Meta-structure correlation in protein space unveils different selection rules for folded and intrinsically disordered proteins

The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDP) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation map to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and responds differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function - enabling information is encoded in IDPs.

On the origin of the selectivity of plasmidic H-NS towards horizontally acquired DNA: Linking H-NS oligomerization and cooperative DNA binding

The nucleoid-associated protein H-NS is a global modulator of the expression of genes associated with adaptation to environmental changes. A variant of H-NS expressed in the R27 plasmid was previously shown to selectively modulate the expression of horizontally acquired genes, with minimal effects on core genes that are repressed by the chromosomal form of H-NS. Both H-NS proteins are formed by an oligomerization domain and a DNA-binding domain, which are connected by a linker that is highly flexible in the absence of DNA. We studied DNA binding by means of oligomer-forming chimeric proteins in which domains of the chromosomal and plasmidic variants are exchanged, as well as in monomeric truncated forms containing the DNA-binding domain and variable portions of the linker. Point mutations in the linker were also examined in full-length and truncated H-NS constructs. These experiments show that the linker region contributes to DNA binding affinity and that it is a main component of the distinct DNA binding properties of chromosomal and plasmidic H-NS. We propose that interactions between the linker and DNA limit the flexibility of the connection between H- NS oligomerization and DNA binding and provide an allosteric indirect readout mechanism to detect long- range distortions of DNA, thus enabling discrimination between core and horizontally acquired DNA.

Protein loop compaction and the origin of the effect of arginine and glutamic acid mixtures on solubility, stability and transient oligomerization of proteins

Addition of a 50 mM mixture of l-arginine and l-glutamic acid (RE) is extensively used to improve protein solubility and stability, although the origin of the effect is not well understood. We present Small Angle X-ray Scattering (SAXS) and Nuclear Magnetic Resonance (NMR) results showing that RE induces protein compaction by collapsing flexible loops on the protein core. This is suggested to be a general mechanism preventing aggregation and improving resistance to proteases and to originate from the polyelectrolyte nature of RE. Molecular polyelectrolyte mixtures are expected to display long range correlation effects according to dressed interaction site theory. We hypothesize that perturbation of the RE solution by dissolved proteins is proportional to the volume occupied by the protein. As a consequence, loop collapse, minimizing the effective protein volume, is favored in the presence of RE.

Classifier combination for in vivo magnetic resonance spectra of brain tumours

In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.

Synthesis and antitumor activity of mechercharmycin A analogues

Several analogs of the cytotoxic thiopeptide IB-01211 or Mechercharmycin A (1) have been synthetized. The cytotoxicity of 1 and the synthetized analogs was evaluated against a panel of three human tumor cell lines. Thiopeptide 1 and the most active derivatives, 2 and 3c, were chosen for further studies like effects on cell cycle progression and induction of apoptosis. Interestingly, the inhibition of cell division and activation of a programmed cell death by apoptosis was detected.