Modeling promoter search by E. coli RNA polymerase: One-dimensional diffusion in a sequence-dependent energy landscape

Abstract

We present a biophysical model of promoter search by Escherichia coli RNA polymerase. We use an unconventional weight matrix derived from promoter strength data to extract the energy landscape common to a large set of known promoters. This exhibits a continuous strengthening of the binding energy when approaching the transcription start site from either side. During promoter search, the RNA polymerase slides along the DNA double helix (one-dimensional diffusion) after randomly binding to it. We discuss the possibility that the sliding has a sequence-dependent component, which implies that the energy landscape influences the movement with respect to speed, direction and efficiency. Based on this assumption, we relate the obtained energy landscape around the promoters to the one-dimensional diffusion of the RNA polymerase. Our analytical results suggest that the sequence-dependent random walk slows down and gets directed upon entering a region of 500 bp around the transcription start site, which significantly increases the efficiency of promoter search. These results may explain how the RNA polymerase is able to find the promoter in biologically relevant times out of a vast excess of non-target sites. Moreover, they provide evidence for a sequence-dependent component of one-dimensional diffusion.

Homotypic clusters of transcription factor binding sites: A model system for understanding the physical mechanics of gene expression

“…Additionally, the presence of weaker sites flanking a strong binding site could lead to a funnel effect where the molecules are directed to the strong binding site and retained there for longer times [61–63] . However, it is controversial whether TFs can bind at all to weak binding sites [64] , which is a necessary assumption required for the funnel effect hypothesis.…”

Energetic funnel facilitates facilitated diffusion

“…The possibility of speed-up due to a funnel has been already proposed in the literature. A theoretical study of RNAP, ignoring the effects of fluctuations, showed that energy gradients directly translate into a deterministic bias toward the target ( 27 ). A computational study, based on Brownian dynamics simulations of a coarse-grained model of the TF–DNA complex, demonstrated that organizing binding energies in a funnel reduces the search time with respect to the case of randomly organized binding energies ( 28 ).…”

Detection of promoter and non-promoter E.coli sequences by analysis of their electrostatic profiles

“…Различные группы исследователей рассматривали в качестве возможных промоторных детерминант такие физические свойства и геометрические характеристики молекулы ДНК, как электростатический потенциал [Polozov et al, 2005;Камзолова и др., 2009;Sorokin et al, 2006;Kamzolova et al, 2005;Polozov et al, 1999], устойчивость к суперскрученности [Wang, Benham, 2006;Benham, 1996;Benham et al, 1997], термодинамическую стабильность [Jost, Everaers, 2009;Yeramian, 2000], изгибность цепи [Rohs et al, 2009], способность формировать изломы [Jensen et al, 1999], а также доступность и расположение доноров и акцепторов водородных связей в большой борозде промоторной ДНК [Weindl et al, 2009]. Все эти характеристики играют важную роль на различных этапах взаимодействия ДНК и РНК-полимеразы: при первичном узнавании, формировании комплекса «белок-ДНК», синтеза первичного РНК-транскрипта и формировании элонгирующего комплекса.…”