Synthetic Receptors for the High-Affinity Recognition of O-GlcNAc Derivatives

The combination of a pyrenyl tetraamine with an isophthaloyl spacer has led to two new water-soluble carbohydrate receptors ("synthetic lectins"). Both systems show outstanding affinities for derivatives of N-acetylglucosamine (GlcNAc) in aqueous solution. One receptor binds the methyl glycoside GlcNAc-β-OMe with Ka ≈20,000 m(-1), whereas the other one binds an O-GlcNAcylated peptide with Ka ≈70,000 m(-1). These values substantially exceed those usually measured for GlcNAc-binding lectins. Slow exchange on the NMR timescale enabled structural determinations for several complexes. As expected, the carbohydrate units are sandwiched between the pyrenes, with the alkoxy and NHAc groups emerging at the sides. The high affinity of the GlcNAcyl-peptide complex can be explained by extra-cavity interactions, raising the possibility of a family of complementary receptors for O-GlcNAc in different contexts

The role of homophilic binding in anti-tumor antibody R24 recognition of molecular surfaces. Demonstration of an intermolecular beta-sheet interaction between vh domains.

The murine antibody R24 and mouse-human Fv-IgG1(kappa) chimeric antibody chR24 are specific for the cell-surface tumor antigen disialoganglioside GD3. X-ray diffraction and surface plasmon resonance experiments have been employed to study the mechanism of "homophilic binding," in which molecules of R24 recognize and bind to other molecules of R24 though their heavy chain variable domains. R24 exhibits strong binding to liposomes containing disialoganglioside GD3; however, the kinetics are unusual in that saturation of binding is not observed. The binding of chR24 to GD3-bearing liposomes is significantly weaker, suggesting that cooperative interactions involving antibody constant regions contribute to R24 binding of membrane-bound GD3. The crystal structures of the Fabs from R24 and chR24 reveal the mechanism for homophilic binding and confirm that the homophilic and antigen-binding idiotopes are distinct. The homophilic binding idiotope is formed largely by an anti-parallel beta-sheet dimerization between the H2 complementarity determining region (CDR) loops of two Fabs, while the antigen-binding idiotope is a pocket formed by the three CDR loops on the heavy chain. The formation of homophilic dimers requires the presence of a canonical conformation for the H2 CDR in conjunction with participation of side chains. The relative positions of the homophilic and antigen-binding sites allows for a lattice of GD3-specific antibodies to be constructed, which is stabilized by the presence of the cell membrane. This model provides for the selective recognition by R24 of cells that overexpress GD3 on the cell surface

Enantioselective carbohydrate recognition by synthetic lectins in water

These chiral “synthetic lectins” are the first to discriminate between carbohydrate enantiomers, and also show unprecedented affinities for monosaccharide substrates.</p

A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management

Evaluation of receptor and chemical transport models for PM10 source apportionment

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models

Assessment of technological options and economical feasibility for cyanophycin biopolymer and high-value amino acid production

Major transitions can be expected within the next few decades aiming at the reduction of pollution and global warming and at energy saving measures. For these purposes, new sustainable biorefinery concepts will be needed that will replace the traditional mineral oil-based synthesis of specialty and bulk chemicals. An important group of these chemicals are those that comprise N-functionalities. Many plant components contained in biomass rest or waste stream fractions contain these N-functionalities in proteins and free amino acids that can be used as starting materials for the synthesis of biopolymers and chemicals. This paper describes the economic and technological feasibility for cyanophycin production by fermentation of the potato waste stream Protamylasse™ or directly in plants and its subsequent conversion to a number of N-containing bulk chemicals

Identification of emulsifier potato peptides by bioinformatics: application to omega-3 delivery emulsions and release from potato industry side streams

We are grateful for the financial support from Innovation Fund Denmark (Grant nr: 7045-00021B, PROVIDE project). We also acknowledge K.M.C. amba (Brande, Denmark) and A.K.V. amba (Langholt, Denmark) for providing the potato samples used in this study.In this work, we developed a novel approach combining bioinformatics, testing of functionality and bottom-up proteomics to obtain peptide emulsifiers from potato side-streams. This is a significant advancement in the process to obtain emulsifier peptides and it is applicable to any type of protein. Our results indicated that structure at the interface is the major determining factor of the emulsifying activity of peptide emulsifiers. Fish oil-in-water emulsions with high physical stability were stabilized with peptides to be predicted to have facial amphiphilicity: (i) peptides with predominantly α-helix conformation at the interface and having 18–29 amino acids, and (ii) peptides with predominantly β-strand conformation at the interface and having 13–15 amino acids. In addition, high physically stable emulsions were obtained with peptides that were predicted to have axial hydrophobic/hydrophilic regions. Peptides containing the sequence FCLKVGV showed high in vitro antioxidant activity and led to emulsions with high oxidative stability. Peptide-level proteomics data and sequence analysis revealed the feasibility to obtain the potent emulsifier peptides found in this study (e.g. γ-1) by trypsin-based hydrolysis of different side streams in the potato industry.Innovation Fund Denmark 7045-00021

Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSEu, with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSEu accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSEu are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSEu tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSEu was in the range 25% - 34%.JRC.C.5-Air and Climat