@article{fallis_no_2013,
	title = {No {Title} {No} {Title}},
	volume = {53},
	issn = {1098-6596},
	doi = {10.1017/CBO9781107415324.004},
	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-α-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 ≤ 2.0 Å 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.},
	number = {9},
	journal = {Journal of Chemical Information and Modeling},
	author = {Fallis, A.G},
	year = {2013},
	note = {arXiv: 1011.1669v3
ISBN: 9788578110796},
	keywords = {icle},
	pages = {1689--1699},
}

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