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In silico targeting PAD4 for the treatment of rheumatoid arthritis

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Abstract

Rheumatoid arthritis (RA) is an autoimmune disorder that causes chronic inflammation with periodic bursts of activity in multiple synovial joints which lead to irreversible damage of cartilage and bone. Although several drugs that reduce inflammation are used for the treatment of RA, they are often associated with side effects. Therefore, the development or identification of a drug with no side effects or reduced side effects is desirable. Protein arginine deiminases (PADs), a set of key enzymes to trigger autoimmune response necessary for the development of RA, can be targeted for the treatment of RA. In the present study, we had developed a pharmacophore model for PAD type 4 (PAD4) protein comprising single aromatic and three hydrogen acceptor groups. Pharmacophore-based virtual screening upon ZINC database mapped several hits which were subsequently reduced by molecular docking with PAD4 protein structure. The best-scoring two ligands (Zinc_00525911 and Zinc_01225171) selected based on docking energy, pharmacophore fitness, and topology among the hits were further validated using molecular dynamics simulation for 10 ns. These two ZINC hits established interactions with key amino acid residues of PAD4 including H-bonds with Arg 372, Arg 374, Asp 350, and His 471 residues. These prioritized hits can be further tested in the in vitro and in vivo models of RA.

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References

  1. Rheumatoid Arthritis (2018) National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Maryland. https://www.niams.nih.gov/health-topics/rheumatoid-arthritis. Accessed 10 May 2018

  2. Scott DL, Wolfe F, Huizinga TWJ (2010) Rheumatoid arthritis. Lancet (London, England) 376:1094–1108. https://doi.org/10.1016/S0140-6736(10)60826-4

    Article  Google Scholar 

  3. Gibofsky A (2012) Comparative effectiveness of current treatments for rheumatoid arthritis. Am J Manag Care 18:S303–S314

    PubMed  Google Scholar 

  4. Venables PJW (2018) Patient education: Rheumatoid arthritis treatment (Beyond the Basics) UpToDate Inc., Waltham. https://www.uptodate.com/contents/rheumatoid-arthritis-treatment-beyond-the-basics Accessed 10 May 2018

  5. Scott DL (2012) Biologics-based therapy for the treatment of rheumatoid arthritis. Clin Pharmacol Ther 91:30–43. https://doi.org/10.1038/clpt.2011.278

    Article  CAS  PubMed  Google Scholar 

  6. Mohanan S, Cherrington BD, Horibata S et al (2012) Potential role of peptidylarginine deiminase enzymes and protein citrullination in cancer pathogenesis. Biochem Res Int 2012:1–11. https://doi.org/10.1155/2012/895343

    Article  CAS  Google Scholar 

  7. Mangat P, Wegner N, Venables PJ, Potempa J (2010) Bacterial and human peptidylarginine deiminases: targets for inhibiting the autoimmune response in rheumatoid arthritis? Arthritis Res Ther 12:209. https://doi.org/10.1186/ar3000

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Guerrin M, Ishigami A, Méchin MC et al (2003) cDNA cloning, gene organization and expression analysis of human peptidylarginine deiminase type I. Biochem J 370:167–174. https://doi.org/10.1042/BJ20020870

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Chirivi RGS, van Rosmalen JWG, Jenniskens GJ et al (2013) Citrullination: a target for disease intervention in multiple sclerosis and other inflammatory diseases? J Clin Cell Immunol 04:1–8. https://doi.org/10.4172/2155-9899.1000146

    Article  CAS  Google Scholar 

  10. Ishigami A, Ohsawa T, Asaga H et al (2002) Human peptidylarginine deiminase type II: molecular cloning, gene organization, and expression in human skin. Arch Biochem Biophys 407:25–31

    Article  CAS  PubMed  Google Scholar 

  11. Suzuki A, Yamada R, Chang X et al (2003) Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet 34:395–402. https://doi.org/10.1038/ng1206

    Article  CAS  PubMed  Google Scholar 

  12. Arita K, Hashimoto H, Shimizu T et al (2004) Structural basis for Ca2+-induced activation of human PAD4. Nat Struct Mol Biol 11:777–783. https://doi.org/10.1038/nsmb799

    Article  CAS  PubMed  Google Scholar 

  13. Teo CY, Shave S, Chor ALT et al (2012) Discovery of a new class of inhibitors for the protein arginine deiminase type 4 (PAD4) by structure-based virtual screening. BMC Bioinformatics 13(Suppl 17):S4. https://doi.org/10.1186/1471-2105-13-S17-S4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Korb O, Stützle T, Exner TE (2009) Empirical scoring functions for advanced protein−ligand docking with PLANTS. J Chem Inf Model 49:84–96. https://doi.org/10.1021/ci800298z

    Article  CAS  PubMed  Google Scholar 

  15. Suzuki A, Yamada R, Yamamoto K (2007) Citrullination by peptidylarginine deiminase in rheumatoid arthritis. Ann N Y Acad Sci 1108:323–339

    Article  CAS  PubMed  Google Scholar 

  16. Baka Z, György B, Géher P et al (2012) Citrullination under physiological and pathological conditions. Joint Bone Spine 79:431–436. https://doi.org/10.1016/j.jbspin.2012.01.008

    Article  CAS  PubMed  Google Scholar 

  17. Eldridge MD, Murray CW, Auton TR et al (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 Aided Mol Des 11:425–445. https://doi.org/10.1023/A:1007996124545

    Article  CAS  PubMed  Google Scholar 

  18. Nakashima K, Arai S, Suzuki A et al (2013) PAD4 regulates proliferation of multipotent haematopoietic cells by controlling c-myc expression. Nat Commun 4:1836. https://doi.org/10.1038/ncomms2862

    Article  CAS  PubMed  Google Scholar 

  19. Wei Y, Liu R, Liu C et al (2017) Identification of novel PAD4 inhibitors based on a pharmacophore model derived from transition state coordinates. J Mol Graph Model 72:88–95. https://doi.org/10.1016/J.JMGM.2016.11.016

    Article  CAS  PubMed  Google Scholar 

  20. Rahman MB, Chor AL, Salleh AB et al (2013) Ligand-based virtual screening for the discovery of inhibitors for protein arginine deiminase type 4 (PAD4). J Postgenomics Drug Biomark Dev 03. https://doi.org/10.4172/2153-0769.1000118

  21. Sussman JL, Lin D, Jiang J et al (1998) Protein Data Bank (PDB): database of three-dimensional structural information of biological macromolecules. Acta Crystallogr Sect D Biol Crystallogr 54:1078–1084. https://doi.org/10.1107/S0907444998009378

    Article  CAS  Google Scholar 

  22. Guex N, Peitsch MC (1997) SWISS - MODEL and the Swiss - PdbViewer : an environment for comparative protein modeling. IS 21:14–2723. https://doi.org/10.1002/elps.1150181505

    Article  Google Scholar 

  23. Kumar SP, Jasrai YT, Pandya HA (2016) Applications of receptor- and ligand-based models in inverse docking experiments: recognition of dihydrofolate reductase using 7,8-Dialkyl- 1,3-Diaminopyrrolo[3,2-f]Quinazolines. Curr Comput Aided Drug Des 12:15–28

    Article  CAS  PubMed  Google Scholar 

  24. Kim S, Thiessen PA, Bolton EE et al (2016) PubChem substance and compound databases. Nucleic Acids Res 44:D1202–D1213. https://doi.org/10.1093/nar/gkv951

    Article  CAS  PubMed  Google Scholar 

  25. Marvin Sketch version 6.3.0 (2014) ChemAxon LLC, Budapest. https://chemaxon.com/company. Accessed 03 Mar 2018

  26. VLife MDS version 4.3 (2008) VLife Sciences Technologies Pvt. Ltd, Pune. http://www.vlifesciences.com/. Accessed 25 Mar 2018

  27. Kumar SP, Rawal RM, Pandya HA, Jasrai YT (2016) Qualitative and quantitative pharmacophore-similarity assessment of anthranilamide-based factor Xa inhibitors: applications on similar molecules with identical biological endpoints. J Recept Signal Transduction 36:189–206

    Article  CAS  Google Scholar 

  28. Ingale KB, Bhatia MS (2012) Identification of structural features for 4-Methyl-3-(6-[phenyl methylene] amino} Pyridine-3-yl)-2h Chromen-2-one derivatives as clotting factor XA inhibitors. Med Chem (Los Angeles) 8:299–307

    CAS  Google Scholar 

  29. Mareddy J, Suresh N, Kumar CG et al (2017) 1, 2, 3-Triazole-nimesulide hybrid: their design, synthesis and evaluation as potential anticancer agents. Bioorg Med Chem Lett 27:518–523

    Article  CAS  PubMed  Google Scholar 

  30. Deuflhard P (1974) A modified Newton method for the solution of ill-conditioned systems of nonlinear equations with application to multiple shooting. Numer Math 22:289–315

    Article  Google Scholar 

  31. Voet A, Qing X, Lee XY et al (2014) Pharmacophore modeling: advances, limitations, and current utility in drug discovery. J Recept Ligand Channel Res 7:81. https://doi.org/10.2147/JRLCR.S46843

    Article  CAS  Google Scholar 

  32. Koes DR, Camacho CJ (2012) ZINCPharmer: pharmacophore search of the ZINC database. Nucleic Acids Res 40:W409–W414. https://doi.org/10.1093/nar/gks378

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Discovery Studio Visualizer version 4.0 (2005) Accelrys Software Inc., San Diego. http://www.3dsbiovia.com/. Accessed 25 Mar 2018

  34. Berendsen HJC, Postma JPM, van Gunsteren WF et al (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81:3684–3690. https://doi.org/10.1063/1.448118

    Article  CAS  Google Scholar 

  35. Darden T, York D, Pedersen L (1993) Particle mesh Ewald: an N*log(N) method for Ewald sums in large systems. J Chem Phys 98:10089–10092. https://doi.org/10.1063/1.464397

    Article  CAS  Google Scholar 

  36. Liu RH, Meng JL (2003) MapDraw: a microsoft excel macro for drawing genetic linkage maps based on given genetic linkage data. Yi chuan Hered 25:317–321

    Google Scholar 

  37. Ferreira L, dos Santos R, Oliva G, Andricopulo A (2015) Molecular docking and structure-based drug design strategies. Molecules 20:13384–13421. https://doi.org/10.3390/molecules200713384

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kontoyiannis DP, Lewis RE (2004) Toward more effective antifungal therapy: the prospects of combination therapy. Br J Haematol 126:165–175. https://doi.org/10.1111/j.1365-2141.2004.05007.x

    Article  CAS  PubMed  Google Scholar 

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Funding

This study is financially supported by the Department of Science and Technology, New Delhi as Innovation in Science Pursuit for Inspired Research (INSPIRE) Fellowship.

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Correspondence to Himanshu A. Pandya.

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Soni, M.N., Kumar, S.P., Johar SR, K. et al. In silico targeting PAD4 for the treatment of rheumatoid arthritis. Struct Chem 30, 1323–1334 (2019). https://doi.org/10.1007/s11224-018-1263-5

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