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Stochastic emergence of multiple intermediates detected by single-molecule quasi-static mechanical unfolding of protein

View Article: PubMed Central - PubMed

ABSTRACT

Experimental probing of a protein-folding energy landscape can be challenging, and energy landscapes comprising multiple intermediates have not yet been defined. Here, we quasi-statically unfolded single molecules of staphylococcal nuclease by constant-rate mechanical stretching with a feedback positioning system. Multiple discrete transition states were detected as force peaks, and only some of the multiple transition states emerged stochastically in each trial. This finding was confirmed by molecular dynamics simulations, and agreed with another result of the simulations which showed that individual trajectories took highly heterogeneous pathways. The presence of Ca2+ did not change the location of the transition states, but changed the frequency of the emergence. Transition states emerged more frequently in stabilized domains. The simulations also confirmed this feature, and showed that the stabilized domains had rugged energy surfaces. The mean energy required per residue to disrupt secondary structures was a few times the thermal energy (1–3 kBT), which agreed with the stochastic feature. Thus, single-molecule quasi-static measurement has achieved notable success in detecting stochastic features of a huge number of possible conformations of a protein.

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Agreement between experiments and MD simulations in the distribution of force-peak locations. (a and b) Distribution of force-peak locations in force-extension relationships derived experimentally, as shown in Fig. 2a–e and f–j from 42 and 43 force-extension curves in the absence and presence of Ca2+, respectively. (c and d) Distribution derived by MD simulations as shown in Supplementary Information, Fig. S3, a–e and f–j in the absence and presence of Ca2+, respectively, each from 50 force-extension curves. The peaks in (a) and (b) are at extensions of 7, 12, 20, 28, 34 and 46.5 nm.
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f3-5_25: Agreement between experiments and MD simulations in the distribution of force-peak locations. (a and b) Distribution of force-peak locations in force-extension relationships derived experimentally, as shown in Fig. 2a–e and f–j from 42 and 43 force-extension curves in the absence and presence of Ca2+, respectively. (c and d) Distribution derived by MD simulations as shown in Supplementary Information, Fig. S3, a–e and f–j in the absence and presence of Ca2+, respectively, each from 50 force-extension curves. The peaks in (a) and (b) are at extensions of 7, 12, 20, 28, 34 and 46.5 nm.

Mentions: Force peaks accompanied by a decrease within 2 nm in the force amplitude three times larger than the noise amplitude (experiments, Fig. 2; MD simulations, Fig. S3) were used to analyze force-peak distribution in both experiments (Fig. 3a, b) and MD simulations (Fig. 3c, d). Noise amplitude was determined as the standard deviation of the force amplitude in the force-extension relationship after subtracting 3-nm moving averages.


Stochastic emergence of multiple intermediates detected by single-molecule quasi-static mechanical unfolding of protein
Agreement between experiments and MD simulations in the distribution of force-peak locations. (a and b) Distribution of force-peak locations in force-extension relationships derived experimentally, as shown in Fig. 2a–e and f–j from 42 and 43 force-extension curves in the absence and presence of Ca2+, respectively. (c and d) Distribution derived by MD simulations as shown in Supplementary Information, Fig. S3, a–e and f–j in the absence and presence of Ca2+, respectively, each from 50 force-extension curves. The peaks in (a) and (b) are at extensions of 7, 12, 20, 28, 34 and 46.5 nm.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5036639&req=5

f3-5_25: Agreement between experiments and MD simulations in the distribution of force-peak locations. (a and b) Distribution of force-peak locations in force-extension relationships derived experimentally, as shown in Fig. 2a–e and f–j from 42 and 43 force-extension curves in the absence and presence of Ca2+, respectively. (c and d) Distribution derived by MD simulations as shown in Supplementary Information, Fig. S3, a–e and f–j in the absence and presence of Ca2+, respectively, each from 50 force-extension curves. The peaks in (a) and (b) are at extensions of 7, 12, 20, 28, 34 and 46.5 nm.
Mentions: Force peaks accompanied by a decrease within 2 nm in the force amplitude three times larger than the noise amplitude (experiments, Fig. 2; MD simulations, Fig. S3) were used to analyze force-peak distribution in both experiments (Fig. 3a, b) and MD simulations (Fig. 3c, d). Noise amplitude was determined as the standard deviation of the force amplitude in the force-extension relationship after subtracting 3-nm moving averages.

View Article: PubMed Central - PubMed

ABSTRACT

Experimental probing of a protein-folding energy landscape can be challenging, and energy landscapes comprising multiple intermediates have not yet been defined. Here, we quasi-statically unfolded single molecules of staphylococcal nuclease by constant-rate mechanical stretching with a feedback positioning system. Multiple discrete transition states were detected as force peaks, and only some of the multiple transition states emerged stochastically in each trial. This finding was confirmed by molecular dynamics simulations, and agreed with another result of the simulations which showed that individual trajectories took highly heterogeneous pathways. The presence of Ca2+ did not change the location of the transition states, but changed the frequency of the emergence. Transition states emerged more frequently in stabilized domains. The simulations also confirmed this feature, and showed that the stabilized domains had rugged energy surfaces. The mean energy required per residue to disrupt secondary structures was a few times the thermal energy (1–3 kBT), which agreed with the stochastic feature. Thus, single-molecule quasi-static measurement has achieved notable success in detecting stochastic features of a huge number of possible conformations of a protein.

No MeSH data available.


Related in: MedlinePlus