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. 2013 Jun 25;110(26):E2342-51.
doi: 10.1073/pnas.1220699110. Epub 2013 Jun 10.

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

Affiliations

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition

Xiakun Chu et al. Proc Natl Acad Sci U S A. .

Abstract

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding-folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative "coupled binding-folding" and three-state noncooperative "folding prior to binding" scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding-folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding-folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found "U-shape" temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments.

Keywords: energy landscape theory; flexible binding-folding; intrinsically disordered proteins.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
The schematic diagram of three typical association mechanisms for IDPs. The diagonal line represents the cooperative process with binding and folding strongly coupled. The noncooperative processes are represented by the two lines along the rectangular edge, corresponding to binding prior to folding (up) and folding prior to binding (down), respectively.
Fig. 2.
Fig. 2.
Energy landscapes of binding and folding. Logarithms of DOS are plotted as a function of energy for (A) two-state homodimer Arc repressor (PDB ID code 1ARR) and (B) three-state homodimer Lambda Cro repressor (PDB ID code 1COP). formula image and formula image are the energy of interfacial binding and monomeric folding interaction. Logarithm of DOS is plotted as a function of Q for (C) Arc repressor and (D) Lambda Cro repressor. formula image and formula image are the fraction of native binding and folding contacts. Because the homodimers are formed by two identical chains, the folding properties of the two monomers are expected to be same. Here, we use quantities of one of the two monomers to represent the corresponding monomeric folding quantities. Energy is plotted as a function of formula image and formula image for (E) Arc repressor and (F) Lambda Cro repressor. White region is not probed by the binding–folding simulations. Energy is in the reduced unit (73).
Fig. 3.
Fig. 3.
The individual effective binding and folding as well as the whole global binding–folding energy landscapes. Quantified energy landscapes for (A) two-state homodimer Arc repressor and (B) three-state homodimer Lambda Cro repressor. All of the funnels are extracted from the binding–folding simulations. The depth of the funnel in z axis corresponds to the energy. Each stratum perpendicular to the energy axis is an ellipse, of which the area is equal to the entropy S. The semimajor axis of the ellipse is formula image, and a monotonic decreasing function of the fraction of native contacts Q,and formula image is a scaling constant for each funnel to achieve a better visualization. The other semi-axis of the ellipse is therefore given by formula image. The unbound states are located at the top of the funnels with the largest energy, entropy, and smallest Q, and the bottom of the funnel corresponds to the native binding state with formula image and formula image. The shape of the funnels is therefore a representation of the relationship between energy E, entropy S, and structural similarity to native structure Q. The energy and entropy are normalized by the sizes of the homodimers for a better visualization.
Fig. 4.
Fig. 4.
The phase diagram of association mechanism. The phase diagram correlates with the spatial structural property and the topography of effective binding and folding energy landscapes for (A) 10 different-sized homodimers and (B) eight similar-sized homodimers. The structural property is described by the ratio of the native contact number of interface versus intramonomer. The topography of the energy landscapes is quantified by the ratio between the effective energy landscape topography measure for interfacial binding formula image and monomeric folding formula image. The PDB ID codes of the 15 homodimers are shown.
Fig. 5.
Fig. 5.
The effective energy landscape topography measures, considering strength of nonnative interactions, perturbations formula image versus formula image, which corresponds to the pure structure-based model without nonnative interactions, for (A) Arc repressor and (B) Lambda Cro repressor. Red points represent the ratio of formula image, blue points represent the ratio of formula image, and green points represent the ratio of formula image as a function of strength of nonnative interactions. The parameter h modulates the strength of nonnative interactions.
Fig. 6.
Fig. 6.
The correlation between the whole global landscape topography measure formula image and thermodynamics as well as kinetics of global binding–folding. The binding transition against glassy trapping temperature formula image correlated with the whole global landscape topography formula image for (A) 10 different-sized homodimers with correlation 0.94, (B) eight similar-sized homodimers with correlation 0.84, and (C) two-state homodimer Arc repressor and three-state homodimer Lambda Cro repressor with varying energetic roughness, showing a correlation of 0.88. The blue lines in A, B, and C are the analytical mean field theoretical prediction of the relationship between formula image and formula image. The logarithm of global binding–folding time correlated with the whole global landscape topography formula image for (D) 10 different-sized homodimers with correction –0.78, (E) eight similar-sized homodimers with correlation –0.91, and (F) two-state homodimer Arc repressor and three-state homodimer Lambda Cro repressor with varying energetic roughness. The red lines in A–E are the linear fits. Because all of the quantities are found to be size scaled (SI Appendix, Figs. S23–S25), the 15 homodimers in the pure structure-based model are divided into different-sized and similar-sized groups to remove the size effect in the underlying correlation between global landscape topography formula image and thermodynamics, as well as kinetics. The parameter h modulates the strength of nonnative interactions and τ is in the unit of simulation time.
Fig. 7.
Fig. 7.
Kinetics at different temperatures for Troponin C site (PDB ID code 1CTA). (A) The binding–folding time formula image as a function of temperature. The error bar represents the SD of the mean value. (B) The second-order moment ratio of the binding–folding time formula image versus temperature. (C) The evolution of nonnative population at different temperatures above the activated dynamical cross-over temperature formula image. (D) The evolution of nonnative population at different temperatures below the activated dynamical cross-over temperature formula image. The fitting lines in C and D are single exponential. Temperature is in the unit of energy by multiplying Boltzmann constant k, and τ is in the unit of simulation time.

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References

    1. Fischer E. Einfluss der configuration auf die wirkung der enzyme. Ber Dtsch Chem Ges. 1894;27(3):2984–2993.
    1. Koshland DE. Application of a theory of enzyme specificity to protein synthesis. Proc Natl Acad Sci USA. 1958;44(2):98–104. - PMC - PubMed
    1. Bosshard HR. Molecular recognition by induced fit: How fit is the concept? News Physiol Sci. 2001;16(4):171–173. - PubMed
    1. Wright PE, Dyson HJ. Intrinsically unstructured proteins: Re-assessing the protein structure-function paradigm. J Mol Biol. 1999;293(2):321–331. - PubMed
    1. Dunker AK, et al. Intrinsically disordered protein. J Mol Graph Model. 2001;19(1):26–59. - PubMed

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