Protease footprinting reveals a surface on transcription factor TFIIB that serves as an interface for activators and coactivators.

Transcriptional stimulation by the model activator GAL4-VP16 (a chimeric protein consisting of the DNA-binding domain of the yeast activator GAL4 and the acidic activation domain of the herpes simplex virus protein VP16) involves a series of poorly understood protein-protein interactions between the VP16 activation domain and components of the RNA polymerase II general transcription machinery. One of these interactions is the VP16-mediated binding and recruitment of transcription factor TFIIB. However, TATA box-binding protein (TBP)-associated factors (TAFs), or coactivators, are required for this interaction to culminate in productive transcription complex assembly, and one such TAF, Drosophila TAF40, reportedly forms a ternary complex with VP16 and TFIIB. Due to TFIIB's central role in gene activation, we sought to directly visualize the surfaces of this protein that mediate formation of the ternary complex. We developed an approach called protease footprinting in which the broad-specificity proteases chymotrypsin and alkaline protease were used to probe binding of 32P-end-labeled TFIIB to GAL4-VP16 or TAF40. Analysis of the cleavage products revealed two regions of TFIIB protected by VP16 from protease attack, one of which overlapped with a region protected by TAF40. The close proximity of the VP16 and TAF40 binding sites on the surface of TFIIB suggests that this region could act as a regulatory interface mediating the effects of activators and coactivators on transcription complex assembly.

A sampling problem in molecular dynamics simulations of macromolecules.

Correlations in low-frequency atomic displacements predicted by molecular dynamics simulations on the order of 1 ns are undersampled for the time scales currently accessible by the technique. This is shown with three different representations of the fluctuations in a macromolecule: the reciprocal space of crystallography using diffuse x-ray scattering data, real three-dimensional Cartesian space using covariance matrices of the atomic displacements, and the 3N-dimensional configuration space of the protein using dimensionally reduced projections to visualize the extent to which phase space is sampled.