Defining an Essence of Structure Determining Residue Contacts in Proteins

The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this “structural essence” has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts—such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed “cone-peeling” that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 Å Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This “structural essence” opens new avenues in the fields of structure prediction, empirical potentials and docking

Directing the evolution of Rubisco and Rubisco activase: first impressions of a new tool for photosynthesis research

During the last decade the practice of laboratory-directed protein evolution has become firmly established as a versatile tool in biochemical research by enabling molecular evolution toward desirable phenotypes or detection of novel structure–function interactions. Applications of this technique in the field of photosynthesis research are still in their infancy, but recently first steps have been reported in the directed evolution of the CO2-fixing enzyme Rubisco and its helper protein Rubisco activase. Here we summarize directed protein evolution strategies and review the progressive advances that have been made to develop and apply suitable selection systems for screening mutant forms of these enzymes that improve the fitness of the host organism. The goal of increasing photosynthetic efficiency of plants by improving the kinetics of Rubisco has been a long-term goal scoring modest successes. We discuss how directed evolution methodologies may one day be able to circumvent the problems encountered during this venture

A new family of giardial cysteine-rich non-VSP protein genes and a novel cyst protein

© 2006 Davids et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The definitive version was published in PLoS ONE 1 (2006): e44, doi:10.1371/journal.pone.0000044.Since the Giardia lamblia cyst wall is necessary for survival in the environment and host infection, we tested the hypothesis that it contains proteins other than the three known cyst wall proteins. Serial analysis of gene expression during growth and encystation revealed a gene, “HCNCp” (High Cysteine Non-variant Cyst protein), that was upregulated late in encystation, and that resembled the classic Giardia variable surface proteins (VSPs) that cover the trophozoite plasmalemma. HCNCp is 13.9% cysteine, with many “CxxC” tetrapeptide motifs and a transmembrane sequence near the C-terminus. However, HCNCp has multiple “CxC” motifs rarely found in VSPs, and does not localize to the trophozoite plasmalemma. Moreover, the HCNCp C-terminus differed from the canonical VSP signature. Full-length epitope-tagged HCNCp expressed under its own promoter was upregulated during encystation with highest expression in cysts, including 42 and 21 kDa C-terminal fragments. Tagged HCNCp targeted to the nuclear envelope in trophozoites, and co-localized with cyst proteins to encystation-specific secretory vesicles during encystation. HCNCp defined a novel trafficking pathway as it localized to the wall and body of cysts, while the cyst proteins were exclusively in the wall. Unlike VSPs, HCNCp is expressed in at least five giardial strains and four WB subclones expressing different VSPs. Bioinformatics identified 60 additional large high cysteine membrane proteins (HCMp) containing ≥20 CxxC/CxC's lacking the VSP-specific C-terminal CRGKA. HCMp were absent or rare in other model or parasite genomes, except for Tetrahymena thermophila with 30. MEME analysis classified the 61 gHCMp genes into nine groups with similar internal motifs. Our data suggest that HCNCp is a novel invariant cyst protein belonging to a new HCMp family that is abundant in the Giardia genome. HCNCp and the other HCMp provide a rich source for developing parasite-specific diagnostic reagents, vaccine candidates, and subjects for further research into Giardia biology