Rapid and accurate ranking of binding affinities of epidermal growth factor receptor sequences with selected lung cancer drugs

The epidermal growth factor receptor (EGFR) is a major target for drugs in treating lung carcinoma. Mutations in the tyrosine kinase domain of EGFR commonly arise in human cancers, which can cause drug sensitivity or resistance by influencing the relative strengths of drug and ATP-binding. In this study, we investigate the binding affinities of two tyrosine kinase inhibitors—AEE788 and Gefitinib—to EGFR using molecular dynamics simulation. The interactions between these inhibitors and the EGFR kinase domain are analysed using multiple short (ensemble) simulations and the molecular mechanics/Poisson–Boltzmann solvent area (MM/PBSA) method. Here, we show that ensemble simulations correctly rank the binding affinities for these systems: we report the successful ranking of each drug binding to a variety of EGFR sequences and of the two drugs binding to a given sequence, using petascale computing resources, within a few days.

[1]  M. Eck,et al.  Structural and mechanistic underpinnings of the differential drug sensitivity of EGFR mutations in non-small cell lung cancer. , 2010, Biochimica et biophysica acta.

[2]  C. Peschel,et al.  Functional Analysis of Epidermal Growth Factor Receptor (EGFR) Mutations and Potential Implications for EGFR Targeted Therapy , 2009, Clinical Cancer Research.

[3]  John Kuriyan,et al.  Activation of tyrosine kinases by mutation of the gatekeeper threonine , 2008, Nature Structural &Molecular Biology.

[4]  Lirong Chen,et al.  Mapping the Binding Site of a Large Set of Quinazoline Type EGF-R Inhibitors Using Molecular Field Analyses and Molecular Docking Studies. , 2003 .

[5]  Trent E Balius,et al.  Quantitative prediction of fold resistance for inhibitors of EGFR. , 2009, Biochemistry.

[6]  Gennady Verkhivker,et al.  Hierarchical Modeling of Activation Mechanisms in the ABL and EGFR Kinase Domains: Thermodynamic and Mechanistic Catalysts of Kinase Activation by Cancer Mutations , 2009, PLoS Comput. Biol..

[7]  Wilfred F. van Gunsteren,et al.  Validation of molecular dynamics simulation , 1998 .

[8]  A. Jemal,et al.  Global Cancer Statistics , 2011 .

[9]  C. Sawyers,et al.  Targeted cancer therapy , 2004, Nature.

[10]  P. Kollman,et al.  Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate−DNA Helices , 1998 .

[11]  A. Voter,et al.  Chapter 4 Accelerated Molecular Dynamics Methods: Introduction and Recent Developments , 2009 .

[12]  L. Byers,et al.  Dual targeting of the vascular endothelial growth factor and epidermal growth factor receptor pathways: rationale and clinical applications for non-small-cell lung cancer. , 2007, Clinical lung cancer.

[13]  Peter V. Coveney,et al.  Real science at the petascale , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[14]  Peter V Coveney,et al.  Peptide recognition by the T cell receptor: comparison of binding free energies from thermodynamic integration, Poisson–Boltzmann and linear interaction energy approximations , 2005, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[15]  Peter V. Coveney,et al.  Virtualizing access to scientific applications with the Application Hosting Environment , 2009, Comput. Phys. Commun..

[16]  Benjamin Haibe-Kains,et al.  Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials. , 2010, The Lancet. Oncology.

[17]  Wei Zhang,et al.  A point‐charge force field for molecular mechanics simulations of proteins based on condensed‐phase quantum mechanical calculations , 2003, J. Comput. Chem..

[18]  M. Meyerson,et al.  The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP , 2008, Proceedings of the National Academy of Sciences.

[19]  Peter V Coveney,et al.  Patient-specific simulation as a basis for clinical decision-making , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[20]  P. Coveney,et al.  HIV decision support: from molecule to man , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[21]  F. Da Settimo,et al.  Computational studies of epidermal growth factor receptor: docking reliability, three-dimensional quantitative structure-activity relationship analysis, and virtual screening studies. , 2009, Journal of medicinal chemistry.

[22]  L. Wodicka,et al.  A small molecule–kinase interaction map for clinical kinase inhibitors , 2005, Nature Biotechnology.

[23]  Holger Gohlke,et al.  The Amber biomolecular simulation programs , 2005, J. Comput. Chem..

[24]  Michael Andrec,et al.  A large data set comparison of protein structures determined by crystallography and NMR: Statistical test for structural differences and the effect of crystal packing , 2007, Proteins.

[25]  N. Gray,et al.  Targeting cancer with small molecule kinase inhibitors , 2009, Nature Reviews Cancer.

[26]  A. Takaoka,et al.  Comparing antibody and small-molecule therapies for cancer , 2006, Nature Reviews Cancer.

[27]  J. Ferlay,et al.  Global Cancer Statistics, 2002 , 2005, CA: a cancer journal for clinicians.

[28]  Junmei Wang,et al.  Development and testing of a general amber force field , 2004, J. Comput. Chem..

[29]  Jacques G. Amar,et al.  Accelerated molecular dynamics methods: introduction and recent developments , 2009 .

[30]  G. Scuseria,et al.  Gaussian 03, Revision E.01. , 2007 .

[31]  Daniel A. Haber,et al.  Epidermal growth factor receptor mutations in lung cancer , 2007, Nature Reviews Cancer.

[32]  P A Kollman,et al.  Continuum solvent studies of the stability of RNA hairpin loops and helices. , 1998, Journal of biomolecular structure & dynamics.

[33]  Gennady Verkhivker,et al.  Computational modeling of structurally conserved cancer mutations in the RET and MET kinases: the impact on protein structure, dynamics, and stability. , 2009, Biophysical journal.

[34]  R. Dror,et al.  A conserved protonation-dependent switch controls drug binding in the Abl kinase , 2009, Proceedings of the National Academy of Sciences.

[35]  G.Ch,et al.  In-silico Interaction Studies of Quinazoline Derivatives for their Inhibitory Action on Both Wild and Mutant EGFRs , 2009 .

[36]  Peter V Coveney,et al.  Modelling biological complexity: a physical scientist's perspective , 2005, Journal of The Royal Society Interface.

[37]  Matthew Meyerson,et al.  Structures of lung cancer-derived EGFR mutants and inhibitor complexes: mechanism of activation and insights into differential inhibitor sensitivity. , 2007, Cancer cell.

[38]  Peter V. Coveney,et al.  Accurate Ensemble Molecular Dynamics Binding Free Energy Ranking of Multidrug-Resistant HIV-1 Proteases , 2010, J. Chem. Inf. Model..

[39]  John Kuriyan,et al.  An Allosteric Mechanism for Activation of the Kinase Domain of Epidermal Growth Factor Receptor , 2006, Cell.

[40]  Peter V. Coveney,et al.  Automated Molecular Simulation Based Binding Affinity Calculator for Ligand-Bound HIV-1 Proteases , 2008, J. Chem. Inf. Model..

[41]  M. Karplus,et al.  Locally accessible conformations of proteins: Multiple molecular dynamics simulations of crambin , 1998, Protein science : a publication of the Protein Society.

[42]  J. Mestan,et al.  AEE788: a dual family epidermal growth factor receptor/ErbB2 and vascular endothelial growth factor receptor tyrosine kinase inhibitor with antitumor and antiangiogenic activity. , 2004, Cancer research.

[43]  Giulio Rastelli,et al.  Fast and accurate predictions of binding free energies using MM‐PBSA and MM‐GBSA , 2009, J. Comput. Chem..

[44]  Gennady Verkhivker,et al.  Exploring sequence-structure relationships in the tyrosine kinome space: functional classification of the binding specificity mechanisms for cancer therapeutics , 2007, Bioinform..

[45]  K Schulten,et al.  VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.

[46]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[47]  A. Ullrich,et al.  Smart drugs: tyrosine kinase inhibitors in cancer therapy. , 2002, Cancer cell.

[48]  Jian Hui Wu,et al.  Impact of EGFR point mutations on the sensitivity to gefitinib: Insights from comparative structural analyses and molecular dynamics simulations , 2006, Proteins.

[49]  Peter V Coveney,et al.  Rapid and accurate prediction of binding free energies for saquinavir-bound HIV-1 proteases. , 2008, Journal of the American Chemical Society.