The Wilemski-Fixman model of diffusion controlled-reactions [J. Chem. Phys. 58, 4009 (1973)] is combined with a generalized random walk description of chain conformations to predict the dependence of the closure time tau on the chain length N of polymers with reactive end groups and nonlocal interactions. The nonlocal interactions are modeled by a modification to the connectivity term in the Edwards continuum representation of the polymer. The modification involves a parameter h lying between 0 and 1 that is a measure of the extent of correlation between adjacent monomers on the chain backbone. Different choices of h correspond to chain conformations of different average radial dimensions. In particular, the values 1/3, 1/2 and 3/5 provide approximations to the statistics of polymers in poor, theta and good solvents, respectively. The closure time tau of such chains is calculated analytically for different N. In all cases, tau is found to vary as a power law in N, Nb, with b a function of h. For the special case h = 1/3, which models collapsed polymers and globular proteins, b is about 1.6-1.7.

Time-dependent fluctuations in the distance x(t) between two segments along a polymer are one measure of its overall conformational dynamics. The dynamics of x(t), modeled as the coordinate of a particle moving in a one-dimensional potential well in thermal contact with a reservoir, is treated with a generalized Langevin equation whose memory kernel K(t) can be calculated from the time-correlation function of distance fluctuations C(t) identical with x(0)x(t). We compute C(t) for a semiflexible continuum model of the polymer and use it to determine K(t) via the GLE. The calculations demonstrate that C(t) is well approximated by a Mittag-Leffler function and K(t) by a power-law decay on time scales of several decades. Both functions depend on a number of parameters characterizing the polymer, including chain length, degree of stiffness, and the number of intervening residues between the two segments. The calculations are compared with the recent observation of a nonexponential C(t) and a power law K(t) in the conformational dynamics within single molecule proteins [Min et al., Phys. Rev. Lett. 94, 198302 (2005)].

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In this paper we explore the rupture dynamics of a model polymer system to capture the microscopic mechanism during relative motion of surfaces at the single polymer level. Our model is similar to the model for friction introduced by Filippov, Klafter, and Urbakh [Filippov et al., Phys. Rev. Lett., 2004, 92, 135503]; but with an important generalization to a flexible transducer (modelled as a bead spring polymer) which is attached to a fixed rigid planar substrate by interconnecting bonds (modelled as harmonic springs), and pulled by a constant force FT. Bonds are allowed to rupture stochastically. The model is simulated, and the results for a certain set of parameters exhibit a sequential rupture mechanism resulting in rupture fronts. A mean field formalism is developed to study these rupture fronts and the possible propagating solutions for the coupled bead and bond dynamics, where the coupling excludes an exact analytical treatment. Numerical solutions to mean field equations are obtained by standard numerical techniques, and they agree well with the simulation results which show sequential rupture. Within a travelling wave formalism based on the Tanh method, we show that the velocity of the rupture front can be obtained in closed form. The derived expression for the rupture front velocity gives good agreement with the stochastic and mean field results, when the rupture is sequential, while propagating solutions for bead and bond dynamics are shown to agree under certain conditions.

Random copolymers made up of subunits with arbritary degrees of flexibility are useful as models of biomolecules with different kinds of secondary structural motifs. We show that the mean square end-to-end distance ͗R 2 ͘ of a two-letter A -B random heteropolymer in which the constituent polymeric subunits are represented as continuum wormlike chains and the randomness is described by the two-state Markov process introduced by Fredrickson, Milner, and Leibler ͓Macromolecules 25, 6341 ͑1992͔͒ can be obtained in closed form. The expression for ͗R 2 ͘ is a function of several parameters, including the number n of subunits, the fraction f of one kind of subunit, the persistence lengths l A and l B of the two subunits, and the degree of correlation between successive subunits.The variation of ͗R 2 ͘ with each of these parameters is discussed.