An efficient method for analyzing conformational properties of a polymer in solvent

We propose an efficient method for investigating conformational properties of a polymer in solvent. The method is a combination of a Monte Carlo (MC) simulation applied to the polymer alone and a statistical-thermodynamic approach for incorporating solvent effects. To illustrate it, we analyze conformations of a simple polymer chain stabilized in a hard-sphere solvent. The generation of polymer conformations is performed using the self-avoiding random walk on a cubic lattice. We argue that by introducing the generalized-ensemble techniques to the MC simulation part, the method can be applied to studies on protein conformations in aqueous solution under any thermodynamic condition.