A mathematical model for human nucleotide excision repair: damage recognition by random order assembly and kinetic proofreading - PubMed (original) (raw)

A mathematical model for human nucleotide excision repair: damage recognition by random order assembly and kinetic proofreading

Kevin J Kesseler et al. J Theor Biol. 2007.

Abstract

A mathematical model of human nucleotide excision repair was constructed and validated. The model incorporates cooperative damage recognition by RPA, XPA, and XPC followed by three kinetic proofreading steps by the TFIIH transcription/repair factor. The model yields results consistent with experimental data regarding excision rates of UV photoproducts by the reconstituted human excision nuclease system as well as the excision of oligonucleotides from undamaged DNA. The model predicts the effect that changes in the initial concentrations of repair factors have on the excision rate of damaged DNA and provides a testable hypothesis on the biochemical mechanism of cooperativity in protein assembly, suggesting experiments to determine if cooperativity in protein assembly results from an increased association rate or a decreased dissociation rate. Finally, a comparison between the random order assembly with kinetic proofreading model and a sequential assembly model is made. This investigation reveals the advantages of the random order assembly/kinetic proofreading model.

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Figures

Figure 1

Schematic of Nucleotide Excision Repair. This figure shows a schematic diagram representing how excision repair is assumed to operate in the random order cooperative assembly and kinetic proofreading model of human excision repair.

Figure 2

Schematic of the Nucleotide Excision Repair model. This figure shows a schematic diagram of the allowable states of the DNA substrate in the model and how they can evolve.

Figure 3

Scatter plots – these panels show results with the model tuned to results from experiments with T<>T dimers (panel A) (Table 4, run 2a) and (6 – 4) photoproducts (Table 5, runs 1 (panel C), 2a (panel B), and 3c (panel D). Each of these panels compares output from the model with experimental results. Each point represents the amount of DNA excision observed in an experiment (the x-coordinate) and the amount excised in a simulation of the experiment using the model (the y-coordinate). The maximal observed excision was 1.5% for T<>T dimers and 12.5% for (6 – 4) photoproducts.

Figure 4

The total normalized squared error from simulating seven different runs from Table 5. The color indicates the error with red being 0 and blue being 5 as shown in the color scale to the right of the figure. The parameters being varied are kPrD, the probability that kinetic proofreading mistakenly dissociates the complex from damaged DNA, and _k_1, the rate at which the complex with all three repair factors undergoes kinetic proofreading. The horizontal axis indicates the variable kPrD (ranging from 0.05 to 0.15) and the vertical axis indicates the parameter _k_1 (ranging from 0.01 to 0.11). Seven different experiments were conducted with each pair of parameter values and the error between the simulations and experiments was calculated.

Figure 5

Repair factor binding isotherms: This figure shows the results of a simulation that models the experiment to determine the dissociation constant for all three repair factors. The percentage of each repair factor bound to DNA vs. the concentration of the repair factor was plotted for undamaged DNA (blue), the T <> T dimer (red), and the 6–4 photoproduct (green). The filled circles connect by dotted lines are experimental results (with error bars), the lines simulated results.

Figure 6

Effect of concentrations of damage recognition factors on repair rate: Each panel shows the effects of varying the concentration of the indicated repair factor on the simulated amount of DNA excised. Each repair factor is varied from 10−4 to 102 times the baseline value while holding the concentrations of the other repair factors constant (the y-axis is a log scale varying from 10−3nM to 5 × 10−2nM).

Figure 7

Cooperativity study: This figure shows how cooperativity affects excision in the model. In the upper 2 panels the x-axis gives the concentration of the repair factors (which range from 10−2 to 102 times the baseline values) and the y-axis gives the value of the cooperativity constant (which ranges from 1 to 100). The color indicates the amount of excision with blue being low and red being high as shown in the color scale in the lower right frame. The upper left frame is the backward cooperativity study and the upper right frame is the forward cooperativity study. The lower left frame is a comparison of the forward cooperativity model (red) and the backward cooperativity model (blue) for a cooperativity constant of 10 in both models.

Figure 8

Random vs. sequential assembly: This figure shows the effect of changing the concentration of repair factors on the amount of (6–4) PP excised for five different configurations of the model: Black is the standard random order assembly model; Red is the sequential model in which the order of binding is RPA, XPA, then XPC; Green is the sequential model where the order of binding was XPC, XPA, then RPA; Purple is the hybrid model where RPA is required to bind first; and Blue is the hybrid model where XPC is required to bind first.

Figure 9

Figure 10

Example of free energy considerations for modeling cooperativity. This figure shows the correct (right) and incorrect (left) ways of handling energy considerations when modeling cooperativity. In both panels complex A represents DNA alone, complexes _B_1 and _B_2 represent DNA with RPA or XPA respectively bound to DNA, and complex _C_12 represents DNA with RPA and XPA bound to DNA.

References

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A mathematical model for human nucleotide excision repair: damage recognition by random order assembly and kinetic proofreading - PubMed (original) (raw)