RNA polymerase motors: dwell time distribution, velocity and dynamical phases

Tripathi, Tripti; Schütz, Gunter M.; Chowdhury, Debashish

doi:10.1088/1742-5468/2009/08/p08018

Cited by 25 publications

(22 citation statements)

References 32 publications

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“…If more than one RNAP molecule initiates from the same promoter one cannot ignore their mutual interactions. On the one hand, pausing RNAP may block the advancement of trailing RNAP and thus induce "traffic jams" [11,12] and phase transitions in the rate of elongation [13]. On the other hand, by the same token the interaction has been demonstrated to be cooperative: Trailing RNAP strongly prevent backtracking, and even "push" the leading RNAP out of pause sites [14,15,16,17,18,19,20].…”

Section: Introductionmentioning

confidence: 99%

RNA Polymerase interactions and elongation rate

Belitsky

Schütz

2019

Journal of Theoretical Biology

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We show that non-steric molecular interactions between RNA polymerase (RNAP) motors that move simultaneously on the same DNA track determine strongly the kinetics of transcription elongation. With a focus on the role of collisions and cooperation, we introduce a stochastic model that allows for the exact analytical computation of the stationary properties of transcription elongation as a function of RNAP density, their interaction strength, nucleoside triphosphate concentration, and rate of pyrophosphate release. Cooperative pushing, i.e., an enhancement of the average RNAP velocity and elongation rate, arises due to stochastic pushing. This cooperative effect cannot be explained by steric hindrance alone but requires a sufficiently strong molecular repulsion. It disappears beyond a critical RNAP density, above which jamming due to collisions takes over. For strong stochastic blocking the cooperative pushing is suppressed at low RNAP densities, but a reappears at higher densities.

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Section: Introductionmentioning

confidence: 99%

RNA Polymerase interactions and elongation rate

Belitsky

Schütz

2019

Journal of Theoretical Biology

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“…Interestingly, the model can predict transcriptional bursts even in the absence of explicit regulation of the transcription by master proteins 33 . In a third example, dwell--time distributions in a two--state motor model was derived first, and on top of that, RNAP traffic model was developed considering steric interactions among many RNAPs moving simultaneously on the same track 34 . One more example we want to mention here is the development of a 'modular' scheme of the RNAP transcription kinetics 35 , which considers alternative and off--pathway states (e.g.…”

Section: General Physical Models On Polymerasesmentioning

confidence: 99%

Computational investigations on polymerase actions in gene transcription and replication: Combining physical modeling and atomistic simulations

Jin

2016

Chinese Phys. B

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Polymerases are protein enzymes that move along nucleic acid chains and catalyze template--based polymerization reactions during gene transcription and replication. The polymerases also substantially improve transcription or replication fidelity through the non--equilibrium enzymatic cycles. We briefly review computational efforts that have been made toward understanding mechano--chemical coupling and fidelity control mechanisms of the polymerase elongation. The polymerases are regarded as molecular information motors during the elongation process. It requires a full spectrum of computational approaches from multiple time and length scales to understand the full polymerase functional cycle. We keep away from quantum mechanics based approaches to the polymerase catalysis due to abundant former surveys, while address only statistical physics modeling approach and all--atom molecular dynamics simulation approach. We organize this review around our own modeling and simulation practices on a single--subunit T7 RNA polymerase, and summarize commensurate studies on structurally similar DNA polymerases. For multi--subunit RNA polymerases that have been intensively studied in recent years, we leave detailed discussions on the simulation achievements to other computational chemical surveys, while only introduce very recently published representative studies, including our own preliminary work on structure--based modeling on yeast RNA polymerase II. In the end, we quickly go through kinetic modeling on elongation pauses and backtracking activities. We emphasize the fluctuation and control mechanisms of the polymerase actions, highlight the non--equilibrium physical nature of the system, and try to bring some perspectives toward understanding replication and transcription regulation from single molecular details to a genome--wide scale.

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“…For some other motors, which move on nucleic acid strand, the analytical forms of the distributions of the dwell times have been reported recently [7,8].…”

Section: Introductionmentioning

confidence: 99%

Stochastic kinetics of a single-headed motor protein: Dwell time distribution of KIF1A

Garai¹,

Chowdhury²

2011

EPL

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KIF1A, a processive single headed kinesin superfamily motor, hydrolyzes Adenosine triphosphate (ATP) to move along a filamentous track called microtubule. The stochastic movement of KIF1A on the track is characterized by an alternating sequence of pause and translocation. The sum of the durations of pause and the following translocation defines the dwell time. Using the NOSC model (Nishinari et. al. PRL, 95, 118101 (2005)) of individual KIF1A, we systematically derive an analytical expression for the dwell time distribution. More detailed information is contained in the probability densities of the "conditional dwell times" τ±± in between two consecutive steps each of which could be forward (+) or backward (-). We calculate the probability densities Ξ±± of these four conditional dwell times. However, for the convenience of comparison with experimental data, we also present the two distributions Ξ * ± of the times of dwell before a forward (+) and a backward (-) step. In principle, our theoretical prediction can be tested by carrying out single-molecule experiments with adequate spatio-temporal resolution.

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RNA polymerase motors: dwell time distribution, velocity and dynamical phases

Cited by 25 publications

References 32 publications

RNA Polymerase interactions and elongation rate

RNA Polymerase interactions and elongation rate

Computational investigations on polymerase actions in gene transcription and replication: Combining physical modeling and atomistic simulations

Stochastic kinetics of a single-headed motor protein: Dwell time distribution of KIF1A

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