High-sequence diversity and structural conservation in the human T-cell receptor ß junctional region during thymic development.

The T-cell repertoire depends on intrathymic genetic rearrangement events in the T-cell receptor (TCR) locus, followed by positive and negative selection. The repertoire thus generated is highly diverse, but recent data indicate that the recombination of gene segments is less stochastic than previously suggested. Very little is known of the junctional complementarity determining region 3 (CDR3), which is to a large degree not germline encoded. We have analyzed the development of the human TCR ß CDR3 repertoire, from the nonselected CD4(+) CD8(+) CD3(-) cells up to the fully selected CD4(+) CD8(-) thymocytes. In addition to spectratyping, a fraction of the CDR3 repertoire was sequenced and a structural in silico analysis of the CDR3 loop characteristics performed. Our data show that the thymic TCR repertoire is extremely diverse, and the effect of the selection events can be detected as a measurable loss of polyclonality in the CDR3 loop. However, the main physicochemical features of the CDR3 loop were found already at the nonselected repertoire and showed no progressive changes during the selection. Thus, the main structural characteristics of the CDR3 loop were already determined by the recombination process and not significantly affected by the extensive thymocyte death associated with selection in the thymus.

Specific Conformational States of Ras GTPase upon Effector Binding.

To uncover the structural and dynamical determinants involved in the highly specific binding of Ras GTPase to its effectors, the conformational states of Ras in uncomplexed form and complexed to the downstream effectors Byr2, PI3Kγ, PLCε, and RalGDS were investigated using molecular dynamics and cross-comparison of the trajectories. The subtle changes in the dynamics and conformations of Ras upon effector binding require an analysis that targets local changes independent of global motions. Using a structural alphabet, a computational procedure is proposed to quantify local conformational changes. Positions detected by this approach were characterized as either specific for a particular effector, specific for an effector domain type, or as effector unspecific. A set of nine structurally connected residues (Ras residues 5-8, 32-35, 39-42, 55-59, 73-78, and 161-165), which link the effector binding site to the distant C-terminus, changed dynamics upon effector binding, indicating a potential effector-unspecific signaling route within the Ras structure. Additional conformational changes were detected along the N-terminus of the central ß-sheet. Besides the Ras residues at the effector interface (e.g., D33, E37, D38, and Y40), which adopt effector-specific local conformations, the binding signal propagates from the interface to distant hot-spot residues, in particular to Y5 and D57. The results of this study reveal possible conformational mechanisms for the stabilization of the active state of Ras upon downstream effector binding and for the structural determinants responsible for effector specificity.

Deciphering the shape and deformation of secondary structures through local conformation analysis.

BACKGROUND: Protein deformation has been extensively analysed through global methods based on RMSD, torsion angles and Principal Components Analysis calculations. Here we use a local approach, able to distinguish among the different backbone conformations within loops, α-helices and ß-strands, to address the question of secondary structures' shape variation within proteins and deformation at interface upon complexation. RESULTS: Using a structural alphabet, we translated the 3 D structures of large sets of protein-protein complexes into sequences of structural letters. The shape of the secondary structures can be assessed by the structural letters that modeled them in the structural sequences. The distribution analysis of the structural letters in the three protein compartments (surface, core and interface) reveals that secondary structures tend to adopt preferential conformations that differ among the compartments. The local description of secondary structures highlights that curved conformations are preferred on the surface while straight ones are preferred in the core. Interfaces display a mixture of local conformations either preferred in core or surface. The analysis of the structural letters transition occurring between protein-bound and unbound conformations shows that the deformation of secondary structure is tightly linked to the compartment preference of the local conformations. CONCLUSION: The conformation of secondary structures can be further analysed and detailed thanks to a structural alphabet which allows a better description of protein surface, core and interface in terms of secondary structures' shape and deformation. Induced-fit modification tendencies described here should be valuable information to identify and characterize regions under strong structural constraints for functional reasons.

A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.