Folding a Polymer via Two-Point Interaction with an External Folding Agent: Use of H-Bonding and Charge-Transfer Interactions

A polymer containing electron-rich aromatic donors (1,5-dialkoxynaphthalene (DAN)) was coerced into a folded state by an external folding agent that contained an electron-deficient aromatic acceptor (pyromellitic diimide (PM)) unit. The donor-containing polymer was designed to carry a tertiary amine moiety in the linking segment, which served as an H-bonding site for reinforcing the interaction with the acceptor containing folding agent that also bore a carboxylic acid group. The H-bonding interaction of the carboxylic acid and the tertiary amine brings the PDI unit between two adjacent DAN units along the polymer backbone to induce charge-transfer (C-T) interactions, and this in turn causes the polymer chain to form a pleated structure. Evidence for the formation of such a pleated structure was obtained from NMR titration studies and also by monitoring the C-T band in their UV-visible spectra. By varying the length of the segment that links the PDI acceptor to the carboxylic acid group, we showed that the most effective folding agent was the one that had a single carbon spacer, as evident from the highest value of the association constant. Control experiments with propionic acid clearly demonstrated the importance of the additional C-T interactions for venerating the folded structures. Further, solution viscosity measurements in the presence of varying amounts of the folding agent revealed a gradual stiffening of the chain in the case of the PDI carrying carboxylic acid, whereas no such affect was seen in the case of simple propionic acid. These observations were supported by D FT calculations of the interactions of a dimeric model of the polymer with the various folding agents; here too the stability of the complex was seen to be highest in the case of the single carbon spacer.

Studies on interaction of colloidal Ag nanoparticles with Bovine Serum Albumin (BSA)

Biofunctionalization of noble metal nanoparticles like Ag, Au is essential to obtain biocompatibility for specific biomedical applications. Silver nanciparticles are being increasingly used in bio-sensing applications owing to excellent optoelectronic properties. Among the serum albumins, the most abundant proteins in plasma, a wide range of physiological functions of Bovine Serum Albumin (BSA) has made it a model system for biofunctionalization. In absence of adequate prior reports, this study aims to investigate the interaction between silver nanoparticles and BSA. The interaction of BSA [0.05-0.85% concentrations] with Ag nanoparticles [50 ppm concentration] in aqueous dispersion was Studied through UV-vis spectral changes, morphological and surface structural changes. At pH 7, which is More than the isoelectric point of BSA, a decrease in absorbance at plasmon peak of uninteracted nanciparticles (425 mn) was noted till 0.45% BSA, beyond that a blue shift towards 410 urn was observed. The blue shift may be attributed to enhanced electron density on the particle surfaces. Increasing pH to 12 enhanced the blue shift further to 400 rim. The conformational changes in BSA at alkaline pH ranges and consequent hydrophobic interactions also played an important role. The equilibrium adsorption data fitted better to Freundlich isotherm compared to Langmuir Curve. The X-ray diffraction study revealed complete coverage of Ag nanoparticles by BSA. The scanning electron microscopic study of the interacted nanoparticles was also carried Out to decipher morphological changes. This study established that tailoring the concentration of BSA and pH of the interaction it was possible to reduce aggregation of nanoparticles. Biofunctionalized Ag nanoparticles with reduced aggregation will be more amenable towards bio-sensing applications. (C) 2009 Elsevier B.V. All rights reserved.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Kinetics and the mechanism of interaction of the endoplasmic reticulum chaperone, calreticulin, with monoglucosylated (Glc(1)Man(9)GlcNAc(2)) substrate

Calreticulin is a lectin-like molecular chaperone of the endoplasmic reticulum in eukaryotes. Its interaction with N-glycosylated polypeptides is mediated by the glycan, Glc(1)Man(9)GlcNAc(2), present on the target glycoproteins. In this work, binding of monoglucosyl IgG (chicken) substrate to calreticulin has been studied using real time association kinetics of the interaction with the biosensor based on surface plasmon resonance (SPR). By SPR, accurate association and dissociation rate constants were determined, and these yielded a micromolar association constant. The nature of reaction was unaffected by immobilization of either of the reactants. The Scatchard analysis values for K-a agreed web crith the one obtained by the ratio k(1)/k(-1). The interaction was completely inhibited by free oligosaccharide, Glc(1)Man(9)GlcNAc(2), whereas Man(9)GlcNAc(2) did not bind to the calreticulin-substrate complex, attesting to the exquisite specificity of this interaction. The binding of calreticulin to IgG was used for the development of immunoassay and the relative affinity of the lectin-substrate association was indirectly measured. The values are in agreement with those obtained with SPR. Although the reactions are several orders of magnitude slower than the diffusion controlled processes, the data are qualitatively and quantitatively consistent with single-step bimolecular association and dissociation reaction. Analyses of the activation parameters indicate that reaction is enthalpically driven and does not involve a highly ordered transition state. Based on these data, the mechanism of its chaperone activity is briefly discussed.