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 S ILVA F IGUEIREDO C ELESTINO 1,2 , Elodie L AINE 1 , Pedro Geraldo P ASCUTTI 2 and Luba T CHERTANOV 1 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 Receptor Tyrosine Kinase III (RTK III) Hubbard et al ., 2004 • PDGFR- α / β • KIT • FLT3 • CSF1-R Ligand-induced dimerization Inactive Active CSF1-R  overexpressed in several types of tumors (e.g. breast, uterine) and inflamatory diseases: ( Alzheimer’s , arthritis, ...) 2/20 Hamilton et al ., 2008

CSF-1R: intracellular domain Autoinhibited Juxtamenbrane domain (JMR):  JM-B (buried) JM-S (switch) JM-Z JM-Z (zipper) Tyrosine kinase domain (TKD):  N-lobe and hinge : nucleotide/inhibitor binding  JM-B Glycine rich nucleotide binding loop (P-loop)  Pseudo JM-S C-lobe : substrate binding and catalysis  KID Kinase insert domain (KID)  Activation loop (A-loop):  DFG motif > “on/off” states Catalytic loop  JMR N-lobe Hinge A-loop C-lobe 3/20

Equivalent Activating mutations A-loop Imatinib Kinase Cancer types References mutations resistance AML, KIT D816 V‡/H/Y mastocytosis and yes [1-3] germ cell tumors FLT3 D835 /Y ‡ /V/H/E/N AML, MDS, ALL no [4] PDGFR- α D842 V‡ 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 a l., 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) 4/20 Kufareva et al ., 2008

Transition between inactive and active states CSF-1R structural transition Inactive Active Autoinhibited PDB: 2OGV PDB: 3LCD DFG D802 Y561;809 D802V JMR N-lobe Hinge A-loop + C-lobe 5/20 Y809 binds as a pseudo-substrate

Methods: Molecular representation Force field Non-bonded interactions Bonded interactions 6/20

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 7/20

Methods: Molecular Dynamics Trajectory analysis Production run Energy minimization Equilibration run Velocities assignment Newton’s equation of movement (leapfrog algorithm ) 8/20

KIT D816V/H structural outcome D816V Laine et al ., 2011 9/20 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? 10/20

Methods: Molecular Dynamics setup MD: Wild type analyses Merge (x2) 50ns D802V -5ns initials 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; Principal Component Berendsen pressure Analysis (PCA) coupling; V-rescale thermostat PME treatment for JMR free energy of binding eletrostatic interactions (GBSA) Electrostatic surface profile 11/20

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

Secondary structure assessment A-loop D802 WT DFG Y809 W821 D802V WT D802V 13/20

Secondary structure assessment JMR Y546 Y571 WT D565 Y561 D802V Y566 Strengthening of the beta-sheets 14/20 Laine et al ., 2011

Principal Component Analyses (PCA) 1 0,9 0,8 Eigenvalues (nm²) 0,7 0,6 0,5 D802V WT 0,4 0,3 D802V 0,2 0,1 0 1 2 3 4 5 6 7 8 9 10 Eigenvector index overlap WT *C-alpha ; KID not taken in consideration 1 o eigenvector 15/20 WT D802V – MD frames D802V

Hydrogen bond prevalence wild D802V E633 E633 Y546 R801 Y546 R801 D778 D778 Y809 Y809 Hydrogen bond Wild D802V 15,26 ns 23,53 ns Prevalence (%) Y546 E633 81.97 18.84 Y809 D778 82.08 42.02 E633 R801 D778 17.35 81.58 E633 Y546 Y546 R801 R801 D778 D778 Y809 Y809 16/20 49,39 ns 40,67 ns

JMR – TKD attachment Thermodynamic cycle Δ Δ G bind [WT-MU] = -8.81 – (+24.63) Δ Δ G bind [WT-MU] =-33.44 kcal/mol JMR is more tightly attached in the WT than in the MU **KIT Δ Δ G bind [WT-MU] = -42.68 kcal/mol Computed on equilibrated conformations Track of the center-of-mass distances JM-B – N-lobe JM-S – C-lobe 17/20

JMR sequence divergence CSF1-R JM-B JM-S CSF1R ---KPKYQVRWKIIESYEGNSYTFI KIT YLQKPMYEVQWKVVEEINGNNYVYI JM-B/JM-S Polar (+) (-) Apolar composition uncharged CSF1R 4 2 9 7 KIT 2 3 10 10 KIT The electrostatic profile of the protein surfaces shows a strong charge complementarity between CSF-1R JMR and the TKD 180 o 18/20 TKD JMR

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 of novel rational drug-design strategy for cancer treatment. 19/20

Acknowledgments ByMoDyM- LBPA (France) Funding Luba Tchertanov ENS Cachan, France Elodie Laine CNPq, Brazil 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