7 research outputs found
Development of a Tetrameric Streptavidin Mutein with Reversible Biotin Binding Capability: Engineering a Mobile Loop as an Exit Door for Biotin
A novel form of tetrameric streptavidin has been engineered to have reversible biotin binding capability. In wild-type streptavidin, loop3–4 functions as a lid for the entry and exit of biotin. When biotin is bound, interactions between biotin and key residues in loop3–4 keep this lid in the closed state. In the engineered mutein, a second biotin exit door is created by changing the amino acid sequence of loop7–8. This door is mobile even in the presence of the bound biotin and can facilitate the release of biotin from the mutein. Since loop7–8 is involved in subunit interactions, alteration of this loop in the engineered mutein results in an 11° rotation between the two dimers in reference to wild-type streptavidin. The tetrameric state of the engineered mutein is stabilized by a H127C mutation, which leads to the formation of inter-subunit disulfide bonds. The biotin binding kinetic parameters (koff of 4.28×10−4 s−1 and Kd of 1.9×10−8 M) make this engineered mutein a superb affinity agent for the purification of biotinylated biomolecules. Affinity matrices can be regenerated using gentle procedures, and regenerated matrices can be reused at least ten times without any observable reduction in binding capacity. With the combination of both the engineered mutein and wild-type streptavidin, biotinylated biomolecules can easily be affinity purified to high purity and immobilized to desirable platforms without any leakage concerns. Other potential biotechnological applications, such as development of an automated high-throughput protein purification system, are feasible
Comparative analyses of a small molecule/enzyme interaction by multiple users of Biacore technology
To gauge the experimental variability associated with Biacore analysis, 36 different investigators analyzed a small molecule/enzyme interaction under similar conditions. Acetazolamide (222 g/mol) binding to carbonic anhydrase II (CAII; 30,000 Da) was chosen as a model system. Both reagents were stable and their interaction posed a challenge to measure because of the low molecular weight of the analyte and the fast association rate constant. Each investigator created three different density surfaces of CAII and analyzed an identical dilution series of acetazolamide (ranging from 4.1 to 1000 nM). The greatest variability in the results was observed during the enzyme immobilization step since each investigator provided their own surface activating reagents. Variability in the quality of the acetazolamide binding responses was likely a product of how well the investigators' instruments had been maintained. To determine the reaction kinetics, the responses from the different density surfaces were fit globally to a 1:1 interaction model that included a term for mass transport. The averaged association and dissociation rate constants were 3.1 ± 1.6 × 106 M-1 s-1 and 6.7 ± 2.5 × 10-2 s-1, respectively, which corresponded to an average equilibrium dissociation constant (KD) of 2.6 ± 1.4 × 10-8 M. The results provide a benchmark of variability in interpreting binding constants from the biosensor and highlight keys areas that should be considered when analyzing small molecule interactions
Large-Eddy Simulation of Turbulent Organized Structures within and above Explicitly Resolved Cube Arrays
Large eddy simulation of high-Reynolds-number atmospheric boundary layer flow with improved near-wall correction
A global benchmark study using affinity-based biosensors
International audienceTo explore the variability in biosensor studies, 150 participants from 20 countries were given the same protein samples and asked to determine kinetic rate constants for the interaction. We chose a protein system that was amenable to analysis using different biosensor platforms as well as by users of different expertise levels. The two proteins (a 50-kDa Fab and a 60-kDa glutathione S-transferase [GST] antigen) form a relatively high-affinity complex, so participants needed to optimize several experimental parameters, including ligand immobilization and regeneration conditions as well as analyte concentrations and injection/dissociation times. Although most participants collected binding responses that could be fit to yield kinetic parameters, the quality of a few data sets could have been improved by optimizing the assay design. Once these outliers were removed, the average reported affinity across the remaining panel of participants was 620 pM with a standard deviation of 980 pM. These results demonstrate that when this biosensor assay was designed and executed appropriately, the reported rate constants were consistent, and independent of which protein was immobilized and which biosensor was used. (C) 2008 Elsevier Inc. All rights reserved