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23/04/2019
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Layout of the presentation
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✓ Basic principles of cell-based assaysSources of cellsQualtitative and (semi)quantitative studiesImportant considerations in quantitative assaysCell-based assays in drug discovery & medicinal chemistry
✓ ApplicationsDrug discovery & medicinal chemistryMaterial scienceNatural products
✓ Challenges and basic references in cell culture and assays
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Cell and biobanks
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❖ Mammalian cells and microorganismsBanco de Células do Rio de Janeiro (BCRJ)Coleção Brasileira de Microrganismos de Ambiente e Indústria (CBMAI)American Type Cell Culture (ATCC)Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbHPublic Health England ... and many others...
❖ A reliable source of cells is essential to the development of a study
❖ Missidentification of cell linesShort tandem repeat (STR) for cell authentication
❖ Contamination with other cells
Mycoplasma is one of the most important problems
Methods: Biouminescence Polymerase chain reaction (PCR)Fluorescence Scanning Electron Mycroscopy (SEM)
Invivogen data http://bcrj.org.br/
Qualitative, (semi)quantitative studies
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✓ Check the blank
✓ Choose your controls with care
✓ Check the error of the experiments
✓ Analyse the cell response variations , samples, etc.
Reproducibility
✓ Design the layout of the experiment
Qualitative: yes/no answer using a cutoffSemi-quantitative: range of response (weak, medium, strong)Quantitative: potency
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Qualitative, (semi)quantitative studies
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Qualitative results
? !
Jones, G. J. Comput. Aided Mol. Des. 2015, 29, 1.
Effectiveconcentration
May be used forAgonist or antagonist
Inhibitoryconcentration
Cytotoxicconcentration
GrowthInhibition
Cytostaticactivity
Quantification: Concentration-response curve
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GI50 IC50 EC50 CC50
GI90 IC90 EC90 CC90
IC50 = 0.711 µM 0.713 µM 0.715 µM
SE = 0.0975 0.143 0.138R2 = 0.995 0.987 0.988S = 3.31 3.22 2.82
LogIC50 -6.15HillSlope -0.704IC50 7.11x10-7
Span 104
95% Confidence IntervalsBottom -7.40 to 3.76Top 97.7 to 106LogIC50 -6.27 to -6.03HillSlope -0.843 to -0.564IC50 5.34x10-7 to 9.45x10-7
Span 95.5 to 112Goodness of FitDegrees of Freedom 14R square 0.995Absolute Sum of Squares 154Sy.x 3.31Number of pointsAnalyzed 18
Std. ErrorBottom 2.60Top 1.90LogIC50 0.0577HillSlope 0.0650Span 3.74
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Quantitative study
Importance of the Hill slope
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✓ Formula: Y= Bottom +(Top -Bottom)(1+10((LogIC50-X).HillSlope))
Hill = -1
Hill = -10
log(inhibitor) vs. responseVariable slope (four parameters) Ambiguous
Best-fit values
Bottom 2.33
Top 99.5
LogIC50 ~ -6.99
HillSlope ~ -7.46
IC50 ~ 1,01x10-7
Span 97.2
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Caldwell, G.W.; et al. Curr. Top. Med. Chem. 2012, 12, 1282.
Quantitative study
Potency versus efficacy
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❖ Potency: amount of a compound that leads to a defined effect.
❖ Efficacy: maximum effect that a compound produces regardlessof the dose.
https://step1.medbullets.com/pharmacology/107007/efficacy-vs-potency
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Factors that influence the assays
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❖ Many problems by bias the assay, like problem with the cell passage,compound degradation or precipitation, plates with problems, amongothers.
❖ For colorimetric assays: Compound can absorb in the same wavelenght.
❖ For fluorescence assays:❖ Compound can supress fluorescence (quencher)❖ Compound can absorb and emmit in the same conditions❖ Cells have green fluorescence background
Always check your system
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Cell lines have a specific size and shape
Round or odd-shape cellsVacuolationGranulationSize and shape of the nucleusetc.
Temporal progression of VERO cellvacuolation (phase-contrast lightmicroscopy; magnification, ×200).
Control cells(negative control)
Concanamycin(Positive control)
1 h incubation
V. cholerae hemolysin1-2 h incubation
Concanamycin +V. cholerae hemolysin
2 h incubation
V. cholerae hemolysinlonger incubation
Figueroa-Arredondo, P.; et al.Infect Immun. 2001, 69, 1613.
c-Myc-knockdown cells (HeLa-630)Confocal microscopy
Cui, F.; et al. Oncol. Lett. 2017, 14, 2878.
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Always check your system
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Negative control Estradiol
Ethanol/water (80:20) Ethanol/water (95:5)
Granulation of breast cancercells (MCF-7) is observed for
Morus alba extracts high ethanol proportion
Manuscript in preparation
Compound precipitation(green and cells (blue)
[cpd] = 50.0 µM
[cpd] = 6.25 µM
Drug discovery process
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Cell-based assays are essential to link the biochemical to in vivo assays via in vitro studies
DrugLigandsBiological
targetPrototype
compound
Disovery and
development
Identification
and
optimization
Clinical
trialsApproval
Clinical trials:
phase IVPhases
I, II e III
0 5 15
Estimated time (years)
Previously to
drug discovery
Cell-based assays
Leitão, A.; Montanari, M. L. C. ; Montanari, C. A. Desenvolvimento de fármacos. In: Montanari, C. A. (Org.) QUÍMICA MEDICINAL: Métodos e fundamentos em planejamento de fármacos. 1ed. São Paulo: EDUSP, 2011, v. , p. 94-127.
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Medicinal Chemistry & cell-based assays
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Known target and ligand Known target only
SBDD(VS) and LBDD(VS)SBDD
de novo
Known ligand only Ligand and target unknown
LBDDLigand diversity (chemical library)
Use compounds with known MoA
LBDD: ligand-based drug discovery VS: virtual screeningSBDD: structure-based drug discovery MoA: mechanism of actionHTS: High-throughput assay HCS: high-content assays
Cell-based assaysCompound(s) bioactive profiling
based on reference ligand
Cell-based assaysPhenotypic linked to mechanism
Compound profiling based onreference ligand
Cell-based assaysCompound(s) bioactive profiling
HTS and HCS
Cell-based assaysMechanism-based assay
Importance of the cell-based assays
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Applications vary from early drug discovery to development
➢ Phenotypic assays – mechanism-based or not➢ Pharmacodynamics
➢ Mechanism of action
➢ Pharmacokinetics & toxic (ADME-Tox) studies➢ Permeability➢ Metabolism➢ Toxicity
➢ Applications under development: 3D technologies andmicrofluidics to replace animal models
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Context
✓ mTOR: master regulator in physiopathotological processesHosking, R. Cell 2012, 149, 957
✓ Roles in nutrient regulation, life span, cancer growth, etc.Maiese, K.; Molecules to Medicine with mTOR. Academic Press, 2016.
✓ Rapamycin and rapalogs: allosteric inhibitors
Waldner, M.; et al. Br. J. Clin. Pharmacol. 2016, 82, 1158
✓ In this work: competitive inhibitors (ATP binding site)
✓ Like other kinase inhibitors: polypharmacological response
(PI3K and mTOR)Smith, M.C.; et al. Mol Cancer Ther. 2016, 15, 2344
Benjamin, D.; et al.
Nat. Rev. Drug Discov. 2011, 10, 868
ATP
HEAT HEAT FAT FRB Kinase FATC
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Cheminformatics Approach
✓ Database: mTOR and PI3K compounds
✓ Filter analysis with 2D parameters
✓ ROCS model
✓ Docking: (a) PI3K and (b) mTOR
Anchoring hydrogen bonds
eMolecules database(5.9 M)
Filter (756 056)
ROCS(2 996)
HB analysis & Clustering(32)
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Chemical set – main scaffolds
Cytotoxicity study
Cell-based screening
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P C -3
Neq
0437
Neq
0438
Neq
0439
Neq
0440
Neq
0441
Neq
0442
Neq
0443
Neq
0444
Neq
0445
Neq
0446
Neq
0449
Neq
0450
Neq
0451
Neq
0453
Neq
0459
Neq
0460
Neq
0461
Neq
0469
Neq
0470
Neq
0474
Neq
0475
Neq
0476
Neq
0481
Neq
0482
Neq
0490
Neq
0495
Neq
0497
Neq
0498
Neq
0503
Neq
0505
Neq
0506
Rap
am
ycin
Bic
alu
tam
ide
MD
V3100
YM
155
0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
1 1 0
1 2 0
1 3 0
C o m p o u n d s [1 0 0 M ]
% C
ell
via
bil
ity
PC3: metastatic prostate cancer cell
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Cell-based screening
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D U 1 4 5
Neq
0437
Neq
0438
Neq
0439
Neq
0440
Neq
0441
Neq
0442
Neq
0443
Neq
0444
Neq
0445
Neq
0446
Neq
0449
Neq
0450
Neq
0451
Neq
0453
Neq
0459
Neq
0460
Neq
0461
Neq
0469
Neq
0470
Neq
0474
Neq
0475
Neq
0476
Neq
0481
Neq
0482
Neq
0490
Neq
0495
Neq
0497
Neq
0498
Neq
0503
Neq
0505
Neq
0506
Rap
am
ycin
Bic
alu
tam
ide
MD
V3100
YM
155
0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
1 1 0
1 2 0
1 3 0
C o m p o u n d s [1 0 0 M ]
% C
ell
via
bil
ity
DU145: metastatic prostate cancer cell
Cell-based screening
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B a lb -c 3 T 3 c lo n e A 3 1
Neq
0437
Neq
0438
Neq
0439
Neq
0440
Neq
0441
Neq
0442
Neq
0443
Neq
0444
Neq
0445
Neq
0446
Neq
0449
Neq
0450
Neq
0451
Neq
0453
Neq
0459
Neq
0460
Neq
0461
Neq
0469
Neq
0470
Neq
0474
Neq
0475
Neq
0476
Neq
0481
Neq
0482
Neq
0490
Neq
0495
Neq
0497
Neq
0498
Neq
0503
Neq
0505
Neq
0506
Rap
am
ycin
Bic
alu
tam
ide
MD
V3100
YM
155
0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
1 1 0
1 2 0
1 3 0
C o m p o u n d s [1 0 0 M ]
% C
ell
via
bil
ity
Balb-C 3T3 clone A31: mouse fibroblast cell (non-tumorogenic)
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Concentration-response data
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Compound PC-3
EC50 (µM)
Balb/C 3T3
%viability (100 µM)
SI
Neq0438 75.0 (±4.3) 68.1(±8.89) >1.33
Neq0440 60.7(±0.95) 95.4(±9.19) >1.65
Rapamycin 43.1(±0.92) 58.3(±7.00) >2.32
SI = selectivity index
Neq0438 Neq0440
Pathway analysis
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PI3K-AKT-mTOR pathwayPC-3 cells
Rapamycin
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Structural features
25Takeuchi, C.S.; et al. J. Med. Chem. 2013, 56, 2218 Grasso, C.S.; et al. Nat. Med. 2015, 21, 555
Neq0438
XL388mTOR
BuparlisibPI3K, mTOR
logKw
E64 E64d Neq0438 Odanacatib-0.77 0.57 1.6 2.0
Samelyn Martinsunpublished result
Fang, Y.; Eglen, R. M. SLAS Discov. 2017, 22, 456.
The most common methods to produce spheroids
Ultra-lowattachment well
Hanging dropplate
Suspension ina bioreactor
Pilar ormagnetic levitation
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Cytostatic activity
3D (spheroid) cultures for liver (HepG2) andprostate (DU145) cancer cells
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Cytostatic activity
2D and 3D (spheroid) cultures for liver (HepG2) andprostate (DU145) cancer cells
Manuscript in preparation
HepG2 (2D) Resazurin standardization
HepG2 (3D)
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Context
✓ Morus alba extracts is commonly used for menopause
(etnopharmacological use)
✓ Challenge: Lack of standardization of extract is a limitation
and challenge
✓ In this work: study the standardized extracts for the
estrogenic activity
✓ Approach: standardize the extract according to the
estrogenicity using cells (bioguided optimization)
✓ Collaboration USP/UFSCar: Dra. Patrícia Bergo, Prof. Dr.
Moacir Forim
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Hormone replacement therapybased on phytotherapeutic compounds
Poluzzi, E.; et al. F. Curr. Med. Chem. 2014, 21, 417.Menezes, I. R. A. ; Leitão, A. ; Montanari, C. A. . Steroids 2006, 71, 417.
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31Turbolysis (A) and ethanol contant (B) are the most important variables.
Analysis of the yield of the extraction
• main
▪ interactions
Chemometric analysis of the extracts using variables
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Effect of the ethanol &screening of the estrogenic activity
Agonist activity Cytotoxic activity
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Estrogen stimulation for low extracts
Days Days
Days Days
E2
Neg. control
Ethanol content (% v/v)
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Potency of the best extracts
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Analysis of the extracts
RRE = relative response for estrogenicity
No correlation was observed between
Yield of the extract
RR
E (%
)
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Cytotoxicity for extracts with high ethanol content
RRE = relative response for estrogenicity
75% (v/v) ethanol
95% (v/v) ethanol
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Analysis of the extracts for the estrogenic activity
RRE = relative response for estrogenicity
Use of non-estrogenic cell line: MDA-MB 231
Ethanol content (% v/v)
RR
E (%
)
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Standardization of the extract
➢ Quantitative analysis of the following parameters:
• Seazon;
• Sun exposure;
• Time of the day to collect the material;
• Stage of the plant development;
• Raining and humidity;
• Distribution of markers of the plant leaves at different hights
➢ According to ANVISA, it is allowed a variation of theconcentration up to 15% when the active marker is used and20% when it is the analytical marker.
Manuscript in preparation
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Context
✓ Propyl and butylparabens are widely used as food preservatives
✓ These are known estrogenic compounds and could lead to cancer
✓ These chemicals contaminate the environment (water)
✓ Exposition can be harmful to humans
Action
✓ Degradation of parabens by photolysis reaction
✓ Analysis of the bioactivity of the degradation product
PrP BuP
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Kinetics of propylparaben alone and in a mixture
Effect of the pH for propylparaben
Degradation studies
As expected, propyl and butylparabens had almost the same results.
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PrP BuP PrP +BuP NC PC
MCF-7 breast cancer cells are estrogen-dependent
Growth promoted by the activation of estrogenic compounds
Estrogenic profile of the material:
t0 = 50 mM; t1/2 = 20 mM; t1 < 1 mM
Phenotypic cell-based studies linked to mechanism
Degradation of thematerial leads to inactive
compounds for MCF-7
Samples were notcytotoxic for mouse fibroblast cell line
Balb/C3T3 clone A31
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Adhesion of fibroblast cells on a biomaterial
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24 h incubation
Control Chitosan Chitosan +1% laponite
Chitosan +2.5% laponite Chitosan +5% laponite Chitosan +10% laponite
➢ Novel chitosan-modified biomaterial was prepared by Dr. Virginia/Prof. Carla➢ Assays were performed to detect the biocompatibility and adhesion
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Cell-based systems for permeability are commonly used for pharmacokinetisassays
Brief overview of a permeability study
Press, B.; Di Grandi, D.Curr. Drug Metabol. 2008, 9, 893.
Challenges
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❑ Use of primary cellsProblem: heterogeneity
❑ Lack of reproducibility❑ Check your controls!
❑ Importance of good laboratory practices
❑ Live cell imaging
❑ Organ-on-chipSpontaneous contractions in mouse embryonic stem cell–derived cardiomyocytes, transduced with CellLight® Actin-GFP.
Live-cell fluorescence imaging (red and green channels) capturing mitotic division in HeLa cells. Cells were transduced with CellLight® Histone 2B-GFP and Mitochondria RFP.
Live cell imagingOrgans-to-human-on-chip
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Basic references
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Books
Scientific society & MeetingSociedade Brasileira de Biologia Celular (SBBC)Congress of SBBC
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