Novel imprinted polymers as artificial enzymes

Derivatives of L-histidine were investigated as suitable models for the Asp-His couple found in the catalytic triad of serine proteases. A combination of molecular dynamics and IH NMR spectroscopy suggested that the most populous conformations of N-acetyl-L-histidine and the N-acetyl-L-histidine anion were predominated by those in which the carboxylate group was gauche to the imidazole ring overcoming steric and electrostatic repulsion, suggesting there is an interaction between the carboxylate group and the imidazole ring. Kinetic studies, using imidazole, N-acetyl-L-histidine and the N-acetyl-L-histidine anion showed that in a DMSO/H20 9: 1 v/v solution, the N-acetyl-L-histidine anion catalysed the hydrolysis of p-nitrophenyl acetate at a greater rate than using either imidazole or N-acetyl-L-histidine as catalyst. This indicates that the carboxylate group affects the nucleophilicity of the unprotonated imidazole ring. 31P MAS NMR spectroscopy was investigated as a new technique for the study of the template molecule environment within the polymer networks. It was found that it was possible to distinguish between template associated with the polymer and that which was precipitated onto the surface, though it was not possible to distinguish between polymer within imprinted cavities and that which was not. Attempts to study the effect of the carboxylate group/imidazole ring interaction in the imprinted cavity of a molecularly imprinted polymer network were hindered by the method used to follow the reaction. It was found though that in a pH 8.0 buffered solution the presence of imprinted cavities increased the rate of reaction for those polymers derived from L-histidine. Some preliminary investigations into the design and synthesis of an MIP which would catalyse the oxy-Cope rearrangement were carried out but the results were inconclusive

Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases

Background Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics. Methods We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case–control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses. Results Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. Conclusions These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity

Comparative quantification of the surfaceome of human multipotent mesenchymal progenitor cells

SummaryMesenchymal progenitor cells have great therapeutic potential, yet incomplete characterization of their cell-surface interface limits their clinical exploitation. We have employed subcellular fractionation with quantitative discovery proteomics to define the cell-surface interface proteome of human bone marrow mesenchymal stromal/stem cells (MSCs) and human umbilical cord perivascular cells (HUCPVCs). We compared cell-surface-enriched fractions from MSCs and HUCPVCs (three donors each) with adult mesenchymal fibroblasts using eight-channel isobaric-tagging mass spectrometry, yielding relative quantification on >6,000 proteins with high confidence. This approach identified 186 upregulated mesenchymal progenitor biomarkers. Validation of 10 of these markers, including ROR2, EPHA2, and PLXNA2, confirmed upregulated expression in mesenchymal progenitor populations and distinct roles in progenitor cell proliferation, migration, and differentiation. Our approach has delivered a cell-surface proteome repository that now enables improved selection and characterization of human mesenchymal progenitor populations