Abstract
In Structural Genomics projects, virtual high-throughput ligand screening can be utilized to provide important functional details for newly determined protein structures. Using a variety of publicly available software tools, it is possible to computationally model, predict, and evaluate how different ligands interact with a given protein. At the Center for Structural Genomics of Infectious Diseases (CSGID) a series of protein analysis, docking and molecular dynamics software is scripted into a single hierarchical pipeline allowing for an exhaustive investigation of protein–ligand interactions. The ability to conduct accurate computational predictions of protein–ligand binding is a vital component in improving both the efficiency and economics of drug discovery. Computational simulations can minimize experimental efforts, the slowest and most cost prohibitive aspect of identifying new therapeutics.
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
Similar content being viewed by others
References
Lang PT, Brozell SR, Mukherjee S, Pettersen EF, Meng EC, Thomas V, Rizzo RC, Case DA, James TL, Kuntz ID (2009) DOCK 6: combining techniques to model RNA-small molecule complexes. RNA 15(6):1219–1230. doi:10.1261/rna.1563609, rna.1563609 [pii]
Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. doi:10.1002/jcc.21256
Macke T, Case DA (1998) Modeling unusual nucleic acid structures. In: Molecular modeling of nucleic acids. American Chemical Society 682:379–393
Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30(10):1545–1614. doi:10.1002/jcc.21287
Binkowski TA, Joachimiak A (2008) Protein functional surfaces: global shape matching and local spatial alignments of ligand binding sites. BMC Struct Biol 8:45. doi:10.1186/1472-6807-8-45
Raicu I, Zhao Y, Dumitrescu C, Foster I, Wilde M (2007) Falkon: a fast and light-weight task execution framework. IEEE/ACM SuperComputing
Zhao Y, Hategan M, Clifford B, Foster I,von Laszewski G, Raicu I, Stef-Praun T, Wilde M (2007) Swift: fast, reliable, loosely coupled parallel computation. IEEE International workshop on scientific workflows, Salt Lake City, Utah, USA
Berman HM, Battistuz T, Bhat TN, Bluhm WF, Bourne PE, Burkhardt K, Feng Z, Gilliland GL, Iype L, Jain S, Fagan P, Marvin J, Padilla D, Ravichandran V, Schneider B, Thanki N, Weissig H, Westbrook JD, Zardecki C (2002) The Protein Data Bank. Acta Crystallogr D Biol Crystallogr 58(Pt 6 No 1):899–907. doi:S0907444902003451 [pii]
Irwin JJ, Sterling T, Mysinger MM, Bolstad ES, Coleman RG (2012) ZINC: a free tool to discover chemistry for biology. J Chem Inf Model 52(7):1757–1768. doi:10.1021/ci3001277
Binkowski TA, Adamian L, Liang J (2003) Inferring functional relationships of proteins from local sequence and spatial surface patterns. J Mol Biol 332(2):505–526
Binkowski TA, Joachimiak A, Liang J (2005) Protein surface analysis for function annotation in high-throughput structural genomics pipeline. Protein Sci 14(12):2972–2981. doi:10.1110/ps.051759005
Shoichet BK (2004) Virtual screening of chemical libraries. Nature 432(7019):862–865. doi:10.1038/nature03197, nature03197 [pii]
Shoichet BK, Leach AR, Kuntz ID (1999) Ligand solvation in molecular docking. Proteins 34(1):4–16. doi:10.1002/(SICI)1097-0134(19990101)34:1<4::AID-PROT2>3.0.CO;2-6
Carlson HA, Masukawa KM, Rubins K, Bushman FD, Jorgensen WL, Lins RD, Briggs JM, McCammon JA (2000) Developing a dynamic pharmacophore model for HIV-1 integrase. J Med Chem 43(11):2100–2114, jm990322h [pii]
Schneider G, Bohm HJ (2002) Virtual screening and fast automated docking methods. Drug Discov Today 7(1):64–70, S1359644601020918 [pii]
Price DJ, Jorgensen WL (2000) Computational binding studies of human pp 60c-src SH2 domain with a series of nonpeptide, phosphophenyl-containing ligands. Bioorg Med Chem Lett 10(18):2067–2070, S0960-894X(00)00401-7 [pii]
Wesolowski SS, Jorgensen WL (2002) Estimation of binding affinities for celecoxib analogues with COX-2 via Monte Carlo-extended linear response. Bioorg Med Chem Lett 12(3):267–270, S0960894X01008253 [pii]
Graves AP, Shivakumar DM, Boyce SE, Jacobson MP, Case DA, Shoichet BK (2008) Rescoring docking hit lists for model cavity sites: predictions and experimental testing. J Mol Biol 377(3):914–934. doi:10.1016/j.jmb.2008.01.049, S0022-2836(08)00096-X [pii]
Deng Y, Roux B (2008) Computation of binding free energy with molecular dynamics and grand canonical Monte Carlo simulations. J Chem Phys 128(11):115103. doi:10.1063/1.2842080
Irwin JJ, Shoichet BK (2005) ZINC-a free database of commercially available compounds for virtual screening. J Chem Inf Model 45(1):177–182. doi:10.1021/ci049714+
Zhao Y, Wilde M, Foster I (eds) (2007) Virtual Data Language: a typed workflow notation for diversely structured scientific data. Workflows for eScience. Springer London
Raicu I, Zhang Z, Wilde M, Foster I, Beckman P, Iskra K, Clifford B (2008) Towards loosely coupled programming on a petascale system. IEEE/ACM SuperComputing
Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26:1781–1802
Binkowski TA, Naghibzadeh S, Liang J (2003) CASTp: computed atlas of surface topography of proteins. Nucleic Acids Res 31(13):3352–3355
Liang J, Edelsbrunner H, Fu P, Sudhakar PV, Subramaniam S (1998) Analytical shape computation of macromolecules: I. Molecular area and volume through alpha shape. Proteins 33(1):1–17
Liang J, Edelsbrunner H, Fu P, Sudhakar PV, Subramaniam S (1998) Analytical shape computation of macromolecules: II. Inaccessible cavities in proteins. Proteins 33(1):18–29
Liang J, Edelsbrunner H, Woodward C (1998) Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Sci 7(9):1884–1897
Kollman PA (1993) Free energy calculations: applications to chemical and biochemical phenomena. Chem Rev 93:2395–2417
Deng Y, Roux B (2006) Calculation of standard binding free energies: aromatic molecules in the T4 lysozyme L99A mutant. J Chem Theory Comput 2(5):1255–1273. doi:10.1021/ct060037v
Roux B, Nina M, Pomes R, Smith JC (1996) Thermodynamic stability of water molecules in the bacteriorhodopsin proton channel: a molecular dynamics free energy perturbation study. Biophys J 71(2):670–681. doi:10.1016/S0006-3495(96)79267-6, S0006-3495(96)79267-6 [pii]
Wang J, Deng Y, Roux B (2006) Absolute binding free energy calculations using molecular dynamics simulations with restraining potentials. Biophys J 91(8):2798–2814. doi:10.1529/biophysj.106.084301, S0006-3495(06)71994-4 [pii]
Boresch S, Tettinger F, Leitgeb M, Karplus M (2003) Absolute binding free energies: a quantitative approach for their calculation. J Phys Chem 107:9535–9551
Woo HJ, Dinner AR, Roux B (2004) Grand canonical Monte Carlo simulations of water in protein environments. J Chem Phys 121(13):6392–6400
Woo HJ, Roux B (2005) Calculation of absolute protein-ligand binding free energy from computer simulations. Proc Natl Acad Sci U S A 102(19):6825–6830
Hermans J, Wang L (1997) Inclusion of loss of translational and rotational freedom in theoretical estimates of free energies of binding. application to a complex of benzene and mutant t4 lysozyme. J Am Chem Soc 119:2707–2714
Gilson MK, Given JA, Bush BL, McCammon JA (1997) The statistical-thermodynamic basis for computation of binding affinities: a critical review. Biophys J 72:1047–1069
Simonson T, Archontis G, Karplus M (2002) Free energy simulations come of age: proteinligand recognition. Acc Chem Res 35:430–437
Beglov D, Roux B (1994) Finite representation of an infinite bulk system: solvent boundary potential for computer simulations. J Chem Phys 100:9050–9063
Berkowitz M, McCammon JA (1982) Molecular dynamics with stochastic boundary conditions. Chem Phys Lett 90:215–217
Im W, Bernèche S, Roux B (2001) Generalized solvent boundary potential for computer simulations. J Chem Phys 114(7):2924–2937
Warshel A, King G (1985) Polarization constraints in molecular dynamics simulation of aqueous solutions: the surface constraint all atom solvent (scaas) model. Chem Phys Lett 121:127–129
Jiang W, Hodoscek M, Roux B (2009) Computation of absolute hydration and binding free energy with free energy perturbation distributed replica-exchange molecular dynamics. J Chem Theory Comput 5:2583–2588
Acknowledgments
This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the US Department of Energy under contract DE-AC02-06CH11357. We would like to acknowledge Drs. Devleena Shivakumar, Mike Wilde, Zhao Zhang for valuable discussions and support on computational method development and implementation. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (“Argonne”). Argonne, a US Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The US Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. This work was in part supported with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contracts No. HHSN272200700058C and HHSN272201200026C and by the National Institute of Heath Grant GM094585.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this protocol
Cite this protocol
Binkowski, T.A., Jiang, W., Roux, B., Anderson, W.F., Joachimiak, A. (2014). Virtual High-Throughput Ligand Screening. In: Anderson, W.F. (eds) Structural Genomics and Drug Discovery. Methods in Molecular Biology, vol 1140. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-0354-2_19
Download citation
DOI: https://doi.org/10.1007/978-1-4939-0354-2_19
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-4939-0353-5
Online ISBN: 978-1-4939-0354-2
eBook Packages: Springer Protocols