Although aluminium acetylacetonate, Al(C5H7O2)3, is a common precursor for chemical vapor deposition (CVD) of aluminium oxide, its gas phase decomposition is not very well investigated. Here, we studied its thermal...

Endocannabinoids, an important class of signaling lipids involved in health and disease, are predominantly synthesized and metabolized by enzymes of the serine hydrolase superfamily. Activity-based protein profiling (ABPP) using fluorescent probes, such as fluorophosphonate (FP)-TAMRA and β-lactone-based MB064, enables drug discovery activities for serine hydrolases. FP-TAMRA and MB064 have distinct, albeit partially overlapping, target profiles but cannot be used in conjunction due to overlapping excitation/emission spectra. We therefore synthesized a novel FP-probe with a green BODIPY as a fluorescent tag and studied its labeling profile in mouse proteomes. Surprisingly, we found that the reporter tag plays an important role in the binding potency and selectivity of the probe. A multiplexed ABPP assay was developed in which a probe cocktail of FP-BODIPY and MB064 visualized most endocannabinoid serine hydrolases in mouse brain proteomes in a single experiment. The multiplexed ABPP assay was employed to profile endocannabinoid hydrolase inhibitor activity and selectivity in the mouse brain.

The chemical reactions used to make antibody-DNA conjugates in many immunoassays diminish antigen-binding activity and yield heterogeneous products. Here, we address these issues by developing an antibody-based rolling circle amplification (RCA) strategy using a fusion of φX174 gene A* protein and Z(mab25) (A*-Zmab). The φX174 gene A* protein is an enzyme that can covalently link with DNA, while the Z(mab25) protein moiety can bind to specific species of antibodies. The DNA in an A*-Zmab conjugate was attached to the A* protein at a site chosen to not interfere with protein function, as determined by enzyme-linked immunosorbent assay (ELISA) and gel mobility shift analysis. The novel A*-Zmab-DNA conjugate retained its binding capabilities to a specific class of murine immunoglobulin γ1 (IgG1) but not to rabbit IgG. This indicates the generality of the A*-Zmab-based immuno-RCA assay that can be used in-sandwich ELISA format. Moreover, the enzymatic covalent method dramatically increased the yields of A*-Zmab-DNA conjugates up to 80% after a 15 min reaction. Finally, sensitive detection of human interferon-γ (IFN-γ) was achieved by immuno-RCA using our fusion protein in sandwich ELISA format. This new approach of the use of site-specific enzymatic DNA conjugation to proteins should be applicable to fabrication of novel immunoassays for biosensing.

The interpretation of high-dimensional structure–activity data sets in drug discovery to predict ligand–protein interaction landscapes is a challenging task. Here we present Drug Discovery Maps (DDM), a machine learning model that maps the activity profile of compounds across an entire protein family, as illustrated here for the kinase family. DDM is based on the t -distributed stochastic neighbor embedding (t-SNE) algorithm to generate a visualization of molecular and biological similarity. DDM maps chemical and target space and predicts the activities of novel kinase inhibitors across the kinome. The model was validated using independent data sets and in a prospective experimental setting, where DDM predicted new inhibitors for FMS-like tyrosine kinase 3 (FLT3), a therapeutic target for the treatment of acute myeloid leukemia. Compounds were resynthesized, yielding highly potent, cellularly active FLT3 inhibitors. Biochemical assays confirmed most of the predicted off-targets. DDM is further unique in that it is completely open-source and available as a ready-to-use executable to facilitate broad and easy adoption.

Affinity reagents recognizing constant parts of antibody molecules are invaluable tools in immunotechnology applications, including purification, immobilization, and detection of immunoglobulins. In this article, murine IgG1, the primary isotype of monoclonal antibodies (mAbs) was used as target for selection of novel binders from a combinatorial ribosome display (RD) library of 1011 affibody molecules. Four rounds of selection using three different mouse IgG1 mAbs as alternating targets resulted in the identification of binders with broad mIgG1 recognition and dissociation constants (KD) in the low nanomolar to low micromolar range. For one of the binders, denoted Zmab25, competition in binding to full length mIgG1 by a streptococcal protein G (SPG) fragment and selective affinity capture of mouse IgG1 Fab fragments after papain cleavage of a full mAb suggest that an epitope functionally overlapping with the SPG-binding site in the CH1 domain of mouse IgG1 had been addressed. Interestingly, biosensor-based binding experiments showed that neither human IgG1 nor bovine Ig, the latter present in fetal bovine serum (FBS) was recognized by Zmab25. This selective binding profile towards murine IgG1 was successfully exploited in species selective recovery of two different mouse mAbs from complex samples containing FBS, resembling a hybridoma culture supernatant.

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Phospholipase A2, group XVI (PLA2G16) is a thiol hydrolase from the HRASLS family that regulates lipolysis in adipose tissue and has been identified as a host factor enabling the cellular entry of picornaviruses. Chemical tools are essential to visualize and control PLA2G16 activity, but they have not been reported to date. Here, we show that MB064, which is a fluorescent lipase probe, also labels recombinant and endogenously expressed PLA2G16. Competitive activity-based protein profiling (ABPP) using MB064 enabled the discovery of α-ketoamides as the first selective PLA2G16 inhibitors. LEI110 was identified as a potent PLA2G16 inhibitor (Ki = 20 nM) that reduces cellular arachidonic acid levels and oleic acid-induced lipolysis in human HepG2 cells. Gel-based ABPP and chemical proteomics showed that LEI110 is a selective pan-inhibitor of the HRASLS family of thiol hydrolases (i.e., PLA2G16, HRASLS2, RARRES3 and iNAT). Molecular dynamic simulations of LEI110 in the reported crystal structure of PLA2G16 provided insight in the potential ligand–protein interactions to explain its binding mode. In conclusion, we have developed the first selective inhibitor that can be used to study the cellular role of PLA2G16.

The molecular basis underlying T-cell recognition of MHC molecules presenting altered peptide ligands is still not well-established. A hierarchy of T-cell activation by MHC class I-restricted altered peptide ligands has been defined using the T-cell receptor P14 specific for H-2D b in complex with the immunodominant lymphocytic choriomeningitis virus peptide gp33 (KAVYNFATM). While substitution of tyrosine to phenylalanine (Y4F) or serine (Y4S) abolished recognition by P14, the TCR unexpectedly recognized H-2D b incomplex with the alanine-substituted semiagonist Y4A, which displayed the most significant structural modification. The observed functional hierarchy gp33 > Y4A > Y4S = Y4F was neither due to higher stabilization capacity nor to differences in structural conformation. However, thermodynamic analysis demonstrated that while recognition of the full agonist H-2D b /gp33 was strictly enthalpy driven, recognition of the weak agonist H-2D b /Y4A was instead entropy driven with a large reduction in the favorable enthalpy term. The fourfold larger negative heat capacity derived for the interaction of P14 with H-2D b /gp33 compared with H-2D b /Y4A can possibly be explained by higher water entrapment at the TCR/MHC interface, which is also consistent with the measured opposite entropy contributions for the interactions of P14 with both MHCs. In conclusion, this study demonstrates that P14 makes use of different strategies to adapt to structural modifications in the MHC/peptide complex.Keywords: MHC r Molecular immunology r Protein-protein interactions r Structural biology r TCR Supporting Information available online IntroductionRecognition of MHC molecules bound to peptides (pMHCs) by TCRs is a critical step for the initiation of T-cell responses.Correspondence: Dr. Adnane Achour e-mail: adnane.achour@ki.seAlthough this interaction is considered as highly specific, it is now well established that TCRs may also recognize other pMHCs [1][2][3][4][5][6].The activation of T cells can be modulated by alterations in the presented peptides [7,8], the CDR loops of the TCR [9] and the * These authors contributed equally to this work. * * These authors shared seniour authorship.C 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.eji-journal.eu Eur. J. Immunol. 2012. 42: 2990 Molecular immunology 2991 α 1 α 2 -domains of MHC molecules [10][11][12][13]. Depending on the quality of the triggered immune responses, APLs can be classified as: (i) agonists with the capacity to trigger a full range of T-cell activation events including TCR downregulation, cytokine production, granule release, and proliferation; (ii) weak agonists with the ability to induce lower magnitudes of TCR activation; (iii) partial agonists that may evoke a fraction of the events that characterize full T-cell activation; (iv) null peptides with no effect; or (v) antagonists that inhibit immune responses triggered by agonists. The slowly increasing number of TCR/pMHC crystal structures has started to provide important insights into a few common struc...