Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Functionalised amyloid fibrils for roles in cell adhesion

We describe experiments designed to explore the possibility of using amyloid fibrils as new nanoscale biomaterials for promoting and exploiting cell adhesion, migration and differentiation in vitro. We created peptides that add the biological cell adhesion sequence (RGD) or a control sequence (RAD) to the C-terminus of an 11-residue peptide corresponding to residues 105-115 of the amyloidogenic protein transthyretin. These peptides readily self-assemble in aqueous solution to form amyloid fibrils, and X-ray fibre diffraction shows that they possess the same strand and sheet spacing in the characteristic cross-beta structure as do fibrils formed by the parent peptide. We report that the fibrils containing the RGD sequence are bioactive and that these fibrils interact specifically with cells via the RGD group displayed on the fibril surface. As the design of such functionalized fibrils can be systematically altered, these findings suggest that it will be possible to generate nanomaterials based on amyloid fibrils that are tailored to promote interactions with a wide variety of cell types. (c) 2007 Elsevier Ltd. All rights reserved.