Conformational sampling of hydrocarbon and lipid chains in an orienting potential

A Distribution Biased Monte Carlo (DBMC) sampling procedure is developed for the efficient generation of chain conformations in the oriented environment of lipid membranes and other liquid crystalline systems. Conformations of the sn‐1 chain of dipalmitoyl phosphatidylcholine (DPPC) were generated by independently sampling torsion angles from continuous distributions in an orienting potential based on a Marcelja mean field; depending on the chain position, the convergence in the deuterium order parameters (SCD) was 100 to 3000 times more efficient with DBMC than with Brownian dynamics. Optimization using joint distribution and torsional potentials of mean force yielded a further threefold increase in sampling efficiency. Overall chain tilt was included using Euler angle rotations and a separate field strength for the anchor. A segmental DBMC procedure was used to generate a set of complete DPPC conformations with well‐converged conformationally averaged SCD consistent with experimental values. These conformations show considerable flexibility, not only in the hydrocarbon tails, but additionally in both the glycerol and head‐group portions of the lipid. An appendix compares DBMC with a number of other Monte Carlo and stochastic dynamics algorithms using the example of a bistable oscillator, and illustrates the tuning of parameters for optimal convergence. © 1994 by John Wiley & Sons, Inc. This article is a US Government work and, as such, is in the public domain in the United States of America.