Publications
2012 |
Lee, Sunghak Statistical Risk Estimation for Communication System Design PhD Thesis 2012, ISSN: 1098-6596. Abstract | Links | BibTeX | Tags: Axial crushing, Energy absorption, icle, Impact absorption energy, Origami pattern, Space frame, Thin-walled tubes, Triggering dent @phdthesis{leeStatisticalRiskEstimation2012, title = {Statistical Risk Estimation for Communication System Design}, author = {Sunghak Lee}, doi = {10.1017/CBO9781107415324.004}, issn = {1098-6596}, year = {2012}, date = {2012-01-01}, volume = {53}, number = {9}, abstract = {Predicting the binding mode of flexible polypeptides to proteins is an important task that falls outside the domain of applicability of most small molecule and protein-protein docking tools. Here, we test the small molecule flexible ligand docking program Glide on a set of 19 non-$alpha$-helical peptides and systematically improve pose prediction accuracy by enhancing Glide sampling for flexible polypeptides. In addition, scoring of the poses was improved by post-processing with physics-based implicit solvent MM- GBSA calculations. Using the best RMSD among the top 10 scoring poses as a metric, the success rate (RMSD $łeq$ 2.0 AA for the interface backbone atoms) increased from 21% with default Glide SP settings to 58% with the enhanced peptide sampling and scoring protocol in the case of redocking to the native protein structure. This approaches the accuracy of the recently developed Rosetta FlexPepDock method (63% success for these 19 peptides) while being over 100 times faster. Cross-docking was performed for a subset of cases where an unbound receptor structure was available, and in that case, 40% of peptides were docked successfully. We analyze the results and find that the optimized polypeptide protocol is most accurate for extended peptides of limited size and number of formal charges, defining a domain of applicability for this approach.}, keywords = {Axial crushing, Energy absorption, icle, Impact absorption energy, Origami pattern, Space frame, Thin-walled tubes, Triggering dent}, pubstate = {published}, tppubtype = {phdthesis} } Predicting the binding mode of flexible polypeptides to proteins is an important task that falls outside the domain of applicability of most small molecule and protein-protein docking tools. Here, we test the small molecule flexible ligand docking program Glide on a set of 19 non-$alpha$-helical peptides and systematically improve pose prediction accuracy by enhancing Glide sampling for flexible polypeptides. In addition, scoring of the poses was improved by post-processing with physics-based implicit solvent MM- GBSA calculations. Using the best RMSD among the top 10 scoring poses as a metric, the success rate (RMSD $łeq$ 2.0 AA for the interface backbone atoms) increased from 21% with default Glide SP settings to 58% with the enhanced peptide sampling and scoring protocol in the case of redocking to the native protein structure. This approaches the accuracy of the recently developed Rosetta FlexPepDock method (63% success for these 19 peptides) while being over 100 times faster. Cross-docking was performed for a subset of cases where an unbound receptor structure was available, and in that case, 40% of peptides were docked successfully. We analyze the results and find that the optimized polypeptide protocol is most accurate for extended peptides of limited size and number of formal charges, defining a domain of applicability for this approach. |