MYJOHNSHOPKINS.EDU
Douglas Poland
Theoretical Chemistry
Johns Hopkins University
Remsen 343
3400 North Charles St.
Baltimore, MD 21218
Phone: 410.516.7441
Email: poland@jhu.edu
Ph.D. - Cornell University
Postdoctoral Fellow - Cornell University
My research centers around the application of statistical mechanics to problems in chemistry and biology. When I first came to Hopkins my interests were mainly in the statistical mechanics of helix-coil transitions in proteins and nucleic acids. Over the years I expanded my interests to include studies of phase transitions in lattice models and the thermodynamics of chemical reactions in nonideal, nonequilibrium systems. Lately most of my work has centered around the calculation of distribution functions for chemical and biochemical systems.
For example, if one knows the heat capacity of a system as a function of temperature (say, expressed as a Taylor series in the temperature), then one can show that this experimental data can be turned into a set of moments of the energy distribution. Thus given the heat capacity through the second power in the temperature, this turns out to be enough information to calculate four moments of the energy distribution. Using the maximum-entropy method, one can then use the moments to calculate an approximate energy distribution (the more moments one has, the more accurate the distribution). When one applies this method to the heat capacity of proteins, one finds that many proteins show a bimodal (two peak) energy distribution, indicating that the thermal unwinding of these molecules involves two distinct populations of species (native and unfolded). This same approach can be applied to the binding of ligands to biopolymers. In that case the appropriate titration curve yields binding moments which in turn can be used to calculate the distribution of species bound to the macromolecule. In this manner the complete binding polynomial (for hundreds of binding sites) can be calculated explicitly.
Recently I have studied the distribution of C-G pairs in the DNA of select organisms, in particular, the tendency for C-G pairs to cluster on all scales with respect to the number of bases considered. I previously found that if I counted the number of C-G pairs in consecutive, nonoverlapping boxes containing a total of m bases, then the width of the distribution function describing how many C-G pairs are in a box increases with respect to m dramatically relative to the width expected for a random distribution. The relative width of the C-G composition distribution function is found to vary accurately as a power law with respect to m, the size of the box, over a very wide range of m values. I express the power law in terms of a characteristic exponent. The enhanced relative width of the distribution functions is a direct consequence of the tendency for boxes of similar composition to follow one another. This tendency represents persistence in composition in composition from box to box. The occurrence of a power law means that the tendency for C-G pairs to cluster is present on all scales of sequence length.