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Single-molecule force measurement opens a new door for investigating detailed biomolecular interactions and their thermodynamic properties by pulling molecules apart while monitoring the force exerted on them. Recent advances in the nonequilibrium work theorem allows one to determine the free-energy landscapes of these events. Such information is valuable for understanding processes such as protein and RNA folding and receptor-ligand binding. Here, we used force as a physical parameter under the traditional chemical and temperature denaturing environment to alter the protein folding energy landscape and compared the change in the unfolding free-energy barrier of the I27 domain of human cardiac titin. We found that the trends in protein unfolding free-energy barriers are consistent for single-molecule force measurements and bulk chemical and temperature studies. The results suggest that the information from single-molecule pulling experiments are meaningful and useful for understanding the mechanism of folding of titin I27.

When analyzing single-molecule data, a low-dimensional set of system observables typically serves as the observational data. We calibrate stochastic dynamical models from time series that record such observables. Numerical techniques for quantifying noise from multiple time scales in a single trajectory, including experimental instrument and inherent thermal noise, are demonstrated. The techniques are applied to study time series coming from both simulations and experiments associated with the nonequilibrium mechanical unfolding of titin's I27 domain. The estimated models can be used for several purposes, (1) detect dynamical signatures of "rare events" by analyzing the effective diffusion and force as a function of the monitored observable, (2) quantify the influence that conformational degrees of freedom, which are typically difficult to directly monitor experimentally, have on the dynamics of the monitored observable, (3) quantitatively compare the inherent thermal noise to other noise sources, for example, instrument noise, variation induced by conformational heterogeneity, and so forth, (4) simulate random quantities associated with repeated experiments, and (5) apply pathwise, that is, trajectory-wise, hypothesis tests to assess the goodness-of-fit of the models and even detect conformational transitions in noisy signals. These items are all illustrated with several examples.

DNA-gold nanoparticle assemblies have shown promise as an alternative technology to DNA microarrays for DNA detection and RNA profiling. Understanding the effect of DNA sequences on the melting temperature of the system is central to developing reliable detection technology. We studied the effects of DNA base-pairing defects, such as mismatches and deletions, on the melting temperature of DNA-nanoparticle assemblies. We found that, contrary to the general assumption that defects lower the melting temperature of DNA, some defects increase the melting temperature of DNA-linked nanoparticle assemblies. The effects of mismatches and deletions were found to depend on the specific base pair, the sequence, and the location of the defects. Our results demonstrate that the surface-bound DNA exhibit hybridization behavior different from that of free DNA. Such findings indicate that a detailed understanding of DNA-nanoparticle assembly phase behavior is required for quantitative interpretation of DNA-nanoparticle aggregation.