Abstract
Computational simulations of essential biological systems in pathogenic organisms are increasingly being used to reveal structural and dynamical features for targets of interest. At the same time, increased research efforts, especially from academia, have been directed toward drug discovery for neglected tropical diseases. Although these diseases cripple large populations in less fortunate parts of the world, either very few new drugs are being developed or the available treatments for them have severe side effects, including death. This chapter walks readers through a computational investigation used to find novel inhibitors to target one of these neglected diseases, African sleeping sickness (human African trypanosomiasis). Such studies may suggest novel small-molecule compounds that could be considered as part of an early-stage drug discovery effort. As an example target protein of interest, we focus on the essential protein RNA-editing ligase 1 (REL1) in Trypanosoma brucei, the causative agent of human African trypanosomiasis.
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References
Carnes J, Stuart K (2008) Working together: the RNA editing machinery in Trypanosoma brucei. In: Göringer HU (ed) RNA editing, vol 20. Nucleic acids and molecular biology (Gross HG, ed). Springer, Berlin/Heidelberg, pp 143–164. doi: 10.1007/978-3-540-73787-2_7
Ochsenreiter T, Hajduk S (2008) The function of RNA editing in trypanosomes. In: Göringer HU (ed), RNA editing, vol 20. Nucleic acids and molecular biology (Gross HG, ed). Springer, Berlin/Heidelberg, pp 181–197. doi: 10.1007/978-3-540-73787-2_9
Golas MM, Bohm C, Sander B et al (2009) Snapshots of the RNA editing machine in trypanosomes captured at different assembly stages in vivo. EMBO J 28:766–778. doi:10.1038/emboj.2009.19
Schnaufer A, Ernst NL, Palazzo SS et al (2003) Separate insertion and deletion subcomplexes of the Trypanosoma brucei RNA editing complex. Mol Cell 12:307–319. doi:S1097276503002867
Schnaufer A, Wu M, Park YJ et al (2010) A protein-protein interaction map of trypanosome 20S editosomes. J Biol Chem 285:5282–5295. doi:M109.059378
Rusché LN, Huang CE, Piller KJ et al (2001) The two RNA ligases of the Trypanosoma brucei RNA editing complex: cloning the essential band IV gene and identifying the band V gene. Mol Cell Biol 21:979–989. doi:10.1128/MCB.21.4.979-989.2001
Schnaufer A, Panigrahi AK, Panicucci B et al (2001) An RNA ligase essential for RNA editing and survival of the bloodstream form of Trypanosoma brucei. Science 291:2159–2162. doi:10.1126/science.1058955
Shuman S, Lima CD (2004) The polynucleotide ligase and RNA capping enzyme superfamily of covalent nucleotidyltransferases. Curr Opin Struct Biol 14:757–764. doi:10.1016/j.sbi.2004.10.006
Deng J, Schnaufer A, Salavati R et al (2004) High resolution crystal structure of a key editosome enzyme from Trypanosoma brucei: RNA editing ligase 1. J Mol Biol 343:601–613. doi:10.1016/j.jmb.2004.08.041
Amaro RE, Swift RV, McCammon JA (2007) Functional and structural insights revealed by molecular dynamics simulations of an essential RNA editing ligase in Trypanosoma brucei. PLoS Negl Trop Dis 1:e68. doi:10.1371/journal.pntd.0000068
Cherepanov AV, de Vries S (2002) Kinetic mechanism of the Mg2+-dependent nucleotidyl transfer catalyzed by T4 DNA and RNA ligases. J Biol Chem 277:1695–1704. doi:10.1074/jbc.M109616200
Håkansson K, Doherty AJ, Shuman S, Wigley DB (1997) X-ray crystallography reveals a large conformational change during guanyl transfer by mRNA capping enzymes. Cell 89:545–553. doi:10.1016/S0092-8674(00)80236-6
Nandakumar J, Shuman S, Lima CD (2006) RNA ligase structures reveal the basis for RNA specificity and conformational changes that drive ligation forward. Cell 127:71–84. doi:10.1016/j.cell.2006.08.038
El Omari K, Ren J, Bird LE et al (2006) Molecular architecture and ligand recognition determinants for T4 RNA ligase. J Biol Chem 281:1573–1579. doi:10.1074/jbc.M509658200
Zhang L, Hermans J (1996) Hydrophilicity of cavities in proteins. Proteins 24:433–438. doi:10.1002/(SICI)1097-0134(199604)24:4<433::AID-PROT3>3.0.CO;2-F
Vriend G (1990) WHAT IF: a molecular modeling and drug design program. J Mol Graph 8(52–56):29
Bas DC, Rogers DM, Jensen JH (2008) Very fast prediction and rationalization of pKa values for protein-ligand complexes. Proteins 73:765–783. doi:10.1002/prot.22102
Li H, Robertson AD, Jensen JH (2005) Very fast empirical prediction and rationalization of protein pKa values. Proteins 61:704–721. doi:10.1002/prot.20660
Olsson MH, Sondergaard CR, Rostkowski M, Jensen JH (2011) PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions. J Chem Theory Comput 7:525–537
Phillips JC, Braun R, Wang W et al (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26:1781–1802. doi:10.1002/jcc.20289
Swift RV, Durrant J, Amaro RE, McCammon JA (2009) Toward understanding the conformational dynamics of RNA ligation. Biochemistry 48:709–719. doi:10.1021/bi8018114
Case DA, Cheatham TE 3rd, Darden T et al (2005) The Amber biomolecular simulation programs. J Comput Chem 26:1668–1688. doi:10.1002/jcc.20290
Hess B, Kutzner C, Van Der Spoel D, Lindahl E (2008) GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4:435–447
Bowers KJ, Chow E, Xu H et al (2006) Scalable algorithms for molecular dynamics simulations on commodity clusters. In: International conference for high performance computing, networking, storage and analysis (SC06), 11–17 Nov 2006, Tampa, FL
Christen M, Hunenberger PH, Bakowies D et al (2005) The GROMOS software for biomolecular simulation: GROMOS05. J Comput Chem 26:1719–1751. doi:10.1002/jcc.20303
MacKerell AD, Bashford D, Bellott M et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616
Hornak V, Abel R, Okur A et al (2006) Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins 65:712–725. doi:10.1002/Prot.21123
Wang JM, Wolf RM, Caldwell JW et al (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174
Meagher KL, Redman LT, Carlson HA (2003) Development of polyphosphate parameters for use with the AMBER force field. J Comput Chem 24:1016–1025. doi:10.1002/Jcc.10262
Oelschlaeger P, Klahn M, Beard WA et al (2007) Magnesium-cationic dummy atom molecules enhance representation of DNA polymerase beta in molecular dynamics simulations: improved accuracy in studies of structural features and mutational effects. J Mol Biol 366:687–701. doi:10.1016/J.Jmb.2006.10.095
Amaro RE, Schnaufer A, Interthal H et al (2008) Discovery of drug-like inhibitors of an essential RNA-editing ligase in Trypanosoma brucei. Proc Natl Acad Sci USA 105:17278–17283. doi:10.1073/pnas.0805820105
Morris GM, Huey R, Lindstrom W et al (2009) AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791. doi:10.1002/jcc.21256
Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461. doi:10.1002/jcc.21334
Lang PT, Brozell SR, Mukherjee S et al (2009) DOCK 6: combining techniques to model RNA-small molecule complexes. RNA 15:1219–1230. doi:rna.1563609
OpenEye Scientific Software I (2010) OEChem, Santa Fe, NM
McGann MR, Almond HR, Nicholls A et al (2003) Gaussian docking functions. Biopolymers 68:76–90. doi:10.1002/Bip.10207
Jones G, Willett P, Glen RC et al (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748. doi:10.1006/jmbi.1996.0897
Halgren TA, Murphy RB, Friesner RA et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 47:1750–1759. doi: 10.1021/jm030644s
Friesner RA, Banks JL, Murphy RB et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749. doi:10.1021/jm0306430
Jain AN (2007) Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. J Comput Aided Mol Des 21:281–306. doi:10.1007/s10822-007-9114-2
Venkatachalam CM, Jiang X, Oldfield T, Waldman M (2003) LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. J Mol Graph Model 21:289–307. doi:10.1016/S1093-3263(02)00164-X
Oprea TI, Matter H (2004) Integrating virtual screening in lead discovery. Curr Opin Chem Biol 8:349–358. doi:10.1016/j.cbpa.2004.06.008
Carlson HA (2002) Protein flexibility and drug design: how to hit a moving target. Curr Opin Chem Biol 6:447–452. doi:S1367593102003411
Lin JH, Perryman AL, Schames JR, McCammon JA (2002) Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J Am Chem Soc 124:5632–5633. doi:ja0260162
Amaro RE, Baron R, McCammon JA (2008) An improved relaxed complex scheme for receptor flexibility in computer-aided drug design. J Comput Aided Mol Des 22:693–705. doi:10.1007/s10822-007-9159-2
Ryan AJ, Gray NM, Lowe PN, Chung CW (2003) Effect of detergent on “promiscuous” inhibitors. J Med Chem 46(16):3448–3451. doi:10.1021/jm0340896
Durrant JD, Hall L, Swift RV et al (2010) Novel naphthalene-based inhibitors of Trypanosoma brucei RNA editing ligase 1. PLoS Negl Trop Dis 4:e803. doi:10.1371/journal.pntd.0000803
Moshiri H, Acoca S, Kala S et al (2011) Naphthalene-based RNA editing inhibitor blocks RNA editing activities and editosome assembly in Trypanosoma brucei. J Biol Chem 286:14178–14189. doi:10.1074/jbc.M110.199646
Moshiri H, Salavati R (2010) A fluorescence-based reporter substrate for monitoring RNA editing in trypanosomatid pathogens. Nucleic Acids Res 38:e138. doi:10.1093/nar/gkq333
Durrant JD, McCammon JA (2011) Towards the development of novel Trypanosoma brucei RNA editing ligase 1 inhibitors. BMC Pharmacol 11:9. doi:10.1186/1471-2210-11-9
Durrant JD, Friedman AJ, McCammon JA (2011) CrystalDock: a novel approach to fragment-based drug design. J Chem Inf Model 51:2573–2580. doi:10.1021/ci200357y
Durrant JD, Amaro RE, McCammon JA (2009) Autogrow: a novel algorithm for protein inhibitor design. Chem Biol Drug Des 73:168–178. doi:10.1111/j.1747-0285.2008.00761.x
Rostkowski M, Olsson MH, Sondergaard CR, Jensen JH (2011) Graphical analysis of pH-dependent properties of proteins predicted using PROPKA. BMC Struct Biol 11:6. doi:10.1186/1472-6807-11-6
Unni S, Huang Y, Hanson RM et al (2011) Web servers and services for electrostatics calculations with APBS and PDB2PQR. J Comput Chem 32:1488–1491. doi:10.1002/jcc.21720
Dolinsky TJ, Czodrowski P, Li H et al (2007) PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Res 35 (Web Server issue):W522–W525. doi: 10.1093/nar/gkm276
Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res 32 (Web Server issue):W665–W667. doi: 10.1093/nar/gkh381
Ho CK, Wang LK, Lima CD, Shuman S (2004) Structure and mechanism of RNA ligase. Structure 12:327–339. doi:10.1016/j.str.2004.01.011
Yin S, Ho CK, Shuman S (2003) Structure-function analysis of T4 RNA ligase 2. J Biol Chem 278:17601–17608. doi:10.1074/jbc.M300817200
Tomkinson AE, Vijayakumar S, Pascal JM, Ellenberger T (2006) DNA ligases: structure, reaction mechanism, and function. Chem Rev 106:687–699. doi:10.1021/cr040498d
Acknowledgments
This work was funded in part by the National Institutes of Health through the NIH Director’s New Innovator Award Program DP2-OD007237 to R.E.A.
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Demir, Ö., Amaro, R.E. (2013). Designing Novel Inhibitors of Trypanosoma brucei . In: Kortagere, S. (eds) In Silico Models for Drug Discovery. Methods in Molecular Biology, vol 993. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-342-8_15
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