Tyrosine Kinase Receptor Priscila DA S ILVA F IGUEIREDO C ELESTINO - - PowerPoint PPT Presentation

Impact of the D802V Mutation on the Structure and Dynamics of the CSF-1R Tyrosine Kinase Receptor

Priscila DA SILVA FIGUEIREDO CELESTINO1,2, Elodie LAINE1 , Pedro Geraldo PASCUTTI2 and Luba TCHERTANOV1

1 ByMoDyM, LBPA, CNRS, École Normale Superiéure de Cachan, France.

2 LMDM, Instituto de Biofísica Carlos Chagas Filho (IBCCF), Universidade Federal do Rio de Janeiro (UFRJ), Brazil.

{pdasilva@lbpa.ens-cachan.fr}

UFRJ IBCCF

Biological context

Hubbard et al., 2004

Inactive Ligand-induced dimerization Active

• PDGFR-α/β
• KIT
• FLT3
• CSF1-R

Receptor Tyrosine Kinase III (RTK III) CSF1-R

• overexpressed in several types of tumors

(e.g. breast, uterine) and inflamatory diseases: (Alzheimer’s , arthritis, ...)

Hamilton et al., 2008 2/20

CSF-1R: intracellular domain



Juxtamenbrane domain (JMR): JM-B (buried) JM-S (switch) JM-Z (zipper)



Tyrosine kinase domain (TKD):



N-lobe and hinge: nucleotide/inhibitor binding



Glycine rich nucleotide binding loop (P-loop)



C-lobe: substrate binding and catalysis

• Kinase insert domain (KID)
• Activation loop (A-loop):

DFG motif > “on/off” states

• Catalytic loop

Autoinhibited Pseudo KID

N-lobe C-lobe Hinge JMR A-loop

JM-B JM-S JM-Z

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Equivalent Activating mutations

Kinase A-loop mutations Cancer types Imatinib resistance References KIT D816V‡/H/Y AML, mastocytosis and germ cell tumors yes [1-3] FLT3 D835 /Y‡/V/H/E/N AML, MDS, ALL no [4] PDGFR-α D842V‡ GIST yes [5] PDGFR-β no data no data no data no data CSF-1R D802V * yes [6-7]

‡ Most common single-amino-acid changes AML = Acute myelogenous leukemia MDS = Myelodysplastic sydrome ALL = Acute lymphoblastic leukemia GIST = Gastrointestinal tumors * Not commonly mutated

1. Piao et al., Proc. Natl. Acad. Sci. U. S. A. 93, 14665-14669 (1996) 2. Tian et al., Am. J. Pathol. 154, 1643-1647 (1999) 3. Chian et al., Blood 98, 1365-1373 (2001) 4. Yamamoto et al., Blood 87, 2434-2439 (2001) 5. Corless et al., J. Clin. Oncology 23, 5357-5364 (2005) 6. Morley et al., Oncogene 18, 3076-3084 (1999) 7. Taylor et al., Oncogene 25, 147-151 (2005)

Kufareva et al., 2008

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Transition between inactive and active states

Inactive Autoinhibited Active PDB: 2OGV PDB: 3LCD

N-lobe C-lobe Hinge JMR A-loop D802 Y561;809

Y809 binds as a pseudo-substrate DFG

CSF-1R structural transition

D802V +

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Methods: Molecular representation

Bonded interactions Non-bonded interactions Force field

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Methods: Why Molecular Mechanics ?

Quantum Mechanics simulations are computationally expensive and not feasible for large number of atoms; Intra and inter-atomic interactions can be calculated by analytical potentials adjusted to energy curves obtained by quantum mechanics calculations. Ex: At room temperature, harmonic potentials approximates well to the Morse potential, that describes the chemical bonds

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Methods: Molecular Dynamics

Energy minimization Velocities assignment Newton’s equation of movement Equilibration run Production run Trajectory analysis (leapfrog algorithm)

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KIT D816V/H structural outcome

D816V

Laine et al., 2011 Chauvot de Beauchêne et al. 2012

Questions

• As CSF1-R is not commonly mutated on cancer, what would be

the structural effects of such mutation?

• As being the member of RTK III more closely related to KIT, the

results are expected to be comparable?

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Methods: Molecular Dynamics setup

Wild type D802V

MD: Merge (x2) 50ns

• 5ns initials

analyses

Model building Production runs Analyses

Modeller v9.8 GROMACS package Protein stability Repare the WT (PDB ID: 2OGV) AMBER99sb force field Secondary structure assessment D802V point mutation PBC; TIP3P water; cubic box Hydrogen bond prevalence 310 K; 1bar; 2fs time step; Berendsen pressure coupling; V-rescale thermostat Principal Component Analysis (PCA) PME treatment for eletrostatic interactions JMR free energy of binding (GBSA) Electrostatic surface profile

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Protein stability

Loop between β3 and helix-C A-loop JMR wild D802V 12/20

Secondary structure assessment

D802 Y809 W821 DFG WT D802V WT D802V

A-loop

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Secondary structure assessment

Y546 Y566 Y561 D565 Y571

WT D802V Laine et al., 2011

JMR

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Strengthening of the beta-sheets

Principal Component Analyses (PCA)

*C-alpha ; KID not taken in consideration WT D802V WT D802V D802V – MD frames

• verlap

1o eigenvector

15/20 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 1 2 3 4 5 6 7 8 9 10 Eigenvalues (nm²) Eigenvector index WT D802V

Hydrogen bond prevalence

15,26 ns 23,53 ns 40,67 ns 49,39 ns

Y546 E633 R801 Y809 D778 Y546 E633 R801 Y809 D778 Y546 E633 R801 Y809 D778 Y546 E633 R801 Y809 D778

wild D802V

Hydrogen bond Prevalence (%) Wild D802V Y546 E633 81.97 18.84 Y809 D778 82.08 42.02 R801 D778 17.35 81.58 16/20

JMR –TKD attachment

Computed on equilibrated conformations

JM-B – N-lobe JM-S – C-lobe

Δ ΔGbind[WT-MU] = -8.81 –(+24.63) Δ ΔGbind[WT-MU] =-33.44 kcal/mol

JMR is more tightly attached in the WT than in the MU **KIT Δ ΔGbind[WT-MU] = -42.68 kcal/mol Track of the center-of-mass distances

Thermodynamic cycle

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JMR sequence divergence

JM-B/JM-S composition (+) (-) Polar uncharged Apolar CSF1R 4 2 9 7 KIT 2 3 10 10

JM-B JM-S

CSF1R ---KPKYQVRWKIIESYEGNSYTFI KIT YLQKPMYEVQWKVVEEINGNNYVYI 180o

TKD JMR

CSF1-R KIT The electrostatic profile of the protein surfaces shows a strong charge complementarity between CSF-1R JMR and the TKD

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Conclusions and perspectives

• The sequence variability of the JMR in type III RTKs is associated with differential

impacts of the equivalent resistant mutations on the structure and dynamics of the receptors;

• The more subtle effects of D802V mutation on the JMR of CSF-1R compared to

D816V/H of KIT could be the sign of a less efficient activating role of CSF-1R D802V compared to KIT D816V/H, as CSF-1R is not commonly found mutated in cancer;

• Further analysis should be performed to investigate the role of the mutation in the

resistance to Imatinib;

• MD simulations on FLT3 and PDGFR-α structures are currently in progress;
• Our future goal is to gather the results for these members of RTK III in order to

relate the differences in sequence and structure with the dynamics and function of this receptor family;

• Structural comparison inside the family can provide insights into the development
• f novel rational drug-design strategy for cancer treatment.

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Acknowledgments

ByMoDyM- LBPA (France) Luba Tchertanov Elodie Laine Manuela Leal da Silva Isaure Chauvot de Beauchêne Priscila da S. Figueiredo Celestino Florent Langenfeld Rohit Arora Samuel Demarest Loic Etheve LMDM – IBCCF (Brazil) Pedro G. Pascutti Funding ENS Cachan, France CNPq, Brazil