Sampling conformation space to model equilibrium fluctuations in proteins
This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales.
sampling conformations equilibrium fluctuations proteins robotics statistical mechanics inverse kinematics