R K Do | PubMed Health

PubMed2000

Attenuation of apoptosis underlies B lymphocyte stimulator enhancement of humoral immune response.

B lymphocyte stimulator (BLyS) is a newly identified monocyte-specific TNF family cytokine. It has been implicated in the development of autoimmunity, and functions as a potent costimulator with antiimmunoglobulin M in B cell proliferation in vitro. Here we demonstrate that BLyS prominently enhances the humoral responses to both T cell-independent and T cell-dependent antigens, primarily by attenuation of apoptosis as evidenced by the prolonged survival of antigen-activated B cells in vivo and in vitro. BLyS acts on primary splenic B cells autonomously, and directly cooperates with CD40 ligand (CD40L) in B cell activation in vitro by protecting replicating B cells from apoptosis. Moreover, although BLyS alone cannot activate the cell cycle, it is sufficient to prolong the survival of naive resting B cells in vitro. Attenuation of apoptosis by BLyS correlates with changes in the ratios between Bcl-2 family proteins in favor of cell survival, predominantly by reducing the proapoptotic Bak and increasing its prosurvival partners, Bcl-2 and Bcl-xL. In either resting or CD40L-activated B cells, the NF-kappaB transcription factors RelB and p50 are specifically activated, suggesting that they may mediate BLyS signals for B cell survival. Together, these results provide direct evidence for BLyS enhancement of both T cell-independent and T cell-dependent humoral immune responses, and imply a role for BLyS in the conservation of the B cell repertoire. The ability of BLyS to increase B cell survival indiscriminately, at either a resting or activated state, and to cooperate with CD40L, further suggests that attenuation of apoptosis underlies BLyS enhancement of polyclonal autoimmunity as well as the physiologic humoral immune response.

2,4-Dinitrophenol↗

PubMed2000

Modeling of loops in protein structures.

Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4-, 8-, and 12-residue loop predictions, respectively, had <2 A RMSD error for the mainchain N, C(alpha), C, and O atoms; the average accuracies were 0.59 +/- 0.05, 1.16 +/- 0.10, and 2.61 +/- 0.16 A, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 A, the average loop prediction error increased by 180, 25, and 3% for 4-, 8-, and 12-residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling.

Models, Molecular↗