Abstract
Five docking tools, namely AutoDock, FRED, CDOCKER, FlexX and GOLD, have been critically examined, with the aim of selecting those most appropriate for use as docking tools for docking molecules to the lectin dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN). This lectin has been selected for its rather non-druggable binding site, which enables complex interactions that guide the binding of the core monosaccharide. Since optimal orientation is crucial for forming coordination bonds, it was important to assess whether the selected docking tools could reproduce the optimal binding conformation for several oligosaccharides that are known to bind DC-SIGN. Our results show that even widely used docking programs have certain limitations when faced with a rather shallow and featureless binding site, as is the case of DC-SIGN. The FRED docking software (OpenEye Scientific Software, Inc.) was found to score as the best tool for docking ligands to DC-SIGN. The performance of FRED was further assessed on another lectin, Langerin. We have demonstrated that this validated docking protocol could be used for docking to other lectins similar to DC-SIGN.
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References
Brooijmans N, Kuntz ID (2003) Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct 32:335–373. doi:10.1146/annurev.biophys.32.110601.142532
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242. doi:10.1093/nar/28.1.235
Bernstein FC, Koetzle TF, Williams GJ, Meyer EF Jr, Brice MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M (1978) The protein data bank: a computer-based archival file for macromolecular structures. Arch Biochem Biophys 185(2):584–591. doi:10.1016/0003-9861(78)90204-7
Kuntz ID, Blaney JM, Oatley SJ, Langridge R, Ferrin TE (1982) A geometric approach to macromolecule-ligand interactions. J Mol Biol 161(2):269–288. doi:10.1016/0022-2836(82)90153-X
Bharatham N, Bharatham K, Shelat AA, Bashford D (2014) Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study. J Chem Inf Model 54(2):648–659. doi:10.1021/ci4004656
Kroemer RT (2007) Structure-based drug design: docking and scoring. Curr Protein Pept Sci 8(4):312–328. doi:10.2174/138920307781369382
Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3(11):935–949. doi:10.1038/nrd1549
Tomašić T, Hajšek D, Švajger U, Luzar J, Obermajer N, Petit-Haertlein I, Fieschi F, Anderluh M (2014) Monovalent mannose-based DC-SIGN antagonists: targeting the hydrophobic groove of the receptor. Eur J Med Chem 75:308–326. doi:10.1016/j.ejmech.2014.01.047
Obermajer N, Sattin S, Colombo C, Bruno M, Švajger U, Anderluh M, Bernardi A (2011) Design, synthesis and activity evaluation of mannose-based DC-SIGN antagonists. Mol Divers 15(2):347–360. doi:10.1007/s11030-010-9285-y
Anderluh M, Jug G, Švajger U, Obermajer N (2012) DC-SIGN antagonists, a potential new class of anti-infectives. Curr Med Chem 19(7):992–1007. doi:10.2174/092986712799320664
Feinberg H, Mitchell DA, Drickamer K, Weis WI (2001) Structural basis for selective recognition of oligosaccharides by DC-SIGN and DC-SIGNR. Science 294(5549):2163–2166. doi:10.1126/science.1066371
LeadIT version 2.1.3 is available from BioSolveIT (GmbH), http://www.biosolveit.de/
Accelrys Discovery Studio 3.0 is available from Accelrys Inc, San Diego http://accelrys.com/
McGaughey GB, Sheridan RP, Bayly CI, Culberson JC, Kreatsoulas C, Lindsley S, Maiorov V, Truchon JF, Cornell WD (2007) Comparison of topological, shape, and docking methods in virtual screening. J Chem Inf Model 47(4):1504–1519. doi:10.1021/ci700052x
McGann M (2011) FRED pose prediction and virtual screening accuracy. J Chem Inf Model 51(3):578–596. doi:10.1021/ci100436p
McGann MR, Almond HR, Nicholls A, Grant JA, Brown FK (2003) Gaussian docking functions. Biopolymers 68(1):76–90. doi:10.1002/bip.10207
Morris GM, Goodsell DS, Huey R, Olson AJ (1996) Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4. J Comput Aid Mol Des 10(4):293–304. doi:10.1007/BF00124499
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
Goodsell DS, Olson AJ (1990) Automated docking of substrates to proteins by simulated annealing. Proteins 8(3):195–202. doi:10.1002/prot.340080302
Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 19(14):1639–1662. doi:10.1002/(SICI)1096-987X(19981115)19:14<1639::AIDJCC10>3.0.CO;2B
GOLD version 5.2 is available from The Cambridge Crystallographic Data Centre, Cambridge, www.ccdc.cam.ac.uk/
Wu G, Robertson DH, Brooks CL 3rd, Vieth M (2003) Detailed analysis of grid-based molecular docking: a case study of CDOCKER-A CHARMm-based MD docking algorithm. J Comput Chem 24(13):1549–1562. doi:10.1002/jcc.10306
Bursulaya BD, Totrov M, Abagyan R, Brooks CL 3rd (2003) Comparative study of several algorithms for flexible ligand docking. J Comput Aid Mol Des 17(11):755–763. doi:10.1023/B:JCAM.0000017496.76572.6f
Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261(3):470–489. doi:10.1006/jmbi.1996.0477
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:10.1107/S0907444902003451
Feinberg H, Castelli R, Drickamer K, Seeberger PH, Weis WI (2007) Multiple modes of binding enhance the affinity of DC-SIGN for high mannose N-linked glycans found on viral glycoproteins. J Biol Chem 282(6):4202–4209. doi:10.1074/jbc.M609689200
Thepaut M, Guzzi C, Sutkeviciute I, Sattin S, Ribeiro-Viana R, Varga N, Chabrol E, Rojo J, Bernardi A, Angulo J, Nieto PM, Fieschi F (2013) Structure of a glycomimetic ligand in the carbohydrate recognition domain of C-type lectin DC-SIGN. Structural requirements for selectivity and ligand design. J Am Chem Soc 135(7):2518–2529. doi:10.1021/ja3053305
Sutkeviciute I, Thepaut M, Sattin S, Berzi A, McGeagh J, Grudinin S, Weiser J, Le Roy A, Reina JJ, Rojo J, Clerici M, Bernardi A, Ebel C, Fieschi F (2014) Unique DC-SIGN clustering activity of a small glycomimetic: a lesson for ligand design. ACS Chem Biol 9(6):1377–1385. doi:10.1021/cb500054h
Feinberg H, Taylor ME, Razi N, McBride R, Knirel YA, Graham SA, Drickamer K, Weis WI (2011) Structural basis for langerin recognition of diverse pathogen and mammalian glycans through a single binding site. J Mol Biol 405(4):1027–1039. doi:10.1016/j.jmb.2010.11.039
Caboche S (2013) LeView: automatic and interactive generation of 2D diagrams for biomacromolecule/ligand interactions. J Cheminf 5(1):40. doi:10.1186/1758-2946-5-40
Halgren TA (1996) Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem 17(5–6):490–519. doi:10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P
GAMESS interface, ChemBio3D Ultra 13.0, CambridgeSoft
Wilantho A, Tongsima S, Jenwitheesuk E (2008) Pre-docking filter for protein and ligand 3D structures. Bioinformation 3(5):189–193. doi:10.6026/97320630003189
Schneider N, Lange G, Hindle S, Klein R, Rarey M (2013) A consistent description of hydrogen bond and dehydration energies in protein-ligand complexes: methods behind the HYDE scoring function. J Comput Aided Mol Des 27(1):15–29. doi:10.1007/s10822-012-9626-2
OMEGA 2.4.3: OpenEye Scientific Software, Santa Fe, NM. http://www.eyesopen.com/. Hawkins PCD, Skillman AG, Warren GL, Ellingson BA, Stahl MT (2010) Conformer generation with OMEGA: Algorithm and validation using high quality structures from the Protein Data Bank and Cambridge Structural Database. J Chem Inf Model 50:572–584. doi: 10.1021/ci100031x
OEDocking 3.0.1: OpenEye Scientific Software, Santa Fe, NM. http://www.eyesopen.com/
MAKE Receptor 3.0.1: OpenEye Scientific Software, Santa Fe, NM. http://www.eyesopen.com/
Mooij WTM, Verdonk ML (2005) General and targeted statistical potentials for protein—ligand interactions. Proteins 61(2):272–287. doi:10.1002/prot.20588
Korb O, Stützle T, Exner TE (2009) Empirical scoring functions for advanced protein—ligand docking with plants. J Chem Inf Model 49(1):84–96. doi:10.1021/ci800298z
Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267(3):727–748. doi:10.1006/jmbi.1996.0897
Eldridge M, Murray C, Auton T, Paolini G, Mee R (1997) Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J Comput Aid Mol Des 11(5):425–445. doi:10.1023/A:1007996124545
Baxter CA, Murray CW, Clark DE, Westhead DR, Eldridge MD (1998) Flexible docking using tabu search and an empirical estimate of binding affinity. Proteins 33(3):367–382. doi:10.1002/(SICI)1097-0134(19981115)33:3<367::AID-PROT6>3.0.CO;2-W
Pymol is available from Delano Scientific LLC, San Francisco, CA, http://pymol.sourceforge.net/
Jain A (2008) Bias, reporting, and sharing: computational evaluations of docking methods. J Comput Aid Mol Des 22(3–4):201–212. doi:10.1007/s10822-007-9151-x
Cross JB, Thompson DC, Rai BK, Baber JC, Fan KY, Hu Y, Humblet C (2009) Comparison of several molecular docking programs: pose prediction and virtual screening accuracy. J Chem Inf Model 49(6):1455–1474. doi:10.1021/ci900056c
Warren GL, Andrews CW, Capelli AM, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S, Tedesco G, Wall ID, Woolven JM, Peishoff CE, Head MS (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49(20):5912–5931. doi:10.1021/jm050362n
Gowthaman R, Deeds EJ, Karanicolas J (2013) Structural properties of non-traditional drug targets present new challenges for virtual screening. J Chem Inf Model 53(8):2073–2081. doi:10.1021/ci4002316
Asensio JL, Arda A, Canada FJ, Jimenez-Barbero J (2013) Carbohydrate-aromatic interactions. Accounts Chem Res 46(4):946–954. doi:10.1021/ar300024d
Seebeck B, Reulecke I, Kämper A, Rarey M (2008) Modelling of metal interaction geometries for protein-ligand docking. Proteins 71(3):1237–1254. doi:10.1002/prot.21818
Hu X, Balaz S, Shelver WH (2004) A practical approach to docking of zinc metalloproteinase inhibitors. J Mol Graph Model 22(4):293–307. doi:10.1016/j.jmgm.2003.11.002
Tomašić T, Rabbani S, Gobec M, Mlinarič Raščan I, Podlipnik Č, Ernst B, Anderluh M (2014) Branched α-D-mannopyranosides: a new class of potent FimH antagonists. Med Chem Commun 5(8):1247–1253. doi:10.1039/C4MD00093E
Mysinger MM, Carchia M, Irwin JJ, Shoichet BK (2012) Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J Med Chem 55(14):6582–6594. doi:10.1021/jm300687e
Holla A, Skerra A (2011) Comparative analysis reveals selective recognition of glycans by the dendritic cell receptors DC-SIGN and Langerin. Protein Eng Des Sel 24(9):659–669. doi:10.1093/protein/gzr016
de Witte L, Nabatov A, Geijtenbeek TB (2008) Distinct roles for DC-SIGN + −dendritic cells and Langerhans cells in HIV-1 transmission. Trends Mol Med 14(1):12–19. doi:10.1016/j.molmed.2007.11.001
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The authors thank OpenEye Scientific Software, Inc. for free academic licenses for their software. The authors thank Professor Roger Pain for proofreading the manuscript.
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This work was supported by the Slovenian Research Agency (Grant No. P1-0208).
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The authors declare that they have no conflict of interest.
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Jug, G., Anderluh, M. & Tomašič, T. Comparative evaluation of several docking tools for docking small molecule ligands to DC-SIGN. J Mol Model 21, 164 (2015). https://doi.org/10.1007/s00894-015-2713-2
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DOI: https://doi.org/10.1007/s00894-015-2713-2