We provide a critical examination of two different methods for generating a donor-acceptor electronic coupling trajectory from a molecular dynamics (MD) trajectory and three methods for sampling that coupling trajectory, allowing the modeling of experimental observables directly from the MD simulation. In the first coupling method we perform a single quantum-mechanical (QM) calculation to characterize the excited state behavior, specifically the transition dipole moment, of the fluorescent probe, which is then mapped onto the configuration space sampled by MD. We then utilize these transition dipoles within the ideal dipole approximation (IDA) to determine the electronic coupling between the probes that mediates the transfer of energy. In the second method we perform a QM calculation on each snapshot and use the complete transition densities to calculate the electronic coupling without need for the IDA. The resulting coupling trajectories are then sampled using three methods ranging from an independent sampling of each trajectory point (the Independent Snapshot Method) to a Markov chain treatment that accounts for the dynamics of the coupling in determining effective rates. The results show that the IDA significantly overestimates the energy transfer rate (by a factor of 2.6) during the portions of the trajectory in which the probes are close to each other. Comparison of the sampling methods shows that the Markov chain approach yields more realistic observables at both high and low FRET efficiencies. Differences between the three sampling methods are discussed in terms of the different mechanisms for averaging over structural dynamics in the system. Convergence of the Markov chain method is carefully examined. Together, the methods for estimating coupling and for sampling the coupling provide a mechanism for directly connecting the structural dynamics modeled by MD with fluorescence observables determined through FRET experiments.

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Scien, 23,13-47, 2004). Usually the rate of this process is predicted using QSAR or other knowledge-based predictors (R Gozalbes, et al., Bioorganic & Med Chem,19, 2615-2624, 2011. However, this approach is not always accurate. Moreover, it does not provide the atomistic details of the process, and thus its prediction cannot be directly exploited to rationally design drugs with higher permeation rate. We developed a protocol for studying the permeation of small organic molecules (e.g. drugs) through lipid membranes by atomistic simulations. This protocol allows computing accurately the permeability coefficient, and provides a detailed atomistic picture of the process. The approach is based on an enhanced sampling technique, bias exchange metadynamics (S. Piana and A. Laio, J Phys Chem B, 111, 4553-4559, 2007), that allows deriving from atomistic simulations a multidimensional free energy landscape and an accurate kinetic model describing the transitions between the relevant metastable states of the system (F Marinelli, et al., Plos Comp Biol, 5, e1000452, 2009). As a benchmark, we applied this protocol on the permeation of ethanol through palmitoyloleoylphosphatidylcholine (POPC) membrane. We are applying the same procedure to study the permeation of two anti-HIV drugs where unbiased simulation of the permeation process is not possible.