Statistical Mechanics and Monte Carlo Studies of Lipid Membranes

Abstract

Over the past 25 years or so experimental studies of lipid bilayer membranes have progressed to the point at which a wealth of data are available from a large variety of experimental measurements. In particular, NMR experiments (Bloom et al, 1991; Brown et al, 1983; Seelig, 1977), X-ray experiments (Mcintosh 1990; Tristram-Nagle et al, 1993), and infrared spectroscopic experiments (Mendelsohn and Senak, 1993) yield data that are related directly to structures and interactions at the molecular level. To aid in the interpretation of this data, and to gain a more complete understanding of lipid bilayers at the molecular level, the next step is to construct theoretical models. To be of use, a theoretical model must be consistent with the data and must contain all of the important atomic level properties as determined from experiment. Ideally, the model will have predictive capabilities. That is, the input to the model will be entirely based upon atomic level properties of the constituent molecules which are independently determined. Then, observable properties of the model will be calculated by the methods of statistical mechanics or from direct computer simulation. Lastly, calculated properties (predictions) of the model will be compared with experimental measurements. Unfortunately, this process is not often so simple in practice. Theoretical models with molecular or atomic level detail are generally too complex to be solved analytically.