1. TOP-LEAD IDENTIFICATION USING ENSEMBLE
BASED VIRTUAL SCREENING AND
PHARMACOPHORE DRUG DESIGN FOR
BREAST CANCER METASTATIC BETA ARRESTIN 2
Student: ÔNG ĐĂNG QUANG – BTBTIU10003
Supervisor: Dr. LÊ THỊ LÝ
International University
National University – HCMC
7. INTRODUCTION
β - ARRESTIN 2 INHIBITOR
ARRB2
progression of breast cancer
invasiveness
CXCR4-mediated chemotaxis
breast
cancer
metastasis,
migration.
extracellular-signal-
regulated kinase (ERK1/2)
Lysophosphatidic Acid (LPA)
protease-activated receptor-2
(PAR-2)
ARRB2 INHIBITOR
Li TT, et al. (2009), Michal AM, et al. (2011), Sun, Yue, et al.(2002), Ge, Lan, et al.(2004), Pampillo, et al.(2009), Alemayehu M, et al. (2013), Mills
GB, Moolenaar WH (2003).
11. RESULTS
β - ARRESTIN 2 SEQUENCE ANALYSIS
>95% identity
among 15
species.
Glaser, Fabian, et al. "ConSurf: identification of functional regions in proteins
by surface-mapping of phylogenetic information." Bioinformatics 19.1
(2003): 163-164.
12. RESULTS
3D STRUCTURE OF β – ARRESTIN 2
A B
blue is modeled structure
red is crystal structure of Bovin
Singh, Salam Pradeep, et al. "Prediction of the three-dimensional structure of serine/threonine protein kinase pto of Solanum lycopersicum by
homology modelling." Bioinformation 8.5 (2012): 212.
13. 3D STRUCTURE OF β – ARRESTIN 2
Z-SCORE
z-score value of the modeled structure is -7.17
Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins.
Nucleic Acids Res 35: W407–410.
14. 3D STRUCTURE OF β – ARRESTIN 2
RAMACHARAN PLOT
- No. of residues in
favoured region: 333
(84.3%)
- No. of residues in
allowed region: 39
(9.9%)
- No. of residues in
outlier region: 23
(5.8%)
Wiederstein M, Sippl MJ (2007)
ProSA-web: interactive web service
for the recognition of errors in three-
dimensional structures of proteins.
Nucleic Acids Res 35: W407–410.
15. TOP 15 POTENTIAL DRUGS MOLECULES
RESULTS
Trott, O.; Olson, A.J., Autodock vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and
multithreading. J Comput Chem 2010, 31, 455-461.
16. TOP 15 POTENTIAL DRUGS MOLECULES
Wishart, David S., et al. "DrugBank: a comprehensive resource for in silico
drug discovery and exploration." Nucleic acids research 34.suppl 1 (2006):
D668-D672.
17. PHARMACOPHORE
GENERATION
Hydrogen Bond Donor
as green vectored spheres
Hydrogen Bond Acceptor
as red vectored spheres
Hydrophobic as yellow
spheres
β-Arrestin2 active site is
shown as green.
(for column 1 & 2)
(for column 3)
18. COMMON PHARMACOPHORE FEATURES
Hydrogen Bond Donor as green vectored spheres
Hydrogen Bond Acceptor as red vectored spheres
Wolber, Gerhard, and Thierry Langer. "LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening
filters." Journal of chemical information and modeling 45.1 (2005): 160-169.
19. RESULTS
MOLECULAR SIMULATION
Total energy profile of human β-Arrestin 2
Kresse, Georg, and Jürgen Hafner. "Ab initio molecular dynamics for liquid metals." Physical Review B 47.1 (1993): 558.
20. MOLECULAR SIMULATION
ROOT MEAN SQUARE DEVIATION & FLUCTUATION ANALYSIS
≈ 0.1 nm
or 1 Å
17000 (ps)
Brunger, Axel T., J. Kuriyan, and Martin Karplus. "Crystallographic R factor refinement by molecular dynamics." Science 235.4787 (1987): 458-460.
21. MOLECULAR SIMULATION
RADIUS OF GYRATION CALCULATION
≈ 0.05 nm
or 0.5 Å
Lindahl, Erik, Berk Hess, and David Van Der Spoel. "GROMACS 3.0: a package for molecular simulation and trajectory analysis." Molecular
modeling annual 7.8 (2001): 306-317.
22. RESULTS
TOP NOVAL DRUG CANDIDATES
AM: arithmetic means
HM: harmonic mean
Beigel, J. H.; Farrar, J.; Han, A. M.; Hayden, F. G.; Hyer, R.; de Jong, M. D.; Lochindarat, S.; Nguyen, T. K.; Nguyen, T. H.; Tran, T. H.; Nicoll, A.; Touch,
S.; Yuen, K. Y. Avian influenza A (H5N1) infection in humans. N. Engl. J. Med. 2005, 353 (13), 1374–1385.
23. THE BEST 2 DRUG CANDIDATES
Rank ID Min.
HM
(kcal/mol)
Predicted Ki
(µM)
AM
(kcal/mol)
SD
(kcal/mol)
1 26 -8.4 -7.682 2.669 -7.604 0.3
2 1 -8 -7.169 6.555 -7.071 0.33
Compound 26 Compound 01
25. - Examining 3D structure of human ARRB2 model.
- Screening Drugbank database entirely for ARRB2 potential inhibitors.
- Suggesting pharmacophore features for ARRB2 inhibitors.
- Suggesting 2 best potential drug molecules as ARRB2 inhibitors.
- Time
- Computational resources
- Practical results
- Running molecular simulation for ARRB2-inhibitor complex.
- Building more good drug molecules as ARRB2 inhibitors.
- Cooperate computational methods with practical results.
- Try different drug database such as NCI (National Cancer Institute).
ACHIEVEMENTS
LIMITATIONS
FUTURE PLANS
26. REFERENCES
(1)Benovic JL, Kuhn H, Weyand I, Codina J, Caron MG, Lefkowitz RJ. 1987. Functional
desensitization of the isolated beta-adrenergic receptor by the beta-adrenergic receptor kinase:
potential role of an analog of the retinal protein arrestin (48-kDa protein). Proc. Natl. Acad. Sci.
USA 84:8879–82
(2)Lefkowitz RJ, Shenoy SK (2005) Transduction of receptor signals by beta-arrestins. Science 308:
512–517.
(3)McDonald PH, Lefkowitz RJ. Beta-Arrestins: new roles in regulating heptahelical receptors’
functions. Cell Signal. 2001; 13:683–689.
(4)Goodman OB, Krupnick JG, Santini F, Gurevich VV, Penn RB, et al. beta-arrestin acts as a clathrin
adaptor in endocytosis of the beta(2)-adrenergic receptor. Nature. 1996; 383:447–450.
(5)Laporte SA, Oakley RH, Zhang J, Holt JA, Ferguson SS, et al. The beta2-adrenergic receptor/beta
arrestin complex recruits the clathrin adaptor AP-2 during endocytosis. Proc Natl Acad Sci USA.
1999; 96:3712-3717.
(6)Claing A, Chen W, Miller WE, Vitale N, Moss J, et al. beta-Arrestin-mediated ADP-ribosylation
factor 6 activation and beta 2-adrenergic receptor endocytosis. J Biol Chem. 2001; 276:42509–
42513.
(7)McDonald PH, Cote NL, Lin FT, Premont RT, Pitcher JA, et al. Identification of NSF as a beta
arrestin1 binding protein - Implications for beta(2)-adrenergic receptor regulation. Journal of
Biological Chemistry. 1999; 274:10677–10680.
(8)Lefkowitz RJ, Shenoy SK (2006) New Roles for b-Arrestins in Cell Signaling: Not Just for Seven-
Transmembrane Receptors. Molecular Cell 24, 643–652.
(9)Buchanan FG, Gorden DL, Matta P, Shi Q, Matrisian LM, DuBois RN. Proc Natl Acad Sci
USA.2006; 103:1492–7.
(10)Zou L, Yang R, Chai J, Pei G. Faseb J. 2008; 22:355–64.
(11)Gavard J, Gutkind JS. Nat Cell Biol. 2006; 8:1223–34.
(12)Mythreye K, Blobe GC. Proc Natl Acad Sci USA. 2009; 106:8221–6.
(13)Lakshmikanthan V, Zou L, Kim JI, Michal A, Nie Z, Messias NC, Benovic JL, Daaka Y. Proc Natl
Acad Sci U S A. 2009; 106:9379–84.
(14)Raghuwanshi SK, Nasser MW, Chen X, Strieter RM, Richardson RM. J Immunol. 2008;
180:5699–706.
(15)Weigelt B, Peterse JL, van ’t Veer LJ (2005) Breast cancer metastasis: markers and models. Nat
Rev Cancer 5: 591–602.
(16)Li TT, Alemayehu M, Aziziyeh AI, Pape C, Pampillo M, et al. (2009) Beta-arrestin/Ral signaling
regulates lysophosphatidic acid-mediated migration and invasion of human breast tumor cells.
Mol Cancer Res 7: 1064–1077.
(17)Michal AM, Peck AR, Tran TH, Liu C, Rimm DL, et al. (2011) Differential expression of arrestins
is a predictor of breast cancer progression and survival. Breast Cancer Res Treat 130: 791–807.
(18)Sun, Yue, et al. "β-Arrestin2 is critically involved in CXCR4-mediated chemotaxis, and this is
mediated by its enhancement of p38 MAPK activation." Journal of Biological Chemistry 277.51
(2002): 49212-49219.
(19)Ge, Lan, et al. "Constitutive protease-activated receptor-2-mediated migration of MDA MB-
231 breast cancer cells requires both β-arrestin-1 and-2." Journal of Biological Chemistry 279.53
(2004): 55419-55424.
(20)Pampillo, Macarena, et al. "Regulation of GPR54 signaling by GRK2 and β-arrestin." Molecular
Endocrinology 23.12 (2009): 2060-2074.
(21)Alemayehu M, Dragan M, Pape C, Siddiqui I, Sacks DB, et al. (2013) b-Arrestin2 Regulates
Lysophosphatidic Acid-Induced Human Breast Tumor Cell Migration and Invasion via Rap1 and IQGAP1.
PLoS ONE 8(2): e56174.
(22)Mills GB, Moolenaar WH (2003) The emerging role of lysophosphatidic acid in cancer. Nat Rev Cancer
3: 582–591.
(23)Leluk, J. et al. (2001) Application of genetic semihomology algorithm to theoretical studies on various
protein families. ActaBiochim. Polon., 48, 21-33.
(24)Fogtman, A. et al.(2005) Beta-Spectrin Consensus Sequence Construction With Variable Threshold
Parameters; Verification of Usefulness, Bio-Algorithms and Med-Systems, 1, 117-120.
(25)Higgins D, Thompson J, Gibson T, Thompson JD, Higgins DG, et al. (1994) CLUSTAL W: improving the
sensitivity of progressive-multiple sequence alignment through sequence weighting, position-specific gap
penalties and weight matrix choice. Nucl Acids Res 22: 4673–4680.
(26)Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, et al. (2007) ClustalW and ClustalX
version 2. Bioinformatics 23: 2947–2948.
(27)Felsenstein J (1989) PHYLIP - Phylogeny Inference Package (Version 3.2). Cladistics 5: 164–166.
(28)Gajewska, E. Leluk, J. (2005) An Approach to Sequence Similarity Significance Estimation, Bio-
Algorithms and Med-Systems (ed. Medical College, Jagiellonian University), 1, 121-124
(29)Kus´ka J, Leluk J, Lesyng B (2010) TALANA: A novel application for protein variability/conservativity
calculation, Bio-Algorithms and Med-Systems, in press.
(30)Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in
three-dimensional structures of proteins. Nucleic Acids Res 35: W407–410.
(31)Trott, O.; Olson, A.J., Autodock vina: Improving the speed and accuracy of docking with a new scoring
function, efficient optimization, and multithreading. J Comput Chem 2010, 31, 455-461.
(32)Wolber, G.; Langer, T., Ligandscout: 3-d pharmacophores derived from protein-bound ligands and
their use as virtual screening filters. J Chem Inf Model 2005, 45, 160-169.
(33)W. B. Gleason & E. R. A. Johnson, “Protein Structure Analysis: A Tools Approach”, Practical Innovation
at BioCon, 2003.
(34)GaussView, Version 5, Roy Dennington, Todd Keith and John Millam, Semichem Inc., Shawnee Mission
KS, 2009.
(35)Berendsen, H.J.C.; van der Spoel, D.; van Drunen, R., GROMACS: A message-passing parallel molecular
dynamics implementation. Comp. Phys. Comm 1995, 91, 43-56.
(36)Hess, et al., GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular
Simulation. J. Chem. Theory Comput 2008, 4, 435-447.
(37)Berendsen, H.J.C.; Postma, J.P.M.; Gunsteren, W.Fv.; Hermans, J., Interaction models for water in
relation to protein hydration. Intermolecular Force,, 1981, pp. 331–342.
(38)Darden, T.A.; York, D.M.; and Pedersen, L.G., Particle mesh Ewald: An N•log(N) method for Ewald
sums in large systems. J. Chem. Phys, 1998, 10089–10092.
(39)Beigel, J. H.; Farrar, J.; Han, A. M.; Hayden, F. G.; Hyer, R.; de Jong, M. D.; Lochindarat, S.; Nguyen, T. K.;
Nguyen, T. H.; Tran, T. H.; Nicoll, A.; Touch, S.; Yuen, K. Y. Avian influenza A (H5N1) infection in humans. N.
Engl. J. Med. 2005, 353 (13), 1374–1385.
(40)Wang, Yaya, et al. "Association of β-arrestin and TRAF6 negatively regulates Toll-like receptor–
interleukin 1 receptor signaling." Nature immunology 7.2 (2006): 139-147.
(41)Kim, You-Me, et al. "Regulation of arrestin-3 phosphorylation by casein kinase II." Journal of Biological
Chemistry 277.19 (2002): 16837-16846.
(42)Sievers, Fabian, et al. "Fast, scalable generation of high‐quality protein multiple sequence alignments
using Clustal Omega." Molecular systems biology 7.1 (2011).
(43)Schmidt, Henning, and Mats Jirstrand. "Systems Biology Toolbox for MATLAB: a computational
platform for research in systems biology." Bioinformatics 22.4 (2006): 514-515.
(44)Glaser, Fabian, et al. "ConSurf: identification of functional regions in proteins by surface-mapping of
phylogenetic information." Bioinformatics 19.1 (2003): 163-164.
(45)Kua, J.; Zhang, Y.; McCammon, J. A. Studying enzyme binding specificity in acetylcholinesterase using a
combined molecular dynamics and multiple docking approach. J. Am. Chem. Soc. 2002, 124 (28), 8260–
8267.
(46)Lin, J. H.; Perryman, A. L.; Schames, J. R.; McCammon, J. A. Computational drug design accommodating
receptor flexibility: the relaxed complex scheme. J. Am. Chem. Soc. 2002, 124 (20), 5632–5633.
32. The mean square fluctuation (MSF) is a measure of the deviation between the
position of particle i and some reference position.
where T is the time over which one wants to average, and is the reference
position of particle i. Typically this reference position will be the time-averaged
position of the same particle i, i.e.
Note that the difference between RMSD and RMSF is that with the latter the average is taken over time, giving a value for each particle i. With RMSD the average is
taken over the particles, giving time resolved values.
When a dynamical system fluctuates about some well-defined
average position, the RMSD from the average over time can be
referred to as the RMSF or root mean square fluctuation.
Notas do Editor
Range of free energy of binding:
-11.6 to -6.6 (kcal/mol)
