Abstract
Receptors are inherently dynamic and this flexibility is important to consider when constructing a model of molecular association. Conformations from molecular dynamics simulations, a well-established method for examining protein dynamics, can be used in virtual screening to account for flexibility in structure-based drug discovery. Different receptor configurations influence docking results. Molecular dynamics simulations can provide snapshots that improve virtual screening predictive power over known crystal structures, most likely as a result of sampling more relevant receptor conformations. Here we highlight some details and nuances of using such snapshots and evaluating them for predictive performance.
Correspondence should be addressed to: senichols@ucsd.edu OR r.baron@utah.edu
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wu, B., Chien, E., Mol, C., Fenalti, G., Liu, W., Katritch, V., Abagyan, R., Brooun, A., Wells, P., Bi, F., Hamel, D., Kuhn, P., Handel, T., Cherezov, V., and Stevens, R. (2010) Structures of the CXCR4 Chemokine GPCR with Small-Molecule and Cyclic Peptide Antagonists, Science 330, 1066–1071.
Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., and Bourne, P. E. (2000) The Protein Data Bank, Nucleic Acids Res 28, 235–242.
Sherman, W., Day, T., Jacobson, M. P., Friesner, R. A., and Farid, R. (2006) Novel procedure for modeling ligand/receptor induced fit effects., J Med Chem 49, 534–553.
Meiler, J., and Baker, D. (2006) ROSETTALIGAND: Protein-small molecule docking with full side-chain flexibility, Proteins 65, 538–548.
Morris, G., Huey, R., Lindstrom, W., Sanner, M., Belew, R., Goodsell, D., and Olson, A. (2009) AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility, J Comput Chem 30, 2785–2791.
Amaro, R. E., Baron, R., and McCammon, J. A. (2008) An improved relaxed complex scheme for receptor flexibility in computer-aided drug design, J Comput Aided Mol Des 22, 693–705.
Rueda, M., Bottegoni, G., and Abagyan, R. (2010) Recipes for the selection of experimental protein conformations for virtual screening, J Chem Info Model 50, 186–193.
Fawcett, T. (2006) An introduction to ROC analysis, Pattern Recogn Lett 27, 861–874.
Nichols, S. E., Baron, R., and McCammon, J. A. (2011) Predictive Power of Molecular Dynamics Receptor Structures in Virtual Screening, J Chem Info Model 51, 1439–1446.
Ivetac, A., and McCammon, J. A. (2009) Elucidating the inhibition mechanism of HIV-1 non-nucleoside reverse transcriptase inhibitors through multicopy molecular dynamics simulations, J Mol Biol 388, 644–658.
De Clercq, E. (2004) Non-nucleoside reverse transcriptase inhibitors (NNRTIs): past, present, and future, Chem Biodiversity 1, 44–64.
McGovern, S. L., and Shoichet, B. K. (2003) Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes, J Med Chem 46, 2895–2907.
Lin, J. H., Perryman, A. L., Schames, J. R., and McCammon, J. A. (2003) The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme, Biopolymers 68, 47–62.
Baron, R., and McCammon, J. A. (2007) Dynamics, hydration, and motional averaging of a loop-gated artificial protein cavity: the W191G mutant of cytochrome c peroxidase in water as revealed by molecular dynamics simulations, Biochemistry 46, 10629–10642.
Nichols, S., Domaoal, R., Thakur, V., Tirado-Rives, J., Anderson, K., and Jorgensen, W. (2009) Discovery of wild-type and Y181C mutant non-nucleoside HIV-1 reverse transcriptase inhibitors using virtual screening with multiple protein structures., J Chem Info Model 49, 1272–1279.
Acknowledgments
The authors would like to thank the members of the McCammon research group for useful discussions. This work was supported in part by the National Science Foundation, the National Institutes of Health, Howard Hughes Medical Institute, the San Diego Supercomputer Center, the Center for Theoretical Biological Physics and the National Biomedical Computational Resource.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Nichols, S.E., Baron, R., McCammon, J.A. (2012). On the Use of Molecular Dynamics Receptor Conformations for Virtual Screening. In: Baron, R. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 819. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-465-0_7
Download citation
DOI: https://doi.org/10.1007/978-1-61779-465-0_7
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-61779-464-3
Online ISBN: 978-1-61779-465-0
eBook Packages: Springer Protocols