A kinetic analysis of the tumor-associated galactopyranosyl-(1→3)-2-acetamido-2-deoxy-α-d-galactopyranoside antigen—lectin interaction

Note: Model identification and analysis of bivalent analyte surface plasmon resonance data

Surface plasmon resonance (SPR) is a widely used, affinity based, label-free biophysical technique to investigate biomolecular interactions. The extraction of rate constants requires accurate identification of the particular binding model. The bivalent analyte model involves coupled non-linear differential equations. No clear procedure to identify the bivalent analyte mechanism has been established. In this report, we propose a unique signature for the bivalent analyte model. This signature can be used to distinguish the bivalent analyte model from other biphasic models. The proposed method is demonstrated using experimentally measured SPR sensorgrams.

Study of carbohydrate-protein interactions using glyco-QDs with different fluorescence emission wavelengths

QDs with different fluorescence emission wavelengths were coated with galactose, glucose, and lactose respectively. The formulas of glyco-QDs were determined by NMR and ICP-OES, and the interactions between glyco-QDs and PNA lectin were investigated by SPR. The results showed that multivalent presentation achieved by using QDs as the scaffold is an effective way to enhance the carbohydrate-protein interactions. The K(D) for the interaction of PNA with multivalent glyco-QDs is over 3 × 10(6)-fold lower than those with the same free sugars. The specific recognition for the sugar coated on the QDs by lectin is maintained. These sugar-coated QDs could be used as a fluorescent probe to label and identify glycoproteins.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2007-2008

This review is the fifth update of the original review, published in 1999, on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2008. The first section of the review covers fundamental studies, fragmentation of carbohydrate ions, use of derivatives and new software developments for analysis of carbohydrate spectra. Among newer areas of method development are glycan arrays, MALDI imaging and the use of ion mobility spectrometry. The second section of the review discusses applications of MALDI MS to the analysis of different types of carbohydrate. Specific compound classes that are covered include carbohydrate polymers from plants, N- and O-linked glycans from glycoproteins, biopharmaceuticals, glycated proteins, glycolipids, glycosides and various other natural products. There is a short section on the use of MALDI mass spectrometry for the study of enzymes involved in glycan processing and a section on the use of MALDI MS to monitor products of the chemical synthesis of carbohydrates with emphasis on carbohydrate-protein complexes and glycodendrimers. Corresponding analyses by electrospray ionization now appear to outnumber those performed by MALDI and the amount of literature makes a comprehensive review on this technique impractical. However, most of the work relating to sample preparation and glycan synthesis is equally relevant to electrospray and, consequently, those proposing analyses by electrospray should also find material in this review of interest.

Grading the commercial optical biosensor literature-Class of 2008: 'The Mighty Binders'

Optical biosensor technology continues to be the method of choice for label-free, real-time interaction analysis. But when it comes to improving the quality of the biosensor literature, education should be fundamental. Of the 1413 articles published in 2008, less than 30% would pass the requirements for high-school chemistry. To teach by example, we spotlight 10 papers that illustrate how to implement the technology properly. Then we grade every paper published in 2008 on a scale from A to F and outline what features make a biosensor article fabulous, middling or abysmal. To help improve the quality of published data, we focus on a few experimental, analysis and presentation mistakes that are alarmingly common. With the literature as a guide, we want to ensure that no user is left behind.