| Literature DB >> 26631674 |
Kenneth W Borrelli1, Andreas Vitalis1, Raul Alcantara1, Victor Guallar1.
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.Entities:
Year: 2005 PMID: 26631674 DOI: 10.1021/ct0501811
Source DB: PubMed Journal: J Chem Theory Comput ISSN: 1549-9618 Impact factor: 6.006