%0 Journal Article %1 Huang2011UnbindingFreeEnergyLandscape %A Huang, Danzhi %A Caflisch, Amedeo %D 2011 %J PLoS Computational Biology %K Hammond-behavior free-energy free-energy-landscape ligand-binding ligand-dissociation networks transition-state-networks %P 1-12 %T The Free Energy Landscape of Small Molecule Unbinding %U http://dx.doi.org/10.1371%2Fjournal.pcbi.1002002 %V 7 %X Most known drugs used to fight human diseases are small molecules that bind strongly to proteins, particularly to enzymes or receptors involved in essential biochemical or physiological processes. The binding process is very complex because of the many degrees of freedom and multiple interactions between pairs of atoms. Here we show that network analysis, a mathematical tool used to study a plethora of complex systems ranging from social interactions (e.g, friendship links in Facebook) to metabolic networks, provides a detailed description of the free energy landscape and pathways involved in the binding of small molecules to an enzyme. Using molecular dynamics simulations to sample the free energy landscape, we provide strong evidence at atomistic detail that small ligands can have multiple favorable positions and orientations in the active site. We also observe a broad heterogeneity of (un)binding pathways. Experimental approaches to the study of fragment binding to proteins have limitations in spatial and temporal resolution. Our network analysis of the molecular dynamics simulations does not suffer from these limitations. It provides a thorough description of the thermodynamics and kinetics of the binding process.

@article{Huang2011UnbindingFreeEnergyLandscape, abstract = {Most known drugs used to fight human diseases are small molecules that bind strongly to proteins, particularly to enzymes or receptors involved in essential biochemical or physiological processes. The binding process is very complex because of the many degrees of freedom and multiple interactions between pairs of atoms. Here we show that network analysis, a mathematical tool used to study a plethora of complex systems ranging from social interactions (e.g, friendship links in Facebook) to metabolic networks, provides a detailed description of the free energy landscape and pathways involved in the binding of small molecules to an enzyme. Using molecular dynamics simulations to sample the free energy landscape, we provide strong evidence at atomistic detail that small ligands can have multiple favorable positions and orientations in the active site. We also observe a broad heterogeneity of (un)binding pathways. Experimental approaches to the study of fragment binding to proteins have limitations in spatial and temporal resolution. Our network analysis of the molecular dynamics simulations does not suffer from these limitations. It provides a thorough description of the thermodynamics and kinetics of the binding process.}, added-at = {2016-03-08T00:27:49.000+0100}, author = {Huang, Danzhi and Caflisch, Amedeo}, biburl = {https://www.bibsonomy.org/bibtex/26cf25813d85cf44d52704019a3f5e696/salotz}, description = {PLOS Computational Biology: The Free Energy Landscape of Small Molecule Unbinding}, interhash = {0006f4eaa2f922287b76a9f29de66bf4}, intrahash = {6cf25813d85cf44d52704019a3f5e696}, journal = {PLoS Computational Biology}, keywords = {Hammond-behavior free-energy free-energy-landscape ligand-binding ligand-dissociation networks transition-state-networks}, month = {February}, pages = {1-12}, timestamp = {2017-12-21T22:14:25.000+0100}, title = {The Free Energy Landscape of Small Molecule Unbinding}, url = {http://dx.doi.org/10.1371%2Fjournal.pcbi.1002002}, volume = 7, year = 2011 }