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Kinetic regulation of multi-ligand binding proteins.

Salakhieva DV, Sadreev II, Chen MZ, Umezawa Y, Evstifeev AI, Welsh GI, Kotov NV - BMC Syst Biol (2016)

Bottom Line: Therefore, buffering effects significantly influence the amounts of free ligands.The presented model makes predictions for the temporal distribution of multisite protein conformations in complex with variable numbers of ligands.Furthermore, it derives the characteristic time and the dynamics for the kinetic responses elicited by a ligand concentration change as a function of ligand concentration and the number of ligand binding sites.

View Article: PubMed Central - PubMed

Affiliation: Kazan (Volga Region) Federal University, 18 Kremlyovskaya St., 420008, Kazan, Russia.

ABSTRACT

Background: Second messengers, such as calcium, regulate the activity of multisite binding proteins in a concentration-dependent manner. For example, calcium binding has been shown to induce conformational transitions in the calcium-dependent protein calmodulin, under steady state conditions. However, intracellular concentrations of these second messengers are often subject to rapid change. The mechanisms underlying dynamic ligand-dependent regulation of multisite proteins require further elucidation.

Results: In this study, a computational analysis of multisite protein kinetics in response to rapid changes in ligand concentrations is presented. Two major physiological scenarios are investigated: i) Ligand concentration is abundant and the ligand-multisite protein binding does not affect free ligand concentration, ii) Ligand concentration is of the same order of magnitude as the interacting multisite protein concentration and does not change. Therefore, buffering effects significantly influence the amounts of free ligands. For each of these scenarios the influence of the number of binding sites, the temporal effects on intermediate apo- and fully saturated conformations and the multisite regulatory effects on target proteins are investigated.

Conclusions: The developed models allow for a novel and accurate interpretation of concentration and pressure jump-dependent kinetic experiments. The presented model makes predictions for the temporal distribution of multisite protein conformations in complex with variable numbers of ligands. Furthermore, it derives the characteristic time and the dynamics for the kinetic responses elicited by a ligand concentration change as a function of ligand concentration and the number of ligand binding sites. Effector proteins regulated by multisite ligand binding are shown to depend on ligand concentration in a highly nonlinear fashion.

No MeSH data available.


Related in: MedlinePlus

Model predictions for the time required for multisite protein conformations to reach their maximal and half growth concentrations. The non-dimensional characteristic times, τmmaxk− (m = 1, 2, 3) for intermediate (a), τ00.5k− for apo- and τ40.5k− for fully bound (b) multisite protein conformations are shown as a function of the step change ligand concentration from UT0/K = 0.1 to UT1/K and LT/K = 3
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Fig9: Model predictions for the time required for multisite protein conformations to reach their maximal and half growth concentrations. The non-dimensional characteristic times, τmmaxk− (m = 1, 2, 3) for intermediate (a), τ00.5k− for apo- and τ40.5k− for fully bound (b) multisite protein conformations are shown as a function of the step change ligand concentration from UT0/K = 0.1 to UT1/K and LT/K = 3

Mentions: Figure 9a shows the model predictions for the characteristic time required for intermediate protein conformations with one, two and three bound ligands to reach their highest concentrations in response to a step change in ligand concentration (Eq. (50) in Methods). The model predicts that the characteristic time τ00.5, required for the apo- form to reach its half growth level monotonically decreases with the increase of the total ligand concentration. However, the characteristic time constant τ40.5, which represents the saturated conformation reveals a distorted bell shaped dependence on ligand concentration (Fig. 9b and Eqs. (52) in Methods). This bell shaped dependence, which was also observed in Fig. 3d, can also be explained by the presence of intermediate conformations. The distortion of the bell shape in Fig. 9b appears to be due to the ligand consumption that is included into the consideration in this section and was not considered in Fig. 3d. This result may be significant for the dynamics of CaM activation as our model predicts that with an increase of the total ligand concentration, the limited amount of ligand leads to an additional increase of τ40.5 compared to the case without the ligand consumption. The model, therefore, predicts possible transient differences in multisite protein signal transduction in response to fast transient kinetics of multisite proteins.Fig. 9


Kinetic regulation of multi-ligand binding proteins.

Salakhieva DV, Sadreev II, Chen MZ, Umezawa Y, Evstifeev AI, Welsh GI, Kotov NV - BMC Syst Biol (2016)

Model predictions for the time required for multisite protein conformations to reach their maximal and half growth concentrations. The non-dimensional characteristic times, τmmaxk− (m = 1, 2, 3) for intermediate (a), τ00.5k− for apo- and τ40.5k− for fully bound (b) multisite protein conformations are shown as a function of the step change ligand concentration from UT0/K = 0.1 to UT1/K and LT/K = 3
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4835871&req=5

Fig9: Model predictions for the time required for multisite protein conformations to reach their maximal and half growth concentrations. The non-dimensional characteristic times, τmmaxk− (m = 1, 2, 3) for intermediate (a), τ00.5k− for apo- and τ40.5k− for fully bound (b) multisite protein conformations are shown as a function of the step change ligand concentration from UT0/K = 0.1 to UT1/K and LT/K = 3
Mentions: Figure 9a shows the model predictions for the characteristic time required for intermediate protein conformations with one, two and three bound ligands to reach their highest concentrations in response to a step change in ligand concentration (Eq. (50) in Methods). The model predicts that the characteristic time τ00.5, required for the apo- form to reach its half growth level monotonically decreases with the increase of the total ligand concentration. However, the characteristic time constant τ40.5, which represents the saturated conformation reveals a distorted bell shaped dependence on ligand concentration (Fig. 9b and Eqs. (52) in Methods). This bell shaped dependence, which was also observed in Fig. 3d, can also be explained by the presence of intermediate conformations. The distortion of the bell shape in Fig. 9b appears to be due to the ligand consumption that is included into the consideration in this section and was not considered in Fig. 3d. This result may be significant for the dynamics of CaM activation as our model predicts that with an increase of the total ligand concentration, the limited amount of ligand leads to an additional increase of τ40.5 compared to the case without the ligand consumption. The model, therefore, predicts possible transient differences in multisite protein signal transduction in response to fast transient kinetics of multisite proteins.Fig. 9

Bottom Line: Therefore, buffering effects significantly influence the amounts of free ligands.The presented model makes predictions for the temporal distribution of multisite protein conformations in complex with variable numbers of ligands.Furthermore, it derives the characteristic time and the dynamics for the kinetic responses elicited by a ligand concentration change as a function of ligand concentration and the number of ligand binding sites.

View Article: PubMed Central - PubMed

Affiliation: Kazan (Volga Region) Federal University, 18 Kremlyovskaya St., 420008, Kazan, Russia.

ABSTRACT

Background: Second messengers, such as calcium, regulate the activity of multisite binding proteins in a concentration-dependent manner. For example, calcium binding has been shown to induce conformational transitions in the calcium-dependent protein calmodulin, under steady state conditions. However, intracellular concentrations of these second messengers are often subject to rapid change. The mechanisms underlying dynamic ligand-dependent regulation of multisite proteins require further elucidation.

Results: In this study, a computational analysis of multisite protein kinetics in response to rapid changes in ligand concentrations is presented. Two major physiological scenarios are investigated: i) Ligand concentration is abundant and the ligand-multisite protein binding does not affect free ligand concentration, ii) Ligand concentration is of the same order of magnitude as the interacting multisite protein concentration and does not change. Therefore, buffering effects significantly influence the amounts of free ligands. For each of these scenarios the influence of the number of binding sites, the temporal effects on intermediate apo- and fully saturated conformations and the multisite regulatory effects on target proteins are investigated.

Conclusions: The developed models allow for a novel and accurate interpretation of concentration and pressure jump-dependent kinetic experiments. The presented model makes predictions for the temporal distribution of multisite protein conformations in complex with variable numbers of ligands. Furthermore, it derives the characteristic time and the dynamics for the kinetic responses elicited by a ligand concentration change as a function of ligand concentration and the number of ligand binding sites. Effector proteins regulated by multisite ligand binding are shown to depend on ligand concentration in a highly nonlinear fashion.

No MeSH data available.


Related in: MedlinePlus