, we developed a workflow for selection of such TCRs with high potency and safety profile suitable for clinical translation.

Predicting the bioactive conformations of macrocycles: a molecular dynamics-based docking procedure with DynaDock.

Macrocyclic compounds are of growing interest as a new class of therapeutics, especially as inhibitors binding to protein-protein interfaces. As molecular modeling is a well-established complimentary tool in modern drug design, the number of attempts to develop reliable docking strategies and algorithms to accurately predict the binding mode of macrocycles is rising continuously. Standard molecular docking approaches need to be adapted to this application, as a comprehensive yet efficient sampling of all ring conformations of the macrocycle is necessary. To overcome this issue, we designed a molecular dynamics-based docking protocol for macrocycles, in which the challenging sampling step is addressed by conventional molecular dynamics (750 ns) simulations performed at moderately high temperature (370 K). Consecutive flexible docking with the DynaDock approach based on multiple, pre-sampled ring conformations yields highly accurate poses with ligand RMSD values lower than 1.8 Å. We further investigated the value of molecular dynamics-based complex stability estimations for pose selection and discuss its applicability in combination with standard binding free energy estimations for assessing the quality of poses in future blind docking studies.

Automated Classification of Airborne Pollen using Neural Networks.

Pollen allergies are considered as a global epidemic nowadays, as they influence more than a quarter of the worldwide population, with this percentage expected to rapidly increase because of ongoing climate change. To date, alerts on high-risk allergenic pollen exposure have been provided only via forecasting models and conventional monitoring methods that are laborious. The aim of this study is to develop and evaluate our own pollen classification model based on deep neural networks. Airborne allergenic pollen have been monitored in Augsburg, Bavaria, Germany, since 2015, using a novel automatic Bio-Aerosol Analyzer (BAA 500, Hund GmbH). The automatic classification system is compared and evaluated against our own, newly developed algorithm. Our model achieves an unweighted average precision of 83.0 % and an unweighted average recall of 77.1 % across 15 classes of pollen taxa. Automatic, real-time information on concentrations of airborne allergenic pollen will significantly contribute to the implementation of timely, personalized management of allergies in the future. It is already clear that new methods and sophisticated models have to be developed so as to successfully switch to novel operational pollen monitoring techniques serving the above need.

Ca2+ binding induced sequential allosteric activation of sortase A: An example for ion-triggered conformational selection.

The allosteric activation of the intrinsically disordered enzyme Staphylococcus aureus sortase A is initiated via binding of a Ca2+ ion. Although Ca2+ binding was shown to initiate structural changes inducing disorder-to-order transitions, the details of the allosteric activation mechanism remain elusive. We performed long-term molecular dynamics simulations of sortase A without (3 simulations of 1.6 µs) and with bound Ca2+ (simulations of 1.6 µs, 1.8 µs, and 2.5 µs). Our results show that Ca2+ binding causes not only ordering of the disordered ß6/ß7 loop of the protein, but also modulates hinge motions in the dynamic ß7/ß8 loop, which is important for the catalytic activity of the enzyme. Cation binding triggers signal transmission from the Ca2+ binding site to the dynamic ß7/ß8 loop via the repetitive folding/unfolding of short helical stretches of the disordered ß6/ß7 loop. These correlated structural rearrangements lead to several distinct conformational states of the binding groove, which show optimal binding features for the sorting signal motif and feature binding energies up to 20 kcal/mol more favorable than observed for the sortase A without Ca2+. The presented results indicate a highly correlated, conformational selection-based activation mechanism of the enzyme triggered by cation binding. They also demonstrate the importance of the dynamics of intrinsically disordered regions for allosteric regulation.

Amino Acid Substitutions within HLA-B*27-Restricted T Cell Epitopes Prevent Recognition by Hepatitis Delta Virus-Specific CD8+ T Cells.

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 in silico 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.IMPORTANCE 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.

Gliotoxin Biosynthesis: Structure, Mechanism, and Metal Promiscuity of Carboxypeptidase GliJ.

The formation of glutathione (GSH) conjugates, best known from the detoxification of xenobiotics, is a widespread strategy to incorporate sulfur into biomolecules. The biosynthesis of gliotoxin, a virulence factor of the human pathogenic fungus Aspergillus fumigatus, involves attachment of two GSH molecules and their sequential decomposition to yield two reactive thiol groups. The degradation of the GSH moieties requires the activity of the Cys-Gly carboxypeptidase GliJ, for which we describe the X-ray structure here. The enzyme forms a homodimer with each monomer comprising one active site. Two metal ions are present per proteolytic center, thus assigning GliJ to the diverse family of dinuclear metallohydrolases. Depending on availability, Zn2+, Fe2+, Fe3+, Mn2+, Cu2+, Co2+, or Ni2+ ions are accepted as cofactors. Despite this high metal promiscuity, a preference for zinc versus iron and manganese was noted. Mutagenesis experiments revealed details of metal coordination, and molecular modeling delivered insights into substrate recognition and processing by GliJ. The latter results suggest a reaction mechanism in which the two scissile peptide bonds of one gliotoxin precursor molecule are hydrolyzed sequentially and in a given order.

BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.

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.

Sequential Inactivation of Gliotoxin by the S-Methyltransferase TmtA.

The epipolythiodioxopiperazine (ETP) gliotoxin mediates toxicity via its reactive thiol groups and thereby contributes to virulence of the human pathogenic fungus Aspergillus fumigatus. Self-intoxication of the mold is prevented either by reversible oxidation of reduced gliotoxin or by irreversible conversion to bis(methylthio)gliotoxin. The latter is produced by the S-methyltransferase TmtA and attenuates ETP biosynthesis. Here, we report the crystal structure of TmtA in complex with S-(5'-adenosyl)-l-homocysteine. TmtA features one substrate and one cofactor binding pocket per protein, and thus, bis-thiomethylation of gliotoxin occurs sequentially. Molecular docking of substrates and products into the active site of TmtA reveals that gliotoxin forms specific interactions with the protein surroundings, and free energy calculations indicate that methylation of the C10a-SH group precedes alkylation of the C3-SH site. Altogether, TmtA is well suited to selectively convert gliotoxin and to control its biosynthesis, suggesting that homologous enzymes serve to regulate the production of their toxic natural sulfur compounds in a similar manner.

Phenyl Esters Are Potent Inhibitors of Caseinolytic Protease P and Reveal a Stereogenic Switch for Deoligomerization.

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.