Selective protein immobilization onto gold nanoparticles deposited under vacuum on a protein-repellent self-assembled monolayer.

The immobilization of proteins on flat substrates plays an important role for a wide spectrum of applications in the fields of biology, medicine, and biochemistry, among others. An essential prerequisite for the use of proteins (e.g., in biosensors) is the conservation of their biological activity. Losses in activity upon protein immobilization can largely be attributed to a random attachment of the proteins to the surface. In this study, we present an approach for the immobilization of proteins onto a chemically heterogeneous surface, namely a surface consisting of protein-permissive and protein-repellent areas, which allows for significant reduction of random protein attachment. As protein-permissive, i.e., as protein-binding sites, ultra pure metallic nanoparticles are deposited under vacuum onto a protein-repellent PEG-silane polymer layer. Using complementary surface characterization techniques (atomic force microscopy, quartz crystal microbalance, and X-ray photoelectron spectroscopy) we demonstrate that the Au nanoparticles remain accessible for protein attachment without compromising the protein-repellency of the PEG-silane background. Moreover, we show that the amount of immobilized protein can be controlled by tuning the Au nanoparticle coverage. This method shows potential for applications requiring the control of protein immobilization down to the single molecule level.

Docking unbound proteins with MIAX: a novel algorithm for protein-protein soft docking.

We propose a new methodology for "soft'' docking unbound protein molecules (reported at the isolated state). The methodology is characterized by its simplicity and easiness of embedment in any rigid body docking process based on point complementarity. It is oriented to allow limited free but not unrealistic interpenetration of the side chains of protein surface amino acid residues. The central step to the technique is a filtering process similar to those in image processing. The methodology assists in deletion of atomic-scale details on the surface of the interacting monomers, leading to the extraction of the most characteristic flattened shape for the molecule as well as the definition of a soft layer of atoms to allow smooth interpenetration of the interacting molecules during the docking process. Although the methodology does not perform structural or conformational rearrangements in the interacting monomers, results output by the algorithm are in fair agreement with the relative position of the monomer in experimentally reported complexes. The algorithm performs especially well in cases where the complexity of the protein surfaces is high, that is in hetero dimmer complex prediction. The algorithm is oriented to play the role of a fast screening engine for proteins known to interact but for which no information other than that of the structures at the isolated state is available. Consequently the importance of the methodology will increase in structural-function studies of thousand of proteins derived from large scale genome sequencing projects being executed all around the globe.