%0 Journal Article %1 Borrelli2005PELE %A Borrelli, Kenneth W. %A Vitalis, Andreas %A Alcantara, Raul %A Guallar, Victor %D 2005 %J Journal of Chemical Theory and Computation %K free-energy-profile ligand-unbinding metropolis-monte-carlo rare-events %N 6 %P 1304-1311 %R 10.1021/ct0501811 %T PELE:  Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique %U http://dx.doi.org/10.1021/ct0501811 %V 1 %X Combining protein structure prediction algorithms and Metropolis Monte Carlo techniques, we provide a novel method to explore all-atom energy landscapes. The core of the technique is based on a steered localized perturbation followed by side-chain sampling as well as minimization cycles. The algorithm and its application to ligand diffusion are presented here. Ligand exit pathways are successfully modeled for different systems containing ligands of various sizes:  carbon monoxide in myoglobin, camphor in cytochrome P450cam, and palmitic acid in the intestinal fatty-acid-binding protein. These initial applications reveal the potential of this new technique in mapping millisecond-time-scale processes. The computational cost associated with the exploration is significantly less than that of conventional MD simulations.

@article{Borrelli2005PELE, abstract = { Combining protein structure prediction algorithms and Metropolis Monte Carlo techniques, we provide a novel method to explore all-atom energy landscapes. The core of the technique is based on a steered localized perturbation followed by side-chain sampling as well as minimization cycles. The algorithm and its application to ligand diffusion are presented here. Ligand exit pathways are successfully modeled for different systems containing ligands of various sizes:  carbon monoxide in myoglobin, camphor in cytochrome P450cam, and palmitic acid in the intestinal fatty-acid-binding protein. These initial applications reveal the potential of this new technique in mapping millisecond-time-scale processes. The computational cost associated with the exploration is significantly less than that of conventional MD simulations. }, added-at = {2017-03-03T03:58:40.000+0100}, author = {Borrelli, Kenneth W. and Vitalis, Andreas and Alcantara, Raul and Guallar, Victor}, biburl = {https://www.bibsonomy.org/bibtex/258e8c358567f1dc968e5f2c27dc4eefe/salotz}, description = {PELE:  Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique - Journal of Chemical Theory and Computation (ACS Publications)}, doi = {10.1021/ct0501811}, eprint = {http://dx.doi.org/10.1021/ct0501811}, interhash = {97f4e91b8e9531afa5b03aa8b2a4bd40}, intrahash = {58e8c358567f1dc968e5f2c27dc4eefe}, journal = {Journal of Chemical Theory and Computation}, keywords = {free-energy-profile ligand-unbinding metropolis-monte-carlo rare-events}, note = {PMID: 26631674}, number = 6, pages = {1304-1311}, timestamp = {2017-03-03T03:58:40.000+0100}, title = {PELE:  Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique}, url = {http://dx.doi.org/10.1021/ct0501811}, volume = 1, year = 2005 }