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Studies of the benzopyran class of selective COX-2 inhibitors using 3D-QSAR and molecular docking

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Abstract

The Gaussian-based 3D-QSAR studies for 58 selective COX-2 (cyclooxygenase-2) inhibitors belonging to benzopyran chemical class were performed. Partial least squares analysis produced statistically significant model with (R 2training  = 0.866) and predictability (Q 2training  = 0.66, Q 2test  = 0.846). The 3D-QSAR model includes steric, electrostatic, hydrophobic, and hydrogen bond acceptor field indicators, whereas the potential field contributions indicate that the steric and hydrophobic features of the molecules play an important role in governing their biological activity. A molecular docking simulation and protein–ligand interaction pattern analysis reveal the importance of Tyr-361 and Ser-516 of the COX-2 active site for X-ray crystal structures and this class of molecules. Thus the combined approach of ligand-based and structure-based models provided an improved understanding in the interaction between benzopyran chemical class and COX-2 inhibition, which will guide the future identification of more potent anti-inflammatory drugs.

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References

  • Brooks WH, Daniel KG, Sung SS, Guida WC (2008) Computational validation of the importance of absolute stereochemistry in virtual screening. J Chem Inf Model 48:639–645

    Article  CAS  Google Scholar 

  • Cappel D, Dixon SL, Sherman W, Duan J (2015) Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling. J Comput Aided Mol Des 29:165–182

    Article  CAS  Google Scholar 

  • Cramer RD, Patterson DE, Bunce JD (1988) Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 110:5959–5967

    Article  CAS  Google Scholar 

  • Crofford LJ (1997) COX-1 and COX-2 tissue expression: implications and predictions. J Rheumatol Suppl 49:15–19

    CAS  PubMed  Google Scholar 

  • Deng Z, Chuaqui C, Singh J (2004) Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein–ligand binding interactions. J Med Chem 47:337–344

    Article  CAS  Google Scholar 

  • Fiorucci S, Meli R, Bucci M, Cirino G (2001) Dual inhibitors of cyclooxygenase and 5-lipoxygenase. A new avenue in anti-inflammatory therapy? Biochem Pharmacol 62:1433–1438

    Article  CAS  Google Scholar 

  • Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749

    Article  CAS  Google Scholar 

  • Friesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, Sanschagrin PC, Mainz DT (2006) Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J Med Chem 49:6177–6196

    Article  CAS  Google Scholar 

  • Fu JY, Masferrer JL, Seibert K, Raz A, Needleman P (1990) The induction and suppression of prostaglandin H2 synthase (cyclooxygenase) in human monocytes. J Biol Chem 265:16737–16740

    CAS  PubMed  Google Scholar 

  • Golbraikh A, Tropsha A (2002) Beware of q2! J Mol Gr Model 20:269–276

    Article  CAS  Google Scholar 

  • Harder E, Damm W, Maple J, Wu C, Reboul M, Xiang JY, Wang L, Lupyan D, Dahlgren MK, Knight JL, Kaus JW, Cerutti DS, Krilov G, Jorgensen WL, Abel R, Friesner RA (2016) OPLS3: a force field providing broad coverage of drug-like small molecules and proteins. J Chem Theory Comput 12:281–296

    Article  CAS  Google Scholar 

  • Jain AN (2000) Morphological similarity: a 3D molecular similarity method correlated with protein-ligand recognition. J Comput Aided Mol Des 14:199–213

    Article  CAS  Google Scholar 

  • Kelly MD, Mancera RL (2004) Expanded interaction fingerprint method for analyzing ligand binding modes in docking and structure-based drug design. J Chem Inf Comput Sci 44:1942–1951

    Article  CAS  Google Scholar 

  • Kujubu DA, Fletcher BS, Varnum BC, Lim RW, Herschman HR (1991) TIS10, a phorbol ester tumor promoter-inducible mRNA from Swiss 3T3 cells, encodes a novel prostaglandin synthase/cyclooxygenase homologue. J Biol Chem 266:12866–12872

    CAS  PubMed  Google Scholar 

  • Kumar S, Tiwari M (2013) Variable selection based QSAR modeling on Bisphenylbenzimidazole as inhibitor of HIV-1 reverse transcriptase. Med Chem 9:955–967

    Article  CAS  Google Scholar 

  • Masferrer JL, Seibert K, Zweifel B, Needleman P (1992) Endogenous glucocorticoids regulate an inducible cyclooxygenase enzyme. Proc Natl Acad Sci USA 89:3917–3921

    Article  CAS  Google Scholar 

  • O’Banion MK, Winn VD, Young DA (1992) cDNA cloning and functional activity of a glucocorticoid-regulated inflammatory cyclooxygenase. Proc Natl Acad Sci USA 89:4888–4892

    Article  Google Scholar 

  • O’Neill GP, Ford-Hutchinson AW (1993) Expression of mRNA for cyclooxygenase-1 and cyclooxygenase-2 in human tissues. FEBS Lett 330:156–160

    PubMed  Google Scholar 

  • Otto JC, Smith WL (1995) Prostaglandin endoperoxide synthases-1 and -2. J Lipid Mediat Cell Signal 12:139–156

    Article  CAS  Google Scholar 

  • Poongavanam V, Kongsted J (2013) Virtual screening models for prediction of HIV-1 RT associated RNase H inhibition. PLoS ONE 8:e73478

    Article  CAS  Google Scholar 

  • Pratim Roy P, Paul S, Mitra I, Roy K (2009) On two novel parameters for validation of predictive QSAR models. Molecules 14:1660–1701

    Article  Google Scholar 

  • Seibert K, Zhang Y, Leahy K, Hauser S, Masferrer J, Perkins W, Lee L, Isakson P (1994) Pharmacological and biochemical demonstration of the role of cyclooxygenase 2 in inflammation and pain. Proc Natl Acad Sci USA 91:12013–12017

    Article  CAS  Google Scholar 

  • Shelley JC, Cholleti A, Frye LL, Greenwood JR, Timlin MR, Uchimaya M (2007) Epik: a software program for pK(a) prediction and protonation state generation for drug-like molecules. J Comput Aided Mol Des 21:681–691

    Article  CAS  Google Scholar 

  • Siu SW, Pluhackova K, Bockmann RA (2012) Optimization of the OPLS-AA force field for long hydrocarbons. J Chem Theory Comput 8:1459–1470

    Article  CAS  Google Scholar 

  • Vane JR (1971) Inhibition of prostaglandin synthesis as a mechanism of action for aspirin-like drugs. Nat New Biol 231:232–235

    Article  CAS  Google Scholar 

  • Wang JL, Aston K, Limburg D, Ludwig C, Hallinan AE, Koszyk F, Hamper B, Brown D, Graneto M, Talley J, Maziasz T, Masferrer J, Carter J (2010a) The novel benzopyran class of selective cyclooxygenase-2 inhibitors. Part III: the three microdose candidates. Bioorg Med Chem Lett 20:7164–7168

    Article  CAS  Google Scholar 

  • Wang JL, Carter J, Kiefer JR, Kurumbail RG, Pawlitz JL, Brown D, Hartmann SJ, Graneto MJ, Seibert K, Talley JJ (2010b) The novel benzopyran class of selective cyclooxygenase-2 inhibitors-part I: the first clinical candidate. Bioorg Med Chem Lett 20:7155–7158

    Article  CAS  Google Scholar 

  • Wang JL, Limburg D, Graneto MJ, Springer J, Hamper JR, Liao S, Pawlitz JL, Kurumbail RG, Maziasz T, Talley JJ, Kiefer JR, Carter J (2010c) The novel benzopyran class of selective cyclooxygenase-2 inhibitors. Part 2: the second clinical candidate having a shorter and favorable human half-life. Bioorg Med Chem Lett 20:7159–7163

    Article  CAS  Google Scholar 

  • Xie WL, Chipman JG, Robertson DL, Erikson RL, Simmons DL (1991) Expression of a mitogen-responsive gene encoding prostaglandin synthase is regulated by mRNA splicing. Proc Natl Acad Sci USA 88:2692–2696

    Article  CAS  Google Scholar 

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Acknowledegements

We acknowledge the Science & Engineering Research Board (A Statutory body under the Department of Science & Technology, Government of India), New Delhi for financial support through the Young Scientist Project SB/YS/LS-130/2014 at the All India Institute of Medical Sciences (AIIMS), Jodhpur, India and National Research Foundation of Korea (NRF), which is funded by the Ministry of Education, Science, and Technology (No: 2012R1A6A3A04038302 and 2017R1C1B2003380).

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Conceived and designed the experiments: DKY, SK. Performed the experiments: DKY, Saloni, SK, HS. Analyzed the data: DKY SK, Saloni. Contributed reagents/materials/analysis tools: DKY, SK, SM, HS, PS, SM, KK, JC, MHK and HPS. Wrote the paper: DKY, SK and RLM.

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Correspondence to Dharmendra K. Yadav or Surendra Kumar.

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The authors have declared that no competing interests exist.

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Yadav, D.K., Saloni, Sharma, P. et al. Studies of the benzopyran class of selective COX-2 inhibitors using 3D-QSAR and molecular docking. Arch. Pharm. Res. 41, 1178–1189 (2018). https://doi.org/10.1007/s12272-017-0945-7

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  • DOI: https://doi.org/10.1007/s12272-017-0945-7

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