Skip to main content

Advertisement

SpringerLink
Log in

Blind prediction of HIV integrase binding from the SAMPL4 challenge

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

Abstract

Here, we give an overview of the protein-ligand binding portion of the Statistical Assessment of Modeling of Proteins and Ligands 4 (SAMPL4) challenge, which focused on predicting binding of HIV integrase inhibitors in the catalytic core domain. The challenge encompassed three components—a small “virtual screening” challenge, a binding mode prediction component, and a small affinity prediction component. Here, we give summary results and statistics concerning the performance of all submissions at each of these challenges. Virtual screening was particularly challenging here in part because, in contrast to more typical virtual screening test sets, the inactive compounds were tested because they were thought to be likely binders, so only the very top predictions performed significantly better than random. Pose prediction was also quite challenging, in part because inhibitors in the set bind to three different sites, so even identifying the correct binding site was challenging. Still, the best methods managed low root mean squared deviation predictions in many cases. Here, we give an overview of results, highlight some features of methods which worked particularly well, and refer the interested reader to papers in this issue which describe specific submissions for additional details.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

Notes

  1. The SAMPL4 challenge was designed, run and evaluated by the Mobley lab with some help from Kim Branson, so when this report uses the word “we” to refer to an action relating to challenge design, logistics, and analysis, it refers to these authors—specifically, Mobley, Branson, Su, Lim, Wymer, and Liu.

  2. The challenge began with 322 compounds, 260 non-binders, and 62 binders, but due to errors and redundancies, final analysis was run on 305 compounds and 56 binders.

References

  1. Abram ME, Hluhanich RM, Goodman DD, Andreatta KN, Margot NA, Ye L, Niedziela-Majka A, Barnes TL, Novikov N, Chen X, Svarovskaia ES, McColl DJ, White KL, Miller MD (2013) Impact of primary Elvitegravir resistance-associated mutations in HIV-1 integrase on drug susceptibility and viral replication fitness. Antimicrob Agents Chemother 57(6):2654–2663

    Article  CAS  Google Scholar 

  2. Benson ML, Faver JC, Ucisik MN, Dashti DS, Zheng Z, Merz KM Jr (2012) Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores. J Comput Aided Mol Des 26(5):647–659

    Article  CAS  Google Scholar 

  3. Blow DM (2002) Rearrangement of Cruickshank’s formulae for the diffraction-component precision index. Acta Crystallogr Sect D Biol Crystallogr 58(5):792–797

    Article  CAS  Google Scholar 

  4. Cherepanov P, Ambrosio ALB, Rahman S, Ellenberger T, Engelman A (2005) Structural basis for the recognition between HIV-1 integrase and transcriptional coactivator p75. Proc Natl Acad Sci USA 102(48):17,308–17,313

    Article  CAS  Google Scholar 

  5. Chodera JD, Mobley DL, Shirts MR, Dixon RW, Branson K, Pande VS (2011) Alchemical free energy methods for drug discovery: progress and challenges. Curr Opin Struct Biol 21(2):150–160

    Article  CAS  Google Scholar 

  6. Christ F, Shaw S, Demeulemeester J, Desimmie BA, Marchand A, Butler S, Smets W, Chaltin P, Westby M, Debyser Z, Pickford C (2012) Small-molecule inhibitors of the LEDGF/p75 binding site of integrase block HIV replication and modulate integrase multimerization. Antimicrob Agents Chemother 56(8):4365–4374

    Article  CAS  Google Scholar 

  7. Christ F, Voet A, Marchand A, Nicolet S, Desimmie BA, Marchand D, Bardiot D, Vander Veken NJ, Van Remoortel B, Strelkov SV, De Maeyer M, Chaltin P, Debyser Z (2010) Rational design of small-molecule inhibitors of the LEDGF/p75-integrase interaction and HIV replication. Nat Meth 6(6):442–448

    Article  CAS  Google Scholar 

  8. Coleman RG, Sterling T, Weiss DR (2014) SAMPL4 & DOCK3.7: lessons for automated docking procedures. J Comput Aided Mol Des. doi:10.1007/s10822-014-9722-6

  9. Corbeil CR, Sulea T, Purisima EO (2010) Rapid prediction of solvation free energy. 2. The first-shell hydration (FiSH) continuum model. J Chem Theory Comput 6(5):1622–1637

    Article  CAS  Google Scholar 

  10. De Clercq E (1999) Perspectives of non-nucleoside reverse transcriptase inhibitors (NNRTIs) in the therapy of HIV-1 infection. Il Farmaco 54(1–2):26–45

    Article  CAS  Google Scholar 

  11. Dewdney TG, Wang Y, Kovari IA, Reiter SJ, Kovari LC (2013) Reduced HIV-1 integrase flexibility as a mechanism for raltegravir resistance. J Struct Biol 184:245–250

    Article  CAS  Google Scholar 

  12. Engelman A, Cherepanov P (2012) The structural biology of HIV-1: mechanistic and therapeutic insights. Nat Rev Microbiol 10(4):279–290

    Article  CAS  Google Scholar 

  13. Ewing TJ, Makino S, Skillman AG, Kuntz ID (2001) DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J Comput Aided Mol Des 15(5):411–428

    Article  CAS  Google Scholar 

  14. 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 proteinligand complexes. J Med Chem 49(21):6177–6196

    Article  CAS  Google Scholar 

  15. Gallicchio E, Deng N, He P, Perryman AL, Santiago DN, Forli S, Olson AJ, Levy RM (2014) Virtual screening of integrase inhibitors by large scale binding free energy calculations. J Comput Aided Mol Des. doi:10.1007/s10822-014-9711-9

  16. Gallicchio E, Lapelosa M, Levy RM (2010) The binding energy distribution analysis method (BEDAM) for the estimation of protein-ligand binding affinities. J Chem Theory Comput 6(9):2961–2977

    Article  CAS  Google Scholar 

  17. Geretti AM, Armenia D, Ceccherini-Silberstein F (2012) Emerging patterns and implications of HIV-1 integrase inhibitor resistance. Curr Opin Infect Dis 25(6):677–686. doi:10.1097/QCO.0b013e32835a1de7

    Article  CAS  Google Scholar 

  18. Greenwald J, Le V, Butler SL, Bushman FD, Choe S (1999) The mobility of an HIV-1 integrase active site loop is correlated with catalytic activity. Biochemistry 38(28):8892–8898

    Article  CAS  Google Scholar 

  19. Hare S, Maertens GN, Cherepanov P (2012) 3[prime]-Processing and strand transfer catalysed by retroviral integrase in crystallo. EMBO J 31(13):3020–3028

    Article  CAS  Google Scholar 

  20. Hare S, Smith SJ, Métifiot M, Jaxa-Chamiec A, Pommier Y, Hughes SH, Cherepanov P (2011) Structural and functional analyses of the second-generation integrase strand transfer inhibitor dolutegravir (S/GSK1349572). Mol Pharmacol 80(4):565–572

    Article  CAS  Google Scholar 

  21. Hare S, Vos AM, Clayton RF, Thuring JW, Cummings MD, Cherepanov P (2010) Molecular mechanisms of retroviral integrase inhibition and the evolution of viral resistance. Proc Natl Acad Sci 107(46):20,057–20,062

    Article  CAS  Google Scholar 

  22. Hawkins PCD, Nicholls A (2012) Conformer generation with OMEGA: learning from the data set and the analysis of failures. J Chem Inf Model 52(11):2919–2936

    Article  CAS  Google Scholar 

  23. 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 Databank and Cambridge Structural Database. J Chem Inf Model 50(4):572–584

    Article  CAS  Google Scholar 

  24. Hogues H, Sulea T, Purisima EO (2014) Exuastive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge. J Comput Aided Mol Des. doi:10.1007/s10822-014-9715-5

  25. Japrung D, Leartsakulpanich U, Chusacultanachai S, Yuthavong Y (2007) Conflicting requirements of Plasmodium falciparum dihydrofolate reductase mutations conferring resistance to pyrimethamine-WR99210 combination. Antimicrob Agents Chemother 51(12):4356–4360

    Article  CAS  Google Scholar 

  26. Jurado KA, Wang H, Slaughter A, Feng L, Kessl JJ, Koh Y, Wang W, Ballandras-Colas A, Patel PA, Fuchs JR, Kvaratskhelia M, Engelman A (2013) Allosteric integrase inhibitor potency is determined through the inhibition of HIV-1 particle maturation. Proc Natl Acad Sci 110(21):8690–8695

    Article  CAS  Google Scholar 

  27. Kessl JJ, Jena N, Koh Y, Taskent-Sezgin H, Slaughter A, Feng L, de Silva S, Wu L, Le Grice SFJ, Engelman A, Fuchs JR, Kvaratskhelia M (2012) Multimode, cooperative mechanism of action of allosteric HIV-1 integrase inhibitors. J Biol Chem 287(20):16,801–16,811

    Article  CAS  Google Scholar 

  28. Krishnan L, Engelman A (2012) Retroviral integrase proteins and HIV-1 DNA integration. J Biol Chem 287(49):40,858–40,866

    Article  CAS  Google Scholar 

  29. Kuhn B, Kollman PA (2000) Binding of a diverse set of ligands to avidin and streptavidin: an accurate quantitative prediction of their relative affinities by a combination of molecular mechanics and continuum solvent models. J Med Chem 43(20):3786–3791

    Article  CAS  Google Scholar 

  30. Kulp JL, Blumenthal SN, Wang Q, Bryan RL, Guarnieri F (2012) A fragment-based approach to the SAMPL3 challenge. J Comput Aided Mol Des 26(5):583–594

    Article  CAS  Google Scholar 

  31. Kumar A, Zhang KYJ (2012) Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge. J Comput Aided Mol Des 26(5):603–616

    Article  CAS  Google Scholar 

  32. Kuntz ID, Chen K, Sharp KA, Kollman PA (1999) The maximal affinity of ligands. Proc Natl Acad Sci 96(18):9997–10,002

    Article  CAS  Google Scholar 

  33. Lindorff-Larsen K, Piana S, Palmo K, Maragakis P, Klepeis JL, Dror RO, Shaw DE (2010) Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins pp NA–NA 78(8):1950–1958

    Google Scholar 

  34. Maertens GN, Hare S, Cherepanov P (2010) The mechanism of retroviral integration from X-ray structures of its key intermediates. Nature 468(7321):326–329

    Article  CAS  Google Scholar 

  35. MarvinSketch version 5.8.2 (2013) ChemAxon. http://www.chemaxon.com/products/marvin/marvinsketch/

  36. Métifiot M, Maddali K, Johnson BC, Hare S, Smith SJ, Zhao XZ, Marchand C, Burke TR, Hughes SH, Cherepanov P, Pommier Y (2013) Activities, crystal structures, and molecular dynamics of dihydro-1H-isoindole derivatives, inhibitors of HIV-1 integrase. ACS Chem Biol 8(1):209–217

    Article  Google Scholar 

  37. Mobley DL, Wymer KL, Lim NM (2014) Blind prediction of solvation free energies from the SAMPL4 challenge. J Comput Aided Mol Des

  38. Naïm M, Bhat S, Rankin KN, Dennis S, Chowdhury SF, Siddiqi I, Drabik P, Sulea T, Bayly CI, Jakalian A (2007) Solvated interaction energy (SIE) for scoring protein-ligand binding affinities. 1. Exploring the parameter space. J Chem Inf Model 47(1):122–133

    Article  Google Scholar 

  39. Newman J, Dolezal O, Fazio V, Caradoc-Davies T, Peat TS (2012) The DINGO dataset: a comprehensive set of data for the SAMPL challenge. J Comput Aided Mol Des 26(5):497–503

    Article  CAS  Google Scholar 

  40. Nicholls A, Mobley DL, Guthrie JP, Chodera JD, Bayly CI, Cooper MD, Pande VS (2008) Predicting small-molecule solvation free energies: an informal blind test for computational chemistry. J Med Chem 51(4):769–779

    Article  CAS  Google Scholar 

  41. OpenEye Python Toolkits. http://www.eyesopen.com (2013)

  42. Peat TS, Dolezal O, Newman J, Mobley DL, Deadman JJ (2014) Interrogating HIV integrase for compounds that bind—a SAMPL4 challenge. J Comput Aided Mol Des. doi:10.1007/s10822-014-9721-7

  43. Peat TS, Warren G (2013) Personal Communication. E-mail exchange

  44. Perryman AL, Forli S, Morris GM, Burt C, Cheng Y, Palmer MJ, Whitby K, McCammon JA, Phillips C, Olson AJ (2010) A dynamic model of HIV integrase inhibition and drug resistance. J Mol Biol 397(2):600–615

    Article  CAS  Google Scholar 

  45. Quashie PK, Mesplède T, Han YS, Veres T, Osman N, Hassounah S, Sloan R, Xu HT, Wainberg MA (2013) Biochemical analysis of the role of G118R-linked dolutegravir drug resistance substitutions in HIV-1 integrase. Antimicrob Agents Chemother 57(12):6223–6235

    Google Scholar 

  46. Quashie PK, Mesplède T, Wainberg MA (2013) Evolution of HIV integrase resistance mutations. Curr Opin Infect Dis 26(1):43–49. doi:10.1097/QCO.0b013e32835ba81c

    Google Scholar 

  47. Skillman AG, Warren GL, Nicholls A (2008) SAMPL at first glance: So much data, so little time…. http://www.eyesopen.com/2008_cup_presentations/CUP9_Skillman.pdf

  48. Sulea T, Cui Q, Purisima EO (2011) Solvated interaction energy (SIE) for scoring protein–ligand binding affinities. 2. Benchmark in the CSAR-2010 scoring exercise. J Chem Inf Model 51(9):2066–2081

    Article  CAS  Google Scholar 

  49. Sulea T, Hogues H, Purisima EO (2012) Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction. J Comput Aided Mol Des 26(5):617–633

    Article  CAS  Google Scholar 

  50. Surpateanu G, Iorga BI (2012) Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors. J Comput Aided Mol Des 26(5):595–601

    Article  CAS  Google Scholar 

  51. 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(2):455–461

    CAS  Google Scholar 

  52. Truchon J, Bayly CI (2007) Evaluating virtual screening methods: good and bad metrics for the “early recognition” problem. J Chem Inf Model 47(2):488–508

    Article  CAS  Google Scholar 

  53. Tsiang M, Jones GS, Niedziela-Majka A, Kan E, Lansdon EB, Huang W, Hung M, Samuel D, Novikov N, Xu Y, Mitchell M, Guo H, Babaoglu K, Liu X, Geleziunas R, Sakowicz R (2012) New class of HIV-1 integrase (IN) inhibitors with a dual mode of action. J Biol Chem 287(25):21,189–21,203

    Article  CAS  Google Scholar 

  54. Voet ARD, Kumar A, Berenger F, Zhang KYJ (2014) Combining in cerebra and in silico approaches for virtual screening and pose prediction in SAMPL4. J Comput Aided Mol Des. doi:10.1007/s10822-013-9702-2

  55. Wainberg MA, Mesplède T, Quashie PK (2012) The development of novel HIV integrase inhibitors and the problem of drug resistance. Curr Opin Virol 2(5):656–662

    Article  CAS  Google Scholar 

  56. Wang J, Wolf R, Caldwell J, Kollman P, Case D (2004) Development and testing of a general amber force field. J Comput Chem 25(9):1157–1174

    Article  CAS  Google Scholar 

  57. Wang R, Liu L, Lai L, Tang Y (1998) SCORE: a new empirical method for estimating the binding affinity of a protein-ligand complex. J Mol Model 4(12):379–394

    Article  CAS  Google Scholar 

  58. Zhang J, Adrian FJ, Jahnke W, Cowan-Jacob SW, Li AG, Iacob RE, Sim T, Powers J, Dierks C, Sun F, Guo GR, Ding Q, Okram B, Choi Y, Wojciechowski A, Deng X, Liu G, Fendrich G, Strauss A, Vajpai N, Grzesiek S, Tuntland T, Liu Y, Bursulaya B, Azam M, Manley PW, Engen JR, Daley GQ, Warmuth M, Gray NS (2010) Targeting Bcr-Abl by combining allosteric with ATP-binding-site inhibitors. Nature 463(7280):501–506

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We acknowledge the financial support of the National Institutes of Health (1R15GM096257-01A1 to DLM and R01 GM073087 and P50 GM103368 to AJO), and computing support from the UCI GreenPlanet cluster, supported in part by NSF Grant CHE-0840513. We are also grateful to OpenEye Scientific Software for support for SAMPL, including for the meeting and for logistical help with the website, and in particular would like to thank Matt Geballe for help with the website and submissions and for helpful discussions, and Paul Hawkins, Greg Warren, and Geoff Skillman for helpful discussions and pointers on analysis. We are also thankful to Tom Peat (CSIRO) and colleagues for the experimental data which made the integrase portion of SAMPL possible, and helped initiate SAMPL4.

Author information

Author notes

  1. Alexander L. Perryman

    Present address: Department of Medicine, Division of Infectious Diseases, Rutgers University-NJ Medical School, Newark, NJ, USA

Authors and Affiliations

  1. Department of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, 147 Bison Modular, Irvine, CA, 92697, USA

    David L. Mobley, Shuai Liu, Nathan M. Lim, Karisa L. Wymer & Justin Su

  2. Department of Chemistry, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA

    David L. Mobley

  3. Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037, USA

    Alexander L. Perryman, Stefano Forli & Arthur J. Olson

  4. Department of Chemistry and Chemical Biology Rutgers, The State University of New Jersey, A203, 610 Taylor Road, Piscataway, NJ, 08854, USA

    Nanjie Deng

  5. Hessian Informatics, LLC. 609 Lakeview Way, Emerald Hills, CA, USA

    Kim Branson

Authors
  1. David L. Mobley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuai Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nathan M. Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Karisa L. Wymer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alexander L. Perryman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Stefano Forli
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nanjie Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Justin Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kim Branson
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Arthur J. Olson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David L. Mobley.

Electronic supplementary material

Below is the link to the electronic supplementary material.

GZ (47,988 KB)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mobley, D.L., Liu, S., Lim, N.M. et al. Blind prediction of HIV integrase binding from the SAMPL4 challenge. J Comput Aided Mol Des 28, 327–345 (2014). https://doi.org/10.1007/s10822-014-9723-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-014-9723-5

Keywords

Search

Navigation