L'économiseur d'écran montre le progrès de chaque trajectoire en temps réel:" "
Il y a 4 cases montrant la forme de la chaîne protéique." msgid "RAH_VIZ_SEARCH" msgstr "\"Searching...\" montre les mouvements que Rosetta essaye d'appliquer à la chaîne. Vous pouvez voir la forme de la chaîne " "en suivant les couleurs de l'arc-en-ciel allant du bleu au rouge." msgid "RAH_VIZ_ACCEPTED" msgstr "\"Accepted\" montre le mouvement accepté le plus récemment." msgid "RAH_VIZ_LOW" msgstr "\"Low Energy\" montre forme d'énergie la plus basse obtenue dans la trajectoire en cours." msgid "RAH_VIZ_NATIVE" msgstr "\"Native\" montre la vraie forme de la protéine obtenue expérimentalement, si celle-ci est connue." msgid "RAH_VIZ_G" msgstr "Il y a également deux graphes et un tracé qui montrent l'énergie et le rmsd de chaque mouvement admis." msgid "RAH_VIZ_ACCEPTED_E" msgstr "\"Accepted Energy\" est le graphe montrant l'énergie de chaque mouvement admis dans cette trajectoire. (l'axe des x représente l'avancement du travail dans la trajectoire, l'axe des y montre l'énergie obtenue pour chaque forme.)" msgid "RAH_VIZ_RMSD" msgstr "\"RMSD\" montre à quel point la structure acceptée en cours est proche de la bonne réponse. (l'axe des x représente le RMSD, l'axe des y représente l'avancement du travail.)" msgid "RAH_VIZ_RMSD_E" msgstr "La dernière case dans le coin inférieur droit, montre l'énergie et le RMSD de chaque mouvement admis. C'est le même genre de " "graphe que ceux de la page des %sMeilleures prédictions%s. Sauf que maintenant, vous les voyez pour chaque mouvement *accepté* dans cette trajectoire. " "Les graphes de la page des meilleures prédictions se composent uniquement des repliements de faible énergie de chaque trajectoire." ######################################### # rah_research.php ######################################## msgid "RAH_RESEARCH_TITLE_A" msgstr "Prediction and Design of Macromolecular Structures and Interactions" msgid "RAH_RESEARCH_INFO" msgstr "For information about $PROJECT, %sclick here%s" msgid "RAH_RESEARCH_INTRO_A" msgstr "The goal of our current research is to develop an improved model of intra- and intermolecular interactions and to use this model to predict and design macromolecular " "structures and interactions. Prediction and design applications, which can be of great biological interest in their own right, also provide stringent and objective tests that " "improve the model and increase fundamental understanding." msgid "RAH_RESEARCH_INTRO_B" msgstr "We use a computer program called Rosetta to carry out protein and design calculations. At the core of Rosetta are potential functions for computing the energies of " "interactions within and between macromolecules, and methods for finding the lowest energy structure for an amino acid sequence (protein-structure prediction) or a " "protein-protein complex and for finding the lowest energy amino acid sequence for a protein or protein-protein complex (protein design). Feedback from the prediction and " "design tests is used continually to improve the potential functions and the search algorithms. Development of one computer program to treat these diverse problems has " "considerable advantages: first, the different applications provide complementary tests of the underlying physical model (the fundamental physics/physical chemistry is, of " "course, the same in all cases); second, many problems of current interest, such as flexible backbone protein design and protein-protein docking with backbone flexibility, " "involve a combination of the different optimization methods." msgid "RAH_RESEARCH_DESIGN_TITLE" msgstr "Design of Protein Structure" msgid "RAH_RESEARCH_DESIGN_A" msgstr "Over the past several years, we have used our computational protein design method to stabilize dramatically several small proteins by redesigning every residue of their " "sequences, to redesign protein backbone conformation, to convert a monomeric protein to a strand-swapped dimer, and to thermostabilize an enzyme. A highlight was the " "redesign of the folding pathway of protein G, a small protein containing two beta-hairpins separated by an alpha-helix. In the naturally occurring protein, the first hairpin is " "disrupted and the second hairpin is formed at the rate limiting step in folding. In a redesigned variant in which the first hairpin is significantly stabilized and the second hairpin " "destabilized, the order of events is reversed: the first hairpin is formed and the second hairpin disrupted in the folding transition state. The ability to redesign protein-folding " "pathways rationally shows that our understanding of the determinants of protein folding has advanced considerably." msgid "RAH_RESEARCH_DESIGN_B" msgstr "Particularly exciting recently is the creation of novel proteins with arbitrarily chosen three-dimensional structures. We developed a general computational strategy for creating " "these protein structures that incorporates full backbone flexibility into rotamer-based sequence optimization. This was accomplished by integrating ab initio protein structure " "prediction, atomic-level energy refinement, and sequence design in Rosetta. The procedure was used to design a 93-residue protein called TOP7 with a novel sequence and " "topology. TOP7 was found to be monomeric and folded, and the x-ray crystal structure of TOP7 is strikingly similar (RMSD = 1.2 Å; see right panel of Figure 1) to the design " "model. The design of a new globular protein fold and the close correspondence of the crystal structure to the design model have broad implications for protein design and " "protein-structure prediction and open the door to the exploration of the large regions of the protein universe not yet observed in nature." msgid "RAH_RESEARCH_DESIGN_PPI_TITLE" msgstr "Design of Protein-Protein Interactions" msgid "RAH_RESEARCH_DESIGN_PPI_A" msgstr "To extend these methods to protein-protein interactions and particularly to the redesign of interaction specificity, we chose the high-affinity complex between colicin E7 DNase " "and its cognate inhibitory immunity protein as a model system. We used the physical model described above and a modification of our rotamer search-based computational " "design strategy to generate novel DNase-inhibitor protein pairs predicted to interact tightly with one another but not with the wild-type proteins. The designed protein " "complexes have subnanomolar affinities, are functional and specific in vivo, and have more than an order of magnitude affinity difference between cognate and noncognate " "pairs in vitro. This approach should be applicable to the design of interacting " "protein pairs with novel specificities for delineating and reengineering protein interaction networks in living cells." msgid "RAH_RESEARCH_DESIGN_PPI_B" msgstr "In collaboration with the research groups of Barry Stoddard and Ray Monnat (%sFred Hutchinson Cancer Research Center%s), we generated an artificial, highly specific " "endonuclease by fusing domains of homing endonucleases I-DmoI and I-CreI through computational optimization of a new domain-domain interface between these normally " "noninteracting proteins. The resulting enzyme, E-DreI (Engineered I-DmoI/I-CreI), binds a long chimeric DNA target site with nanomolar affinity, cleaving it precisely at a rate " "equivalent to its natural parents. We are currently trying to generate new endonucleases by extending our design methodology to protein--nucleic acid interfaces to redesign " "the protein-DNA interface." msgid "RAH_RESEARCH_DESIGN_PPI_C" msgstr "In both of these systems it has been possible to determine x-ray crystal structures of the designed complexes. As in the TOP7 case, the actual structures are very close to the " "design models (Figure 1, left panel), which validates the accuracy of our approach to high-resolution modeling." msgid "RAH_RESEARCH_PRED_PS_TITLE" msgstr "Prediction of Protein Structure" msgid "RAH_RESEARCH_PRED_PS_A" msgstr "The picture of protein folding that motivates our approach to ab initio protein tertiary structure prediction is that sequence-dependent local interactions bias segments of the " "chain to sample distinct sets of local structures, and that nonlocal interactions select the lowest free-energy tertiary structures from the many conformations compatible with " "these local biases. In implementing the strategy suggested by this picture, we use different models to treat the local and nonlocal interactions. Rather than attempting a " "physical model for local sequence-structure relationships, we turn to the protein database and take the distribution of local structures adopted by short sequence segments " "(fewer than 10 residues in length) in known three-dimensional structures as an approximation to the distribution of structures sampled by isolated peptides with the " "corresponding sequences." msgid "RAH_RESEARCH_PRED_PS_B" msgstr "The primary nonlocal interactions considered are hydrophobic burial, electrostatics, main-chain hydrogen bonding, and excluded volume. Structures that are simultaneously " "consistent with both the local sequence structure biases and the nonlocal interactions are generated by using simulated annealing to minimize the nonlocal interaction energy " "in the space defined by the local structure distributions." msgid "RAH_RESEARCH_PRED_PS_C" msgstr "Rosetta has been tested in the biannual %sCASP%s (critical assessment of structure prediction) experiments in which predictors are challenged to make blind predictions of the " "structures adopted by protein sequences whose structures have been determined but not yet published. Since CASP3 in 1998, Rosetta has consistently been the top " "performing method for ab initio prediction, as reported by independent assessors. In the CASP4 experiment, for example, Rosetta was tested on 21 proteins. The predictions " "for these proteins, which lack detectable sequence similarity to any protein with a previously determined structure, were of unprecedented accuracy and consistency. (Some " "examples are shown in Figure 2.) Excellent predictions were also made in the CASP5 and CASP6 experiments. Encouraged by these promising results, we generated " "models for all large protein families fewer than 150 amino acids in length." msgid "RAH_RESEARCH_PRED_PS_D" msgstr "A highlight of CASP6 was the first de novo blind prediction that used our high-resolution refinement methodology to achieve close to high-resolution accuracy. The relatively " "short sequence (76 residues) allowed us to apply our all-atom refinement methodology not only to the native sequence but also to the sequence of many homologs. The " "center of the lowest energy cluster of structures turned out to be remarkably close to the native structure (1.5 Å; Figure 3). The-high resolution refinement protocol decreased " "the RMSD from 2.2 Å to 1.5 Å, and the side chains pack in a somewhat native-like manner in the protein core (Figure 3, right panel)." msgid "RAH_RESEARCH_PRED_PS_E" msgstr "We have extended the Rosetta ab initio structure prediction strategy to the problem of using limited experimental data to generate models of proteins. By incorporating " "chemical shift and NOE information and more recently dipolar coupling information into the Rosetta structure generation procedure, we have been able to generate much " "more accurate models than with ab initio structure prediction alone or when using the same limited data sets with conventional nuclear magnetic resonance (NMR) structure " "generation methodology. An exciting recent development is that the Rosetta procedure can also take advantage of unassigned NMR data and hence circumvent the difficult " "and tedious step of assigning NMR spectra." msgid "RAH_RESEARCH_PRED_PS_F" msgstr "The Rosetta ab initio structure prediction method, the Rosetta-based NMR structure determination method, and a new method for comparative modeling that uses the Rosetta " "de novo approach to model the parts of a structure (primarily long loops) that cannot be modeled accurately based on a homologous structure template have all been " "implemented in a public server called %sRobetta%s. This server, which has a constant backlog of users worldwide, was one of the best all-around fully automated structure " "prediction servers in the CASP5 and CASP6 tests." msgid "RAH_RESEARCH_PRED_PPI_TITLE" msgstr "Prediction of Protein-Protein Interactions" msgid "RAH_RESEARCH_PRED_PPI_A" msgstr "For a number of years we have worked on protein structure refinement, a challenging problem because of the large number of degrees of freedom. We became interested in " "protein-protein docking because, with the approximation that the two partners do not undergo significant conformational changes during docking, the space to be " "searched -the six rigid-body degrees of freedom in addition to the side-chain degrees of freedom- is much smaller. While important in its own right, this problem is a good stepping " "stone to the harder structure refinement problem." msgid "RAH_RESEARCH_PRED_PPI_B" msgstr "We developed a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. This method employs a low-resolution, " "rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations with the Monte Carlo minimization procedure " "and physical model used in our high-resolution structure prediction work. The simultaneous optimization of side-chain and rigid-body degrees of freedom contrasts with most " "other current approaches, which model protein-protein docking as a rigid-body shape-matching problem, with the side chains kept fixed. We have recently improved the " "method (RosettaDock) by developing an algorithm that allows efficient sampling of off-rotamer side-chain conformations during docking." msgid "RAH_RESEARCH_PRED_PPI_C" msgstr "The power of RosettaDock was highlighted in the recent blind %sCAPRI%s protein-protein docking challenge that was held in December 2004. In CAPRI, predictors are given the " "structures of two proteins known to form a complex, and challenged to predict the structure of the complex. RosettaDock predictions for targets without significant backbone " "conformational changes were striking, as shown in Figure 4. Not only were the rigid-body orientations of the two partners predicted nearly perfectly but also almost all the " "interface side chains were modeled very accurately. These correct models clearly stood out as lower in energy than all other models we generated, which suggests the " "potential function is reasonably accurate." msgid "RAH_RESEARCH_PRED_PPI_D" msgstr "These promising results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated " "components, and more generally suggest that high-resolution modeling of structures and interactions is within reach. A clear goal for our monomeric structure prediction work " "is to approach the level of accuracy of these models." msgid "RAH_RESEARCH_IMPROV_TITLE" msgstr "Improvement of Physical Model" msgid "RAH_RESEARCH_IMPROV" msgstr "Our current approach to improving energy functions involves a combination of quantum chemistry calculations on simple model compounds, traditional molecular mechanics " "approaches, and protein structural analysis. We have used such an approach to develop an improved hydrogen-bonding potential. A particularly notable result is that the " "orientation dependence of the hydrogen bond in quantum chemistry calculations on formamide dimers is remarkably similar to that seen in side-chain--side-chain hydrogen " "bonds in protein structures but different from that in current molecular mechanics force fields, which neglect the covalent character of the hydrogen bond. Feedback from the " "prediction and design calculations has provided continual impetus and guidance for improving the energy function; for example, inadequacies in our treatment of " "protein-protein interactions have led to the recent development of a rotamer-based model for water-mediated hydrogen bonds." msgid "RAH_RESEARCH_FUTURE_TITLE" msgstr "Plans for the Future" msgid "RAH_RESEARCH_FUTURE_A" msgstr "Our prediction and design methods have now reached the point where they can be applied to important biological problems. Particularly encouraging after years of work on " "high-resolution modeling are the close to atomic resolution predictions of the structures of complexes in CAPRI (Figure 4), the 1.5-Å de novo prediction in CASP6 (Figure 3), " "and the close agreement of the TOP7 (Figure 1, right) and protein-protein interface design models (Figure 1, left) with the x-ray crystal structures. These results suggest that " "high-resolution modeling is starting to work." msgid "RAH_RESEARCH_FUTURE_B" msgstr "In the next several years, we aim to improve and extend our methods. We are particularly focused on improving the accuracy of high-resolution structure prediction (which will " "be required if the models are to be generally useful). To accomplish this, we will work to improve the underlying physical model and the sampling methodology. We are also " "developing improved methods to predict and redesign protein-DNA interaction specificity, and extending our protein design methodology to the design of enzymes that " "catalyze chemical reactions not catalyzed by naturally occurring proteins." msgid "RAH_RESEARCH_END" msgstr "Please visit our web site at %s for additional information including a list of our research publications." msgid "RAH_RESEARCH_FIG_A" msgstr "Figure 1: Design of proteins and protein-protein interactions with high-resolution accuracy. Comparison of design " "model and crystal structure of (left) interface of novel designed endonuclease with new DNA cleavage specificity, " "and (right) the de novo designed protein TOP7.
Left panel, Tanja Kortemme. Right panel, Gautam Dantas." msgid "RAH_RESEARCH_FIG_B" msgstr "Figure 2: Blind protein structure predictions from CASP3 and CASP4." "
A: Left, crystal structure of the MarA transcription factor bound to DNA; right, our best submitted model in CASP3." "Despite many incorrect details, the overall fold is predicted with sufficient accuracy to allow insights into the mode of " "DNA binding.
" "B: Left, the crystal structure of bacteriocin AS-48; middle, our best submitted model in CASP4; right, a structurally " "and functionally related protein (NK-lysin) identified using this model in a structure-based search of the Protein Data " "Bank (PDB). The structural and functional similarity is not recognizable using sequence comparison methods (the identity between the two sequences is only 5 percent).
" "C: Left, crystal structure of the second domain of MutS; middle, our best submitted model for this domain in CASP4; " "right, a structurally related protein (RuvC) with a related function recognized using the model in a structure-based " "search of the PDB. The similarity was not recognized using sequence comparison or fold recognition methods.
" "Image: Rich Bonneau" msgid "RAH_RESEARCH_FIG_C" msgstr "Figure 3: The first close to atomic-level resolution, blind ab initio structure prediction-CASP6 T281. The " "high-resolution refinement methodology described in the text produced a model 1.5-Å RMSD from the crystal " "structure (left panel), with aspects of the native side-chain packing (right panel). " "
Image: Phil Bradley" msgid "RAH_RESEARCH_FIG_D" msgstr "Figure 4: CAPRI (critical assessment of predicted interactions) protein-protein docking results. Superposition of " "predicted (blue) and x-ray (red and orange) protein complex structures. Green, a side chain whose conformation " "was correctly predicted to change upon complex formation. Upper panel, whole complex. Lower panel, details of the " "interface. In addition to the rigid-body orientation, the conformations of most of the side chains are predicted " "correctly.
Image: Ora Furman" #EOF