Kinetic proofreading models for cell signaling predict ways to escape kinetic proofreading

In the context of cell signaling, kinetic proofreading was introduced to explain how cells can discriminate among ligands based on a kinetic parameter, the ligand-receptor dissociation rate constant. In the kinetic proofreading model of cell signaling, responses occur only when a bound receptor undergoes a complete series of modifications. If the ligand dissociates prematurely, the receptor returns to its basal state and signaling is frustrated. We extend the model to deal with systems where aggregation of receptors is essential to signal transduction, and present a version of the model for systems where signaling depends on an extrinsic kinase. We also investigate the kinetics of signaling molecules, “messengers,” that are generated by aggregated receptors but do not remain associated with the receptor complex. We show that the extended model predicts modes of signaling that exhibit kinetic discrimination for some range of parameters but for other parameter values show little or no discrimination and thus escape kinetic proofreading. We compare model predictions with experimental data.

The effects of sequence context on DNA curvature.

Recent experiments have exposed significant discrepancies between experimental data and predictive models for DNA structure. These results strongly suggest that DNA structural parameters incorporated in the models are not always sufficient to account for the influence of sequence context and of specific ion effects. In an attempt to evaluate these two effects, we have investigated repetitive DNA sequences with the sequence motif GAGAG.CTCTC located in different helical phasing arrangements with respect to poly(A) tracts and GGGCCC.GGGCCC sequence motifs. Methods used are ligase-mediated cyclization and gel mobility experiments along with DNase I cutting and chemical probe studies. The results provide new evidence for curvature in poly(A) tracts. They also show that the sequence context in which bending and flexible sequence elements are found is an important aspect of sequence-dependent DNA conformation. Although dinucleotide models generally have good predictive power, this work demonstrates that in some instances sequence elements larger than the dinucleotide must be taken into account, and hence it provides a starting point for the appropriate modification and refinement of existing structural models for DNA.