Skip to main content
Springer Nature Link
Log in

Design, structure-based focusing and in silico screening of combinatorial library of peptidomimetic inhibitors of Dengue virus NS2B-NS3 protease

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Serine protease activity of the NS3 protein of Dengue virus is an important target of antiviral agents that interfere with the viral polyprotein precursor processing catalyzed by the NS3 protease (NS3pro), which is important for the viral replication and maturation. Recent studies showed that substrate-based peptidomimetics carrying an electrophilic warhead inhibit the NS2B-NS3pro cofactor-protease complex with inhibition constants in the low micromolar concentration range when basic amino acid residues occupy P1 and P2 positions of the inhibitor, and an aldehyde warhead is attached to the P1. We have used computer-assisted combinatorial techniques to design, focus using the NS2B-NS3pro receptor 3D structure, and in silico screen a virtual library of more than 9,200 peptidomimetic analogs targeted around the template inhibitor Bz-Nle-Lys-Arg-Arg-H (Bz—benzoyl) that are composed mainly of unusual amino acid residues in all positions P1–P4. The most promising virtual hits were analyzed in terms of computed enzyme-inhibitor interactions and Adsorption, Distribution, Metabolism and Excretion (ADME) related physico-chemical properties. Our study can direct the interest of medicinal chemists working on a next generation of antiviral chemotherapeutics against the Dengue Fever towards the explored subset of the chemical space that is predicted to contain peptide aldehydes with NS3pro inhibition potencies in nanomolar range which display ADME-related properties comparable to the training set inhibitors.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Abbreviations

ADME:

Adsorption distribution metabolism and excretion

CFF91:

Consistent class II force field

DEN2:

Dengue virus serological type 2

DHF:

Dengue hemorrhagic fever

MM:

Molecular mechanics

NS2B:

Nonstructural protein 2B (essential cofactor)

NS3:

Nonstructural protein 3

NS3pro:

Serine protease domain of the NS3 protein

Abu:

α-Aminobutyric acid

Bz:

Benzoyl

Cit:

Citrulline

hHis:

Homo-histidine

N-MeArg:

(N-methyl)-arginine

2Nal:

β-(2-Naphthyl)-alanine

Nle:

Norleucine

Nva:

Norvaline

Orn:

Ornithine

p(Py)Ala:

β-(4-Pyridyl)-alanine

p(Ac)Phe:

(4-N-Acetylamino)-phenylalanine

m(Am)Phe:

(3-Amino)-phenylalanine

p(Am)Phe:

(4-Amino)-phenylalanine

p(Cl)Phe:

(4-Chloro)-phenylalanine

p(CN)Phe:

(4-Cyano)-phenylalanine

m(Gn)Phe:

(3-Guanidino)-phenylalanine

p(Gn)Phe:

(4-Guanidino)-phenylalanine

m(Im)Phe:

(3-Imino)-phenylalanine

p(Im)Phe:

(4-Imino)-phenylalanine

p(Ip)Phe:

(4-Isopropyl)-phenylalanine

(Md)Phe:

(3,4-Methylenedioxy)-phenylalanine

p(Hm)Phe:

(4-Hydroxymethyl)-phenylalanine

p(Me)Phe:

(4-Methyl)-phenylalanine

(dMo)Phe:

(3,4-Dimethoxy)-phenylalanine

p(Ph)Phe:

(4-Phenyl)-phenylalanine

References

  1. Rice CM (1996) In: Fields BN, Knipe DM, Howley PM (eds) Fields virology. Lippincott-Raven, Philadelphia, pp 931–959

    Google Scholar 

  2. Gosh D, Basu A (2008) Present perspectives on flaviviral chemotherapy. Drug Discov Today 13:619–624

    Article  Google Scholar 

  3. Mackenzie JS, Gubler DJ, Petersen LR (2004) Emerging flaviviruses: the spread and resurgence of Japanese encephalitis, West Nile and dengue viruses. Nat Med 10(12 suppl):S98–S109

    Article  CAS  Google Scholar 

  4. Dengue and Dengue Haemorrhagic Fever (2009) WHO fact sheet no. 117. World Health Organization, Geneva. Retrieved from http://http://www.who.int/mediacentre/factsheets/fs117/en/ 1/9/2009

  5. Chambers TJ, Hahn CS, Galler R, Rice CM (1990) Flavivirus genome organization, expression, and replication. Annu Rev Microbiol 44:649–688

    Article  CAS  Google Scholar 

  6. Falgout B, Pethel M, Zhang YM, Lai CJ (1991) Both nonstructural proteins NS2B and NS3 are required for the proteolytic processing of dengue virus nonstructural proteins. J Virol 65:2467–2475

    CAS  Google Scholar 

  7. Chambers TJ, Weir RC, Grakoui A, McCourt DW, Bazan JF, Fletterick RJ, Rice CM (1990) Evidence that the N-terminal domain of nonstructural protein NS3 from yellow fever virus is a serine protease responsible for site-specific cleavages in the viral polyprotein. Proc Natl Acad Sci USA 87:8898–8902

    Article  CAS  Google Scholar 

  8. Preugschat F, Yao CW, Strauss JH (1990) In vitro processing of dengue virus type 2 nonstructural proteins NS2A, NS2B, and NS3. J Virol 64:4364–7434

    CAS  Google Scholar 

  9. Li H, Clum S, You S, Ebner KE, Padmanabhan R (1999) The serine protease and RNA-stimulated nucleoside triphosphatase and RNA helicase functional domains of dengue virus type 2 NS3 converge within a region of 20 amino acids. J Virol 73:3108–3116

    CAS  Google Scholar 

  10. Murthy HM, Clum S, Padmanabhan R (1999) Dengue virus NS3 serine protease. Crystal structure and insights into interaction of the active site with substrates by molecular modeling and structural analysis of mutational effects. J Biol Chem 274:5573–5580

    Article  CAS  Google Scholar 

  11. Clum S, Ebner KE, Padmanabhan R (1997) Cotranslational membrane insertion of the serine proteinase precursor NS2B-NS3(Pro) of dengue virus type 2 is required for efficient in vitro processing and is mediated through the hydrophobic regions of NS2B. J Biol Chem 272:30715–30723

    Article  CAS  Google Scholar 

  12. Leung D, Schroder K, White H, Fang NX, Stoermer MJ, Abbenante G, Martin JL, Young PR, Fairlie DP (2001) Activity of recombinant dengue 2 virus NS3 protease in the presence of a truncated NS2B co-factor, small peptide substrates, and inhibitors. J Biol Chem 276:45762–45771

    Article  CAS  Google Scholar 

  13. Zhang L, Mohan PM, Padmanabhan R (1992) Processing and localization of Dengue virus type 2 polyprotein precursor NS3-NS4A-NS4B-NS5. J Virol 66:7549–7554

    CAS  Google Scholar 

  14. Chanprapaph S, Saparpakorn P, Sangma C, Niyomrattanakit P, Hannongbua S, Angsuthanasombat C, Katzenmeier G (2005) Competitive inhibition of the dengue virus NS3 serine protease by synthetic peptides representing polyprotein cleavage sites. Biochem Biophys Res Commun 330:1237–1246

    Article  CAS  Google Scholar 

  15. Ganesh VK, Muller N, Judge K, Luan CH, Padmanabhan R, Murthy KH (2005) Identification and characterization of nonsubstrate based inhibitors of the essential dengue and West Nile virus proteases. Bioorg Med Chem 13:257–264

    Article  CAS  Google Scholar 

  16. Ekonomiuk D, Su XC, Ozawa K, Bodenreider C, Lim SP, Yin Z, Keller TH, Beer D, Patel V, Otting G, Caflisch A, Huang D (2009) Discovery of a non-peptidic inhibitor of west nile virus NS3 protease by high-throughput docking. PLoS Negl Trop Dis 3:e356

    Article  Google Scholar 

  17. Li J, Lim SP, Beer D, Patel V, Wen D, Tumanut C, Tully DC, Williams JA, Jiricek J, Priestle JP, Harris JL, Vasudevan SG (2005) Functional profiling of recombinant NS3 proteases from all four serotypes of dengue virus using tetrapeptide and octapeptide substrate libraries. J Biol Chem 280:28766–28774

    Article  CAS  Google Scholar 

  18. Wahab HA, Yusof R, Rahman NA (2007) A search for vaccines and therapeutic for dengue: a review. Curr Comput Aided Drug Des 3:341–352

    Article  Google Scholar 

  19. Othman R, Kiat TS, Khalid N, Yusof R, Newhouse EI, Newhouse JS, Alam M, Rahman NA (2008) Docking of noncompetitive inhibitors into dengue virus type 2 protease: understanding the interactions with allosteric binding sites. J Chem Inf Model 48:1582–1591

    Article  CAS  Google Scholar 

  20. Yin Z, Patel SJ, Wang WL, Wang G, Chan WL, Rao KR, Alam J, Jeyaraj DA, Ngew X, Patel V, Beer D, Lim SP, Vasudevan SG, Keller TH (2006) Peptide inhibitors of Dengue virus NS3 protease. Part 1: warhead. Bioorg Med Chem Lett 16:36–39

    Article  CAS  Google Scholar 

  21. Yin Z, Patel SJ, Wang WL, Chan WL, Ranga Rao KR, Wang G, Ngew X, Patel V, Beer D, Knox JE, Ma NL, Ehrhardt C, Lim SP, Vasudevan SG, Keller TH (2006) Peptide inhibitors of dengue virus NS3 protease. Part 2: SAR study of tetrapeptide aldehyde inhibitors. Bioorg Med Chem Lett 16:40–43

    Article  CAS  Google Scholar 

  22. Luo D, Xu T, Hunke C, Grüber G, Vasudevan SG, Lescar J (2008) Crystal structure of the NS3 protease-helicase from dengue virus. J Virol 82:173–183

    Article  CAS  Google Scholar 

  23. Murthy HM, Judge K, DeLucas L, Padmanabhan R (2000) Crystal structure of Dengue virus NS3 protease in complex with a Bowman–Birk inhibitor: implications for flaviviral polyprotein processing and drug design. J Mol Biol 301:759–767

    Article  CAS  Google Scholar 

  24. Erbel P, Schiering N, D’Arcy A, Renatus M, Kroemer M, Lim SP, Yin Z, Keller TH, Vasudevan SG, Hommel U (2006) Structural basis for the activation of flaviviral NS3 proteases from dengue and West Nile virus. Nat Struct Mol Biol 13:372–373

    Article  CAS  Google Scholar 

  25. Llinàs-Brunet M, Bailey M, Fazal G, Ghiro E, Gorys V, Goulet S, Halmos T, Maurice R, Poirier M, Poupart M-A, Rancourt Thibeault JD, Wernic D, Lamarre D (2000) Highly potent and selective peptide-based inhibitors of the hepatitis C virus serine protease: towards smaller inhibitors. Bioorg Med Chem Lett 10:2267–2270

    Article  Google Scholar 

  26. Johansson A, Hubatsch I, Åkerblom E, Lindeberg G, Winiwarter S, Danielson UH, Hallberg A (2001) Inhibition of hepatitis C virus NS3 protease activity by product-based peptides is dependent on helicase domain. Bioorg Med Chem Lett 11:203–206

    Article  CAS  Google Scholar 

  27. Perni RB, Britt SD, Court JC, Courtney LF, Deininger DD, Farmer LJ, Gates CA, Harbeson SL, Kim JL, Landro JA, Levin RB, Luong Y-P, O’Malley ET, Pitlik J, Rao BG, Schairer WC, Thomson JA, Tung RD, Van Drie JH, Wei Y (2003) Inhibitors of hepatitis C virus NS3.4A protease 1. Non-charged tetrapeptide variants. Bioorg Med Chem Lett 13:4059–4063

    Article  CAS  Google Scholar 

  28. Perni RB, Pitlik J, Britt SD, Court JJ, Courtney LF, Deininger DD, Farmer LF, Gates CA, Harbeson SL, Levin RB, Lin C, Lin K, Moon Y-C, Luong Y-P, O’Malley ET, Rao BG, Thomson JA, Tung RD, Van Drie JH, Wei Y (2004) Inhibitors of hepatitis C virus NS3.4A protease 2. Warhead SAR and optimization. Bioorg Med Chem Lett 14:1441–1446

    Article  CAS  Google Scholar 

  29. Frecer V, Kabelac M, De Nardi P, Pricl S, Miertus S (2004) Structure-based design of inhibitors of NS3 serine protease of hepatitis C virus. J Mol Graph Model 22:209–220

    Article  CAS  Google Scholar 

  30. Liverton NJ, Holloway MK, McCauley JA, Rudd MT, Butcher JW, Carroll SS, DiMuzio J, Fandozzi C, Gilbert KF, Mao S-S, McIntyre CJ, Nguyen KT, Romano JJ, Stahlhut M, Wan B-L, Olsen DB, Vacca JP (2008) Molecular modeling based approach to potent P2–P4 macrocyclic inhibitors of hepatitis C NS3/4A protease. J Am Chem Soc 130:4607–4609

    Article  CAS  Google Scholar 

  31. Boloor A, Hanway D, Joshi M, Winn DT, Mendez G, Walls M, Wei P, Qian F, Zhang X, Zhang Y, Hepperle ME, Li X, Campbell DA, Betancort JM (2009) Synthesis and antiviral activity of HCV NS3/4A peptidomimetic boronic acid inhibitors. Bioorg Med Chem Lett 19:5708–5711

    Article  CAS  Google Scholar 

  32. Liverton NJ, Carroll SS, Dimuzio J, Fandozzi C, Graham DJ, Hazuda D, Holloway MK, Ludmerer SW, McCauley JA, McIntyre CJ, Olsen DB, Rudd MT, Stahlhut M, Vacca JP (2010) MK-7009, a potent and selective inhibitor of hepatitis C virus NS3/4A protease. Antimicrob Agents Chemother 54:305–311

    Article  CAS  Google Scholar 

  33. Frecer V, Burello E, Miertus S (2005) Combinatorial design of nonsymmetrical cyclic urea inhibitors of aspartic protease of HIV-1. Bioorg Med Chem 13:5492–5501

    Article  CAS  Google Scholar 

  34. Frecer V, Berti F, Benedetti F, Miertus S (2008) Design of peptidomimetic inhibitors of aspartic protease of HIV-1 containing -Phe Psi Pro- core and displaying favourable ADME-related properties. J Mol Graph Model 27:376–387

    Article  CAS  Google Scholar 

  35. Frecer V, Megnassan E, Miertus S (2009) Design and in silico screening of combinatorial library of antimalarial analogs of triclosan inhibiting Plasmodium falciparum enoyl-acyl carrier protein reductase. Eur J Med Chem 44:3009–3019

    Article  CAS  Google Scholar 

  36. Rungrotmongkol T, Frecer V, De-Eknamkul W, Hannongbua S, Miertus S (2009) Design of oseltamivir analogs inhibiting neuraminidase of avian influenza virus H5N1. Antiviral Res 82:51–58

    Article  CAS  Google Scholar 

  37. Bajusz S, Szell E, Bagdy D, Barabas E, Horvath G, Dioszegi M, Fittler Z, Szabo G, Juhasz A, Tomori E (1990) Highly active and selective anticoagulants: d-Phe-Pro-Arg-H, a free tripeptide aldehyde prone to spontaneous inactivation, and its stable N-methyl derivative, d-MePhe-Pro-Arg-H. J Med Chem 33:1729–1735

    Article  CAS  Google Scholar 

  38. Fehrentz J-A, Paris M, Heitz A, Velek J, Liu C-F, Winternitz F, Martinez J (1995) Improved solid phase synthesis of C-terminal peptide aldehydes. Tetrahedron Lett 36:7871–7874

    Article  CAS  Google Scholar 

  39. Cerius2 Life Sciences software, version 4.6 (2002) Accelrys, San Diego, CA

  40. Peters KP, Fauck J, Frommel C (1996) The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. J Mol Biol 256:201–213

    Article  CAS  Google Scholar 

  41. Jarvis RA, Patrick EA (1973) Clustering using a similarity measure based on shared near neighbors. IEEE Trans Comput C22:1025–1034

    Article  Google Scholar 

  42. Seifert MH (2009) Targeted scoring functions for virtual screening. Drug Discov Today 14:562–569

    Article  Google Scholar 

  43. Böhm HJ (1994) The development of a simple empirical scoring function to estimate the binding constant for a protein–ligand complex of known three-dimensional structure. J Comput Aided Mol Des 8:243–256

    Article  Google Scholar 

  44. Böhm HJ (1998) Prediction of binding constants of protein ligands: a fast method for the prioritization of hits obtained from de novo design or 3D database search programs. J Comput Aided Mol Des 12:309–323

    Article  Google Scholar 

  45. Muegge I, Martin YC (1999) A general and fast scoring function for protein–ligand interactions: a simplified potential approach. J Med Chem 42:791–804

    Article  CAS  Google Scholar 

  46. Muegge I, Martin YC, Hajduk PJ, Fesik SW (1999) Evaluation of PMF scoring in docking weak ligands to the FK506 binding protein. J Med Chem 42:2498–2503

    Article  CAS  Google Scholar 

  47. Verkhivker GM, Appelt K, Freer ST, Villafranca JE (1995) Empirical free energy calculations of ligand–protein crystallographic complexes. I. Knowledge-based ligand–protein interaction potentials applied to the prediction of human immunodeficiency virus 1 protease binding affinity. Protein Eng 8:677–691

    Article  CAS  Google Scholar 

  48. Stahl M (2000) In: Böhm HJ, Schneider G (eds) Virtual screening for bioactive molecules. Wiley-VCH, Weinheim, pp 229–264

    Chapter  Google Scholar 

  49. Jain AN (2004) Virtual screening in lead discovery and optimization. Curr Opin Drug Discov Devel 7:396–403

    CAS  Google Scholar 

  50. QikProp, version 2.0.005 (2002) Schrödinger LLC, New York, NY

  51. Maple JR, Hwang MJ, Stockfish TP, Dinur U, Waldman M, Ewing CS, Hagler AT (1994) Derivation of class II force fields. I. Methodology and quantum force field for the alkyl functional group and alkane molecules. J Comput Chem 15:162–182

    Article  CAS  Google Scholar 

  52. Rappé AK, Goddard WA III (1991) Charge equilibration for molecular dynamics simulations. J Phys Chem 95:3358–3363

    Article  Google Scholar 

  53. Available Chemicals Directory, version 3.0 (2008) Symyx Technologies Inc., Santa Clara, CA

  54. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG (2007) ClustalW and ClustalX version 2. Bioinformatics 23:2947–2948

    Article  CAS  Google Scholar 

  55. Insight-II Life Sciences software, version 2005 (2005) Accelrys, San Diego, CA

  56. Duffy EM, Jorgensen WL (2000) Prediction of properties from simulations: free energies of solvation in hexadecane, octanol, and water. J Am Chem Soc 122:2878–2888

    Article  CAS  Google Scholar 

  57. Jorgensen WL, Duffy EM (2000) Prediction of drug solubility from Monte Carlo simulations. Bioorg Med Chem Lett 10:1155–1158

    Article  CAS  Google Scholar 

  58. Jorgensen WL, Duffy EM (2002) Prediction of drug solubility from structure. Adv Drug Deliv Rev 54:355–366

    Article  CAS  Google Scholar 

  59. Voet D, Voet JG (1995) Biochemistry, 2nd edn. Wiley, New York

    Google Scholar 

Download references

Acknowledgments

This work has been done within the ICS-UNIDO global program on Rational Drug Design and Discovery. The institutional support to this work is gratefully acknowledged.

Author information

Authors and Affiliations

  1. International Centre for Science and High Technology, UNIDO, AREA Science Park, Padriciano 99, 34012, Trieste, Italy

    Vladimir Frecer & Stanislav Miertus

  2. Cancer Research Institute, Slovak Academy of Sciences, 83391, Bratislava, Slovakia

    Vladimir Frecer

  3. Laboratory of Molecular, Biostructural and Nanomaterial Modeling, Consortium AREA Science Park of Trieste, AREA Science Park, 34012, Trieste, Italy

    Vladimir Frecer

Authors
  1. Vladimir Frecer
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Stanislav Miertus
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Stanislav Miertus.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Frecer, V., Miertus, S. Design, structure-based focusing and in silico screening of combinatorial library of peptidomimetic inhibitors of Dengue virus NS2B-NS3 protease. J Comput Aided Mol Des 24, 195–212 (2010). https://doi.org/10.1007/s10822-010-9326-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-010-9326-8

Keywords