Aug 2026· Journal of Chemical Physics· Vol 165 5· 0 citations· 35 references
Medicine
Abstract
Helical segments in polymer chains are often transient, finite, and dynamically evolving, yet their origin and stability remain incompletely understood. Here, we develop a minimal coarse-grained statistical-mechanical theory that explains how such "living helices" emerge in fluctuating polymer systems. Using a three-state model with cooperative interactions, we show that helix formation proceeds through a multistep nucleation mechanism. An initial constrained pre-nucleus forms first, followed by cooperative stabilization that promotes the growth of finite helical segments. The resulting free-energy landscape naturally favors marginally stable helices whose size is determined by a competition between cooperative gains and nonlinear penalties arising from stiffness, torsional strain, and solvent fluctuations. By formulating the dynamics as a stochastic process in segment size, we derive analytical expressions for both formation times and lifetimes within a mean first-passage framework. For representative parameters relevant to flexible polymers and peptide segments, the theory predicts characteristic timescales in the nanosecond to sub-microsecond range. These results provide a unified physical picture of "living helices" as finite, mobile, and fluctuating excitations and identify cooperativity and fluctuations as the key determinants of transient secondary structure in polymeric systems.
Macromolecular coil-to-helix transitions simultaneously modify local geometry and persistence length, driving complex changes in overall chain size. Here, we apply the wormlike (persistent) chain model to both coil and helical fragments to examine how the degree of helicity, θ, and average helical fragment length, kh, dictate global chain dimensions. Using scaling arguments, we construct a conformational diagram comprising six distinct regimes for the end-to-end distance. We then employ a minimal coarse-grained molecular dynamics model to verify the theory. Mapping structural properties extracted from these simulations onto the proposed regime diagram enables direct quantitative comparison. This, alongside microscopic conformational analysis, corroborates our theoretical framework. We highlight that the competition between local chain compactization and increased stiffness upon helix formation produces a non-monotonic behavior of the end-to-end distance. Furthermore, to demonstrate the generality of our approach, we systematically vary the hydrogen-bonding monomer spacing m for pairs {i, i + m}. Spacings of m = 4, 5, and 6 are used as coarse-grained representations of α-, π-, and 1-7 helices, respectively. As m increases, the helix becomes locally more compact while its persistence length grows. The regime diagrams constructed for these distinct configurations, combined with robust quantitative agreement between theory and simulation, demonstrate that our framework effectively captures how variations in helix geometry and stiffness control macromolecular dimensions across the transition.
Karthik C Sinha, Alexey A. Gavrilov, A. Rumyantsev· Journal of Chemical Physics· 1 citation
We investigate the structure and dynamics of a polymer in a fluid containing mobile spherical colloidal crowders of radius $R$. We compare and contrast the behavior with Langevin dynamics (LD) and lattice--Boltzmann molecular dynamics (LBMD), the latter incorporating long-range hydrodynamic interactions. Both the colloid size relative to the monomer radius $r$ and the volume fraction $\phi$ are varied to determine how crowding modifies polymer behavior. Increasing volume fraction induces polymer compaction, with the mechanism strongly dependent on the size ratio $R/r$. Small colloids primarily modify the short-wavelength polymer conformation, causing self-avoiding-walk-like behavior to persist to shorter length scales, whereas large colloids reduce the effective long-wavelength Flory exponent, indicating degraded solvent quality consistent with a confinement-blob picture. Polymer diffusion exhibits distinct behavior in LD and LBMD. In LD, diffusion decreases rapidly and depends strongly on $R/r$; a phenomenological scaling involving $\ln(1+R/r)$ captures this size dependence, and additional scaling with $R_g$ reduces scatter, indicating polymer-scale correlations induced by crowding. In contrast, LBMD diffusion follows an effective-medium-like exponential dependence on concentration, governed by hydrodynamic coupling. Rouse-mode analysis identifies three regimes: scaling breakdown at low volume fraction, Zimm-like behavior at intermediate density in both LD and LB, and at high density hydrodynamic screening in LB with confinement-dominated dynamics in LD.
Setarehalsadat Changizrezaei, C. Denniston· 0 citations
This work presents a minimal coarse-grained molecular dynamics model for the coil-helix transition in polymers. We demonstrate that the addition of a Morse potential to a freely jointed chain with volume and bond potentials is sufficient to reproduce the essential thermodynamic features of the transition. From the simulations performed, the Zimm-Bragg propagation parameter s and nucleation parameter σ are extracted, providing quantitative measures of helical propensity and cooperativity, respectively. To illustrate the versatility of the model, this study systematically varies the spacing between hydrogen-bonding monomers using an i → i + m motif, with m = 4, 5, and 6 corresponding to coarse-grained representations of α-, π-, and 1-7 helices. This approach is used to evaluate how hydrogen-bond spacing influences the transition behavior and the resulting cooperativity. As the monomer spacing m between hydrogen-bonding pairs increases, the number of monomers that must be confined for the first hydrogen bond to form also increases, leading to increased cooperativity (lower nucleation parameter σ) and a sharper transition, as reflected in the simulation results. This behavior is consistent with that observed in natural helices of different types, underscoring the model's ability to capture how molecular architecture governs helix formation.
Karthik C Sinha, Alexey A. Gavrilov, A. Rumyantsev· Journal of Chemical Physics· 1 citation
Melt memory in semicrystalline polymers is the remarkable ability of polymer chains to retain structural information from a prior crystalline state after being heated above the melting temperature. This phenomenon can induce extraordinary self-nucleation and strongly influence crystallization kinetics and final material properties, yet its molecular origin remains unresolved. Here, using molecular dynamics simulations of linear polymer chains in which the strength of nonbonded interchain interactions is systematically tuned, we show that enhanced interchain attractions stabilize nanoscale regions of increased density and extended trans-planar conformations that persist in the melt, as revealed by analyzing the dynamics through a density-field approach. These residual ordered regions in the melt act as self-nuclei upon cooling, providing a molecular explanation for experimental observations of persistent melt memory in polar polymers. By varying a single chemically meaningful parameter, i.e., the strength of interchain attraction, our model bridges weakly interacting polyolefins and polymers with stronger dipolar or hydrogen-bonding interactions, establishing a direct link between molecular cohesion and memory retention. The results demonstrate that melt memory originates from the interaction-mediated survival of localized structural order in the melt rather than from a completely randomized chain state. These findings provide a molecular framework connecting the chemical structure, intermolecular forces, and macroscopic crystallization behavior, offering new principles for controlling polymer solidification and designing semicrystalline materials with tailored properties.
A. de Nicola, A. Müller, Dario Cavallo et al.· Journal of the American Chem...· 0 citations
Active matter systems exhibit unique nonequilibrium phenomena that bridge the fields of soft condensed matter and biological physics. In this study, we investigate the structural and dynamical behaviors of a six-armed star copolymer immersed in a dense bath of active Brownian particles (ABPs) via Langevin dynamics simulations. Our results reveal a universal scaling relation for rotational dynamics: ω ∼ Pe1.2, which is independent of the copolymer's bending rigidity κ, thereby confirming the Péclet number (Pe) as the key variable governing nonequilibrium kinetics. Through a torque balance analysis to rotational dissipation, we derive theoretical bounds on the scaling exponent and relate the observed value n ≈ 1.2 to the weakly nonlinear regime where activity-driven accumulation competes with self-propelled escape. We find that interaction potential parameters finely tune the system's behavior: stronger and longer-range interactions promote compact conformations at low ABP densities, while enhancing rotational dynamics. At higher ABP densities, crowding effects dominate, leading to non-monotonic structural and dynamical responses. The effective diffusivity follows Deff/D0 ∼ 1 + αPe2 at moderate Pe and transitions to a different scaling regime (Pe1.3) at high Pe. Our analysis reveals that rotational motion is a finite-range phenomenon: for short arm lengths, the polymer arms sustain bent conformations enabling ABP collection and persistent rotation; other active-particle-induced arm collapse causes rotation to cease. These findings provide a theoretical framework for the quantitative design of active polymer composites and have important implications for intelligent soft materials and micro-nano robotics.
Yiqi Xia, Zihang Bao, Lixiang Cai et al.· RSC Advances· 0 citations
Cooperative dynamics in soft materials such as colloidal suspensions, gels, and polymers stem from complex surface interactions and structural heterogeneities, driving behaviors such as yielding, failure, and avalanches. In X-ray photon correlation spectroscopy (XPCS), these dynamics manifest as localized decorrelation bursts in the two-time intensity correlation function, whose physical significance has remained difficult to quantify with traditional models that assume uniform and random motion. Here, we develop a deep-learning framework that detects and tracks such bursts as individual dynamical events. Combining theoretical validation with XPCS measurements of dense colloidal suspensions, we show that cooperative rearrangement regions (CRRs) are organized into temporally correlated hierarchies and cascades, with event durations and recurrence patterns that depart from homogeneous relaxation models. The results reveal a multiscale pathway for structural relaxation in dense colloids and demonstrate that intermittent features in XPCS encode physically meaningful cooperative dynamics. Our approach provides a route to quantifying avalanche-like and heterogeneous relaxation in soft, glassy, and disordered materials. We introduce an AI-powered framework that interprets intermittent bursts in two-time correlation functions as spatiotemporal "objects". Leveraging deep learning, it detects and tracks CRRs, extracting their occurrence times and durations to support detailed analysis. Validated through theory and experiment, this approach reveals the hierarchical and cascading nature of CRRs, offering new insights into relaxation dynamics in dense colloidal suspensions. It provides a robust tool for investigating complex behaviors in disordered systems.
Hong He, Yuan Tian, Heyi Liang et al.· Soft Matter· 0 citations