From Isotropic to Anisotropic Side Chain Representations: Comparison of Three Models for Residue Contact Estimation

The criterion to determine residue contact is a fundamental problem in deriving knowledge-based mean-force potential energy calculations for protein structures. A frequently used criterion is to require the side chain center-to-center distance or the -to- atom distance to be within a pre-determined cutoff distance. However, the spatially anisotropic nature of the side chain determines that it is challenging to identify the contact pairs. This study compares three side chain contact models: the Atom Distance criteria (ADC) model, the Isotropic Sphere Side chain (ISS) model and the Anisotropic Ellipsoid Side chain (AES) model using 424 high resolution protein structures in the Protein Data Bank. The results indicate that the ADC model is the most accurate and ISS is the worst. The AES model eliminates about 95% of the incorrectly counted contact-pairs in the ISS model. Algorithm analysis shows that AES model is the most computational intensive while ADC model has moderate computational cost. We derived a dataset of the mis-estimated contact pairs by AES model. The most misjudged pairs are Arg-Glu, Arg-Asp and Arg-Tyr. Such a dataset can be useful for developing the improved AES model by incorporating the pair-specific information for the cutoff distance

Synergism between particle-based multiplexing and microfluidics technologies may bring diagnostics closer to the patient

In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick high-throughput assays. On the one hand, recent progress in microfluidics technologies is expected to strongly support the development of miniaturized analytical devices, which will speed up (bio)analytical assays. On the other hand, a higher throughput can be obtained by the simultaneous screening of one sample for multiple targets (multiplexing) by means of encoded particle-based assays. Multiplexing at the macro level is now common in research labs and is expected to become part of clinical diagnostics. This review aims to debate on the “added value” we can expect from (bio)analysis with particles in microfluidic devices. Technologies to (a) decode, (b) analyze, and (c) manipulate the particles are described. Special emphasis is placed on the challenges of integrating currently existing detection platforms for encoded microparticles into microdevices and on promising microtechnologies that could be used to down-scale the detection units in order to obtain compact miniaturized particle-based multiplexing platforms

Quantification of Airborne Fossil and Biomass Carbonylic Carbon by Combined Radiocarbon Analysis and LC-MS.

Abstract not availableJRC.(EI)-Environment Institut

Platform technologies for molecular diagnostics near the patient's bedside

It is believed Lab-on-Chip systems will become a mainstream technology within the next centuries. Especially because of new findings in molecular medicine and global trends such as the changing global population in third world countries and an ageing population in industrial countries, the need for fast and reliable diagnostics is rising tremendously. Hence, diagnostics have to become more frequently and more easily available. In this regard, technologies have to be found that enable the cost-effective production and hence an affordable price. In a joint-project between seven Fraunhofer institutes a Lab-on-Chip system was developed which consists of a credit-card-sized cartridge and a base station. The cartridges contain besides the reagents necessary for a specific assay also functionalities such as pumping or heating enabling a self-contained system without any fluidic interfaces, which tend to be error-prone. Because of the modularity of the system it is possible to integrate an optical sensor as well an electrochemical sensor into the cartridge. Hence, the system can be customized to serve the needs of the particular assays. This chapter will describe the system including generic design rules for such Lab-on-Chip systems, the development of these rules into a modular Lab-on-Chip system, the integration of biomedical assays, and the production possibility of this system