The RNA-Bound Conformation of Neamine as Determined by Transferred NOE Experiments

Optimization of Experimental Parameters to Explore Small-Ligand/Aptamer Interactions through Use of (1) H NMR Spectroscopy and Molecular Modeling

Aptamers constitute an emerging class of molecules designed and selected to recognize any given target that ranges from small compounds to large biomolecules, and even cells. However, the underlying physicochemical principles that govern the ligand-binding process still have to be clarified. A major issue when dealing with short oligonucleotides is their intrinsic flexibility that renders their active conformation highly sensitive to experimental conditions. To overcome this problem and determine the best experimental parameters, an approach based on the design-of-experiments methodology has been developed. Here, the focus is on DNA aptamers that possess high specificity and affinity for small molecules, L-tyrosinamide, and adenosine monophosphate. Factors such as buffer, pH value, ionic strength, Mg(2+) -ion concentration, and ligand/aptamer ratio have been considered to find the optimal experimental conditions. It was then possible to gain new insight into the conformational features of the two ligands by using ligand-observed NMR spectroscopic techniques and molecular mechanics.

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.