Enzyme State Classification and Dynamics from smFRET

Modeling smFRET dynamics using 3-state Hidden Markov Models. The left figure illustrates a trajectory of smFRET acceptor (red) and donor (blue) counts. The right figure shows estimated probabilities through timestamps for each of the states with state one in red, state two in green, and state three in blue.

For Enzyme, we employ the enhanced sampling MD to (1) predict FRET distributions for candidate residue pairs to help design efficient smFRET experiments and (2) interpret smFRET data (determine 3D structure of different FRET peaks). In addition, the smFRET experimental data will be used to correct MD data (e.g., using ensemble filtering through importance sampling) for more accurate predictions of unmeasured FRET distributions.

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