No Arabic abstract
Biopolymer self-assembly pathways are central to biological activity, but are complicated by the ability of the monomeric subunits of biopolymers to adopt different conformational states. As a result, biopolymer nucleation often involves a two-step mechanism where the monomers first condense to form a metastable intermediate, and this then converts to a stable polymer by conformational rearrangement of its constituent monomers. While existing mathematical models neglect the dynamics by which intermediates convert to stable polymers, experiments and simulations show that these dynamics frequently occur on comparable timescales to condensation of intermediates and growth of mature polymers, and thus cannot be ignored. Moreover, nucleation intermediates are responsible for cell toxicity in pathologies such as Alzheimers, Parkinsons, and prion diseases. Due to the relationship between conformation and biological function, the slow conversion dynamics of these species will strongly affect their toxicity. In this study, we present a modified Oosawa model which explicitly accounts for simultaneous assembly and conversion. To describe the conversion dynamics, we propose an experimentally motivated initiation-propagation (IP) mechanism in which the stable phase arises locally within the intermediate, and then spreads through additional conversion events induced by nearest-neighbor interactions, analogous to one-dimensional Glauber dynamics. Our mathematical analysis shows that the competing timescales of assembly and conversion result in a nonequilibrium critical point, separating a regime where intermediates are kinetically unstable from one where conformationally mixed intermediates can accumulate. Our work provides the first general model of two-step biopolymer nucleation, which can be used to quantitatively predict the concentration and composition of biologically crucial intermediates.
In many systems, nucleation of a stable solid may occur in the presence of other (often more than one) metastable phases. These may be polymorphic solids or even liquid phases. In such cases, nucleation of the solid phase from the melt may be facilitated by the metastable phase because the latter can wet the interface between the parent and the daughter phases, even though there may be no signature of the existence of metastable phase in the thermodynamic properties of the parent liquid and the stable solid phase. Straightforward application of classical nucleation theory (CNT) is flawed here as it overestimates the nucleation barrier since surface tension is overestimated (by neglecting the metastable phases of intermediate order) while the thermodynamic free energy gap between daughter and parent phases remains unchanged. In this work we discuss a density functional theory (DFT) based statistical mechanical approach to explore and quantify such facilitation. We construct a simple order parameter dependent free energy surface that we then use in DFT to calculate (i) the order parameter profile, (ii) the overall nucleation free energy barrier and (iii) the surface tension between the parent liquid and the metastable solid and also parent liquid and stable solid phases. The theory indeed finds that the nucleation free energy barrier can decrease significantly in the presence of wetting. This approach can provide a microscopic explanation of Ostwald step rule and the well-known phenomenon of disappearing polymorphs that depends on temperature and other thermodynamic conditions. Theory reveals a diverse scenario for phase transformation kinetics some of which may be explored via modern nanoscopic synthetic methods.
Test experiments of hybridization in DNA microarrays show systematic deviations from the equilibrium isotherms. We argue that these deviations are due to the presence of a partially hybridized long-lived state, which we include in a kinetic model. Experiments confirm the model predictions for the intensity vs. free energy behavior. The existence of slow relaxation phenomena has important consequences for the specificity of microarrays as devices for the detection of a target sequence from a complex mixture of nucleic acids.
In single molecule laser optical tweezer (LOT) pulling experiments a protein or RNA is juxtaposed between DNA handles that are attached to beads in optical traps. The LOT generates folding trajectories under force in terms of time-dependent changes in the distance between the beads. How to construct the full intrinsic folding landscape (without the handles and the beads) from the measured time series is a major unsolved problem. By using rigorous theoretical methods---which account for fluctuations of the DNA handles, rotation of the optical beads, variations in applied tension due to finite trap stiffness, as well as environmental noise and the limited bandwidth of the apparatus---we provide a tractable method to derive intrinsic free energy profiles. We validate the method by showing that the exactly calculable intrinsic free energy profile for a Generalized Rouse Model, which mimics the two-state behavior in nucleic acid hairpins, can be accurately extracted from simulated time series in a LOT setup regardless of the stiffness of the handles. We next apply the approach to trajectories from coarse grained LOT molecular simulations of a coiled-coil protein based on the GCN4 leucine zipper, and obtain a free energy landscape that is in quantitative agreement with simulations performed without the beads and handles. Finally, we extract the intrinsic free energy landscape from experimental LOT measurements for the leucine zipper, which is independent of the trap parameters.
By combining analytical and numerical calculations, we investigate the minimal-energy shape of short DNA loops of approximately $100$ base pairs (bp). We show that in these loops the excess twist density oscillates as a response to an imposed bending stress, as recently found in DNA minicircles and observed in nucleosomal DNA. These twist oscillations, here referred to as twist waves, are due to the coupling between twist and bending deformations, which in turn originates from the asymmetry between DNA major and minor grooves. We introduce a simple analytical variational shape, that reproduces the exact loop energy up to the fourth significant digit, and is in very good agreement with shapes obtained from coarse-grained simulations. We, finally, analyze the loop dynamics at room temperature, and show that the twist waves are robust against thermal fluctuations. They perform a normal diffusive motion, whose origin is briefly discussed.
By means of computer simulations of a coarse-grained DNA model we show that the DNA hairpin zippering dynamics is anomalous, i.e. the characteristic time T scales non-linearly with N, the hairpin length: T ~ N^a with a>1. This is in sharp contrast with the prediction of the zipper model for which T ~ N. We show that the anomalous dynamics originates from an increase in the friction during zippering due to the tension built in the closing strands. From a simple polymer model we get a = 1+ nu = 1.59 with nu the Flory exponent, a result which is in agreement with the simulations. We discuss transition path times data where such effects should be detected.