140 research outputs found
Over de cyclus der zogenaamde drempelgeulen in de oostelijke uitloop van de Zimmermangeul
No full textReeds jarenlang vormt het Nauw van Bath in het bovenstroomse deel van de Westerschelde een der moeilijkst te bevaren geulgedeelten van de scheepvaartweg van en naar Antwerpen. Als gevolg van het verrichten van omvangrijke baggerwerken langs de noordoostelijke rand van de Plaat van Saaftinge (bijlage 1) heeft de in scheepvaartkringen beruchte Bocht van Bath de laatste jaren een wat gunstiger ligging verkregen. Het aan de benedenstroomse zijde van het Nauw van Bath optredende vloedstroombeeld (dwarsstromingen vanuit de Zimmermangeul) vormt echter een omstandigheid waarmee ook thans nog terdege rekening moet worden gehouden. In het begin van 1963 vond in het Nauw van Bath ter hoogte van de uitloop van de Zimmermangeul een ernstige scheepsramp plaats. De bewuste uitloop vertoonde toendertijd een opmerkelijk sterke ontwikkeling met een vooral bij springtij zeer ongunstige stromingssituatie. Voor de Antwerpse Zeediensten was de toenemende ontwikkeling van de Zimmermangeul overigens reeds in oktober 1962 reden een onderzoek naar het in dit gebied optredende stroombeeld te verrichten. De opgetreden scheepsramp vormde voor de Studiedienst Vlissingen de aanleiding een onderzoek naar de ontwikkelingen in ing. D. de Looff ir. J. van Malde dit gebied in te stellen
Understanding the Binding of Starch Fragments to Granule-Bound Starch Synthase
No full textGranule-bound starch synthase (GBSS) plays a major role, that of chain elongation, in the biosynthesis of amylose, a starch component with mostly (1 → 4)-α connected long chains of glucose with a few (1 → 6)-α branch points. Chain-length distributions (CLDs) of amylose affect functional properties, which can be controlled by changing appropriate residues on granule-bound starch synthase (GBSS). Knowing the binding of GBSS and amylose at a molecular level can help better determine the key amino acids on GBSS that affect CLDs of amylose for subsequent use in molecular engineering. Atomistic molecular dynamics simulations with explicit solvent and docking approaches were used in this study to build a model of the binding between rice GBSS and amylose. Amylose fragments containing 3-12 linearly linked glucose units were built to represent the starch fragments. The stability of the complexes, interactions between GBSS and sugars, and difference in structure/conformation of bound and free starch fragments were analyzed. The study found that starch/amylose fragments with 5 or 6 glucose units were suitable for modeling starch binding to GBSS. The removal of an interdomain disulfide on GBSS was found to affect both GBSS and starch stability. Key residues that could affect the binding ability were also indicated. This model can help rationalize the design of mutants and suggest ways to make single-point mutations, which could be used to develop plants producing starches with improved functional properties.Full Tex
Permeability of Dermatological Solutes through the Short Periodicity Phase of Human Stratum Corneum Lipid Bilayers
No full textDetermining the permeability of drug-like solutes through the densely packed and heterogeneous stratum corneum lipid layer presents a significant challenge. In this study, we employed umbrella sampling with a periodic weighing function applied to the center of mass of the lipid bilayers. Precise umbrella sampling was conducted with an interframe distance of 0.5 Å, spanning from the bilayer center to the water phase, and each frame was simulated for at least 20 ns. Autocorrelation functions, potential of mean force (PMF), and diffusivity profiles were analyzed for six solutes (testosterone, benzene, caffeine, ethanol, mannitol, and histidine). The results revealed that autocorrelations were dependent solely on the medium, whether water or lipid phase. Diffusivity and PMF profiles along the reaction coordinate were influenced by the hydrophilicity of the solute rather than its size. For hydrophobic solutes, the PMF curves exhibited a minimum at the bilayer center, while for hydrophilic solutes, the PMFs peaked at the bilayer center and lipid tails (where the lipid tails are not interacting with the cholesterol). Diffusivity curves were low at the bilayer center and water phase, with peaks observed at the headgroup or the boundary between fatty acid and cholesterol (1 nm from the bilayer center). The quantitative findings presented in this work hold significance for pharmacists and drug designers.No Full Tex
Development of a model for granule-bound starch synthase I activity using free-energy calculations
No full textStarch is a branched polymer of glucose with two components, both of which have (1 → 4)-α linear links and (1 → 6)-α branch points: amylopectin, of high molecular weight with many short branches, and amylose, of lower molecular weight and only a few long-chain branches. Granule-bound starch synthase I (GBSSI) is one of the main enzymes controlling amylose synthesis and chain-length distribution. As production of different GBSSI mutants is time-consuming and laborious, molecular dynamics (MD) simulations are used here to predict the binding of different GBSSI mutants to a representative amylose fragment. The simulations were atomistic, with explicit solvent and docking, a method successfully used to understand the binding of wild-type GBSSI to amylose fragments. The binding of GBSSI to G5 (a pentasaccharide amylose fragment) is combined with free-energy calculations employing a thermodynamic integration method to predict the effects of mutations on enzyme activity. Ten GBSSI mutants with different enzyme activities were analyzed to find the structural and energy changes among different single amino-acid mutants and their possible relationship to starch characteristics. Comparing the structural changes and the relative binding free energy of G5 to the wild type GBSSI and GBSSI mutants, it was found that mutants with negative binding energy (lower than -2.0 kcal/mol) are more likely to have higher enzyme activity and amylose content compared to the wild type. This theoretical paper used simulations and robust free energy calculations to interpret in planta data with potential predictions as to what mutants might be generated to give desired properties. This study can be used to help develop grains with improved functional properties.Full Tex
Learning epistatic interactions from sequence-activity data to predict enantioselectivity
No full textEnzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues
Effects of chickpea protein fractions on α-amylase activity in digestion
No full textThis study concerns the effects of endogenous proteins on starch digestion kinetics. It investigates the effects in chickpeas of hydrolysates released from the endogenous proteins albumin, globulin and glutelin on the in vitro activity of porcine pancreatic α-amylase (PPA) and on starch digestion. Using a docking simulation, potential proteinaceous α-amylase inhibitors (α-AIs) belonging to the small peptides of albumin, globulin and glutelin are identified and their binding mechanisms with PPA are explored. It was found that cooking and pepsin hydrolysis led to severe degradation of protein fractions, accompanied by the enrichment of small (<10 kDa) peptides, among which peptides <3 kDa exhibited strong inhibitory activity (up to 50%). Most of the active α-AIs were therefore considered to be found in the fractions <3 kDa, and were further characterized by mass spectrometry combined with in silico analysis. Docking results showed that glutelin could produce the most α-AIs (45 peptides), followed by globulin (41) and albumin (12). Among these, 71 peptides were predicted to exhibit a competitive or uncompetitive type of inhibition on PPA, whereas 6 peptides performed a noncompetitive inhibition. The competitive and uncompetitive α-AIs inhibited enzyme activity mainly by binding to a flexible loop and three major catalytic residues in PPA, and the latter by interacting with the non-catalytic regions of PPA. Different inhibition types therefore can together to hinder the formation of enzyme-starch complexes, so that PPA activity is inhibited and starch digestibility could be reduced.No Full Tex
Crystal structures of protein-bound cyclic peptides
No full textCyclization is an important post-translational modification of peptides and proteins that confers key advantages such as protection from proteolytic degradation, altered solubility, membrane permeability, bioavailability, and especially restricted conformational freedom in water that allows the peptide backbone to adopt the major secondary structure elements found in proteins. Non-ribosomal synthesis in bacteria, fungi, and plants or synthetic chemistry can introduce unnatural amino acids and non-peptidic constraints that modify peptide backbones and side chains to fine-tune cyclic peptide structure. Structures can be potentially altered further upon binding to a protein in biological environments. Here we analyze three-dimensional crystal structures for 211 bioactive cyclic peptides bound to 65 different proteins. The protein-bound cyclic peptides were examined for similarities and differences in bonding modes, for main-chain and side-chain structure, and for the importance of polarity, hydrogen bonds, hydrophobic effects, and water molecules in interactions with proteins. Many protein-bound cyclic peptides show backbone structures like those (strands, sheets, turns, helices, loops, or distorted variations) found at protein-protein binding interfaces. However, the notion of macrocycles simply as privileged scaffolds that primarily project side-chain substituents for complementary interactions with proteins is dispelled here. Unlike small-molecule drugs, the cyclic peptides do not rely mainly upon hydrophobic and van der Waals interactions for protein binding; they also use their main chain and side chains to form polar contacts and hydrogen bonds with proteins. Compared to small-molecule ligands, cyclic peptides can bind across larger, polar, and water-exposed protein surface areas, making many more contacts that can increase affinity, selectivity, biological activity, and ligand-receptor residence time. Cyclic peptides have a greater capacity than small-molecule drugs to modulate protein-protein interfaces that involve large, shallow, dynamic, polar, and water-exposed protein surfaces
Bisubstrate ether‐linked uridine‐peptide conjugates as O‐GlcNAc transferase inhibitors
No full textTheO-linked beta-N-acetylglucosamine (O-GlcNAc) transferase (OGT) is a master regulator of installingO-GlcNAc onto serine or threonine residues on a multitude of target proteins. Numerous nuclear and cytosolic proteins of varying functional classes, including translational factors, transcription factors, signaling proteins, and kinases are OGT substrates. AberrantO-GlcNAcylation of proteins is implicated in signaling in metabolic diseases such as diabetes and cancer. Selective and potent OGT inhibitors are valuable tools to study the role of OGT in modulating a wide range of effects on cellular functions. We report linear bisubstrate ether-linked uridine-peptide conjugates as OGT inhibitors with micromolar affinity.In vitroevaluation of the compounds revealed the importance of donor substrate, linker and acceptor substrate in the rational design of bisubstrate analogue inhibitors. Molecular dynamics simulations shed light on the binding of this novel class of inhibitors and rationalized the effect of amino acid truncation of acceptor peptide on OGT inhibition
Comparative occupancy analysis (CoOAn)- a straightforward and directly applicable 3D-QSAR formalism to extract molecular features obligatory for designing potent leads
No full textA simple and directly applicable 3D-QSAR method, termed Comparative Occupancy Analysis (CoOAn), has been developed. The method is based on the comparison of local occupancies of fragments of an aligned set of molecules in a 3D-grid space. The formalism commendably extracts the crucial position-specific molecular features and correlates them quantitatively to their biological endpoints. The method has been effectively applied and efficaciously validated on three large and diverse datasets?thrombin, glycogen phosphorylase b (GPB), and thermolysin inhibitors. Several robust and statistically significant predictive 3D-QSAR models were developed while simultaneously considering the influence of grid spacing on the accuracy of the results. The models, generated by the G/PLS chemometric method, not only unswervingly identified the obligatory chemical features but advantageously detected those that are unfavourable or detrimental for the molecular activity. The CoOAn models can profitably be used to optimize existing molecules as well as to design new leads with more desirable (and/or less detrimental) features. The activity-modulating features (together with their distance-constraints) extracted by the methodology can also be incorporated into a pharmacophore-type query to search a chemical database for novel leads
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