FoldX is an empirical force field that was developed for the rapid evaluation of the effect of mutations on the stability, folding and dynamics of proteins and nucleic acids. The core functionality of FoldX, namely the calculation of the free energy of a macromolecule based on its high-resolution 3D structure, is now publicly available through a web server at . The current release allows the calculation of the stability of a protein, calculation of the positions of the protons and the prediction of water bridges, prediction of metal binding sites and the analysis of the free energy of complex formation. Alanine scanning, the systematic truncation of side chains to alanine, is also included. In addition, some reporting functions have been added, and it is now possible to print both the atomic interaction networks that constitute the protein, print the structural and energetic details of the interactions per atom or per residue, as well as generate a general quality report of the pdb structure. This core functionality will be further extended as more FoldX applications are developed.

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We have developed a statistical mechanics algorithm, TANGO, to predict protein aggregation. TANGO is based on the physico-chemical principles of beta-sheet formation, extended by the assumption that the core regions of an aggregate are fully buried. Our algorithm accurately predicts the aggregation of a data set of 179 peptides compiled from the literature as well as of a new set of 71 peptides derived from human disease-related proteins, including prion protein, lysozyme and beta2-microglobulin. TANGO also correctly predicts pathogenic as well as protective mutations of the Alzheimer beta-peptide, human lysozyme and transthyretin, and discriminates between beta-sheet propensity and aggregation. Our results confirm the model of intermolecular beta-sheet formation as a widespread underlying mechanism of protein aggregation. Furthermore, the algorithm opens the door to a fully automated, sequence-based design strategy to improve the aggregation properties of proteins of scientific or industrial interest.

a b s t r a c tThe correlation between mRNA and protein abundances in the cell has been reported to be notoriously poor. Recent technological advances in the quantitative analysis of mRNA and protein species in complex samples allow the detailed analysis of this pathway at the center of biological systems. We give an overview of available methods for the identification and quantification of free and ribosome-bound mRNA, protein abundances and individual protein turnover rates. We review available literature on the correlation of mRNA and protein abundances and discuss biological and technical parameters influencing the correlation of these central biological molecules.

The genetic and biochemical networks which underlie such things as homeostasis in metabolism and the developmental programs of living cells, must withstand considerable variations and random perturbations of biochemical parameters. These occur as transient changes in, for example, transcription, translation, and RNA and protein degradation. The intensity and duration of these perturbations differ between cells in a population. The unique state of cells, and thus the diversity in a population, is owing to the different environmental stimuli the individual cells experience and the inherent stochastic nature of biochemical processes (for example, refs 5 and 6). It has been proposed, but not demonstrated, that autoregulatory, negative feedback loops in gene circuits provide stability, thereby limiting the range over which the concentrations of network components fluctuate. Here we have designed and constructed simple gene circuits consisting of a regulator and transcriptional repressor modules in Escherichia coli and we show the gain of stability produced by negative feedback.

In the transition state for unfolding of barnase, the hydrophobic core between the major alpha-helix and beta-sheet is somewhat weakened, the C terminus of the major helix is largely intact but its N terminus is exposed and a major loop has been invaded by solvent.

The conformational properties of a 16 residue peptide, corresponding to the second beta-hairpin of the B1 domain of protein G, have been studied by nuclear magnetic resonance spectroscopy (NMR). This fragment is monomeric under our experimental conditions and in pure water adopts a population containing up to 40% native-like beta-hairpin structure. The detection by NMR of a native-like beta-hairpin in aqueous solution, reported here for the first time, indicates that these structural elements may have an important role in the early steps of protein folding. It also provides a good model to study in detail the sequence determinants of beta-hairpin structure stability, as has been done with alpha-helices.

Protein aggregation results in beta-sheet-like assemblies that adopt either a variety of amorphous morphologies or ordered amyloid-like structures. These differences in structure also reflect biological differences; amyloid and amorphous beta-sheet aggregates have different chaperone affinities, accumulate in different cellular locations and are degraded by different mechanisms. Further, amyloid function depends entirely on a high intrinsic degree of order. Here we experimentally explored the sequence space of amyloid hexapeptides and used the derived data to build Waltz, a web-based tool that uses a position-specific scoring matrix to determine amyloid-forming sequences. Waltz allows users to identify and better distinguish between amyloid sequences and amorphous beta-sheet aggregates and allowed us to identify amyloid-forming regions in functional amyloids.