This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Accurate modeling of the electronic excitation transfer (EET) process is critical to the use of fluorescence-detected resonance energy transfer (FRET) as a structural biology tool. FRET is widely used to study protein-protein and protein-nucleic acid interactions in vitro and in vivo, as well as protein and nucleic acid structures. These studies rely on a number of approximations related to structural dynamics as well as the interactions between the two fluorophores involved in FRET. We propose to examine several of these approximations using molecular dynamics (MD) simulations in close connection with time-resolved fluorescence experiments, which are also performed in my laboratory. In particular, we have already completed initial simulations on a common soluble protein, hen egg-white lysozyme (HEWL) with a donor fluorophore (D) attached by conventional chemisty and an acceptor fluorophore (A) bound into a natural binding pocket. These simulations suggest that two approximations normally made in analysis of FRET data are in error in this system: 1) The = 2/3 approximation, which says that the relative orientations of the D and A are completely uncorrelated, and 2) The = < 1 / R^6 > approximation, which says that the relative orientation (given by kappa) is uncorrelated with the distance between D and A (given by R). We have completed 10 ns of room temperature MD simulation, which show that = 0.623 -- quite close to the ideal 2/3. However, the average energy transfer rate determined using the = 2/3 assumption is 1.6 times larger than that calculated from the simulation. This large difference is due to the failure of the second approximation. For instance, in our simulations making the assumption that kappa and R are uncorrelated (i.e. using < 1 / R^6 >) gives an energy transfer rate that is 1.5 times larger than taking the proper dynamical average ( < kappa^2 / R^6 >). In this system, orientation and distance appear to be strongly correlated. However, with MD simulations of proteins, one must always be concerned with the completeness of sampling, particularly when comparing to experiments that measure structural data averaged over long timescales (i.e. ms). Thus, we propose to extend the current MD simulations using replica exchange molecular dynamics (REMD), which is new to my group. The size of this protein dictates that a large number of replicas (> 20) will be required and that each replica will require several processors (4-8). Thus, we anticipate using 80-160 processors at a time, making strong use of the parallel computing environment of the various teragrid computers.
Showing the most recent 10 out of 292 publications
