Abstract
ROS1 fusion kinase—highly expressed in a variety of human cancers—has emerged as an important and attractive target for anticancer drug design. Crizotinib, a well-known drug approved by the FDA as an ALK inhibitor to treat advanced NSCLC, also shows potent inhibitoy activity against ROS1. However, the development of serious resistance due to secondary mutations has been observed in clinical studies. To provide insight into the mechanisms of this drug resistance, molecular dynamics simulations and free-energy calculations were carried out for complexes of crizotinib with wild-type (WT) ROS1 as well as the mutated L2026M and G2032R forms. MD simulations indicated that the L2026M and G2032R systems are slightly less flexible than the WT system. Binding free energy calculations showed that the L2026M and G2032R mutations significantly reduce the binding affinity of crizotinib for ROS1, and that the resistance to crizotinib caused by the L2026M and G2032R mutations arises mostly from increases in entropic terms. Furthermore, calculations of per-residue binding free energies highlighted increased and decreased contributions of some residues in the L2026M and G2032R systems relative to those in the WT system. The present study therefore yielded detailed insight into the mechanisms of resistance to crizotinib caused by the L2026M and G2032R mutations, which should provide the basis for rational drug design to combat crizotinib resistance.
Superposition of the average structures obtained from the last 10 ns of the molecular dynamics simulation trajectoriy for WT (green) and mutated ROS1 (cyan)
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References
Ou SH, Tan J, Yen Y, Soo RA (2012) ROS1 as a ‘druggable’ receptor tyrosine kinase: lessons learned from inhibiting the ALK pathway. Expert Rev Anticancer Ther 12(4):447–456
Shaw AT, Camidge DR, Engelman JA, Solomon BJ, Kwak EE, Clark JW, Salgia R, Shapiro G, Bang YJ, Tan W, Tye L, Wilner KD, Stephenson P, Varella-Garcia M, Bergethon K, Iafrate AJ, Ou SH (2012) ROS1 rearrangements define a unique molecular class of lung cancers. J Clin Oncol 30(8):863–870
Awad MM, Katayama R, McTigue M, Liu W, Deng YL, Brooun A, Friboulet L, Huang D, Falk MD, Timofeevski S, Wilner KD, Lockerman EL, Khan TM, Mahmood S, Gainor JF, Digumarthy SR, Stone JR, Mino-Kenudson M, Christensen JG, Iafrate AJ, Engelman JA, Shaw AT (2013) Acquired resistance to crizotinib from a mutation in CD74–ROS1. N Engl J Med 368(25):2395–2401
Gainor JF, Shaw AT (2013) Emerging paradigms in the development of resistance to tyrosine kinase inhibitors in lung cancer. J Clin Oncol 31(31):3987–3996
Zou HY, Li Q, Engstrom LD, West M, Appleman V, Wong KA, McTigue M, Deng YL, Liu W, Brooun A, Timofeevski S, McDonnell SRP, Jiang P, Falk MD, Lappin PB, Affolter T, Nichols T, Hu W, Lam J, Johnson TW, Smeal T, Charest A, Fantin VR (2015) PF-06463922 is a potent and selective next-generation ROS1/ALK inhibitor capable of blocking crizotinib-resistant ROS1 mutations. Proc Natl Acad Sci USA 112(11):3493–3498
Sun H, Li Y, Tian S, Wang J, Hou T (2014) P-loop conformation governed crizotinib resistance in G2032R-mutated ROS1 tyrosine kinase: clues from free energy landscape. PLoS Comput Biol 10(7):e1003729
Davare MA, Vellore NA, Wagner JP, Eide CA, Goodman JR, Drilon A, Deininger MW, Ohare T, Druker BJ (2015) Structural insight into selectivity and resistance profiles of ROS1 tyrosine kinase inhibitors. Proc Natl Acad Sci USA 112(39):E5381–E5390
Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22:195–201
Frisch M, Trucks G, Schlegel H, Scuseria G, Robb M, Cheeseman J, Montgomery J Jr, Vreven T, Kudin K, Burant J (2004) Gaussian 03. Gaussian, Inc., Wallingford
Bayly CI, Cieplak P, Cornell W, PKollman PA (1993) A well behaved electrostatic potential based method using charge restraints for deriving atomic charges: the RESP model. J Phys Chem 97:10269–10280
Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general Amber force field. J Comput Chem 25:1157–1174
Hornak V, Abel R, Okur A, Strockbine B, Roitberg A, Simmerling C (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins Struct Funct Bioinf 65:712–725
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935
Case DA, Darden TA, Cheatham TE III, Simmerling CL, Wang J, Duke RE, Luo R, Walker RC, Zhang W, Merz KM, Roberts B, Hayik S, Roitberg A, Seabra G, Swails J, Goetz AW, Kolossváry I, Wong KF, Paesani F, Vanicek J, Wolf RM, Liu J, Wu X, Brozell SR, Steinbrecher T, Gohlke H, Cai Q, Ye X, Wang J, Hsieh MJ, Cui G, Roe DR, Mathews DH, Seetin MG, Salomon-Ferrer R, Sagui C, Babin V, Luchko T, Gusarov S, Kovalenko A, Kollman PA (2012) AMBER 12. University of California, San Francisco
Salomon-Ferrer R, Götz AW, Poole D, Le Grand S, Walker RC (2013) Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald. J Chem Theory Comput 9:3878–3888
Wu X, Wan S, Wang G, Jin H, Li Z, Tian Y, Zhu Z, Zhang J (2015) Molecular dynamics simulation and free energy calculation studies of kinase inhibitors binding to active and inactive conformations of VEGFR-2. J Mol Graph Model 56:103–112
Darden T, York D, Pedersen L (1993) Particle mesh Ewald: an N·log-(N) method for Ewald sums in large systems. J Chem Phys 98:10089–10092
Ryckaert JP, Ciccotti G, Berendsen HJC (1977) Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23:327–341
Rocchia W, Alexov E, Honig B (2001) Extending the applicability of the nonlinear Poisson–Boltzmann equation: multiple dielectric constants and multivalent ions. J Phys Chem B 105:6507–6514
Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized Born model. Proteins Struct Funct Bioinf 55:383–394
Acknowledgements
We acknowledge the financial support provided by the National Natural Science Foundation of China (no. 81202413 and 81573263) and the National Natural Science Foundation of Guangdong, China (no. 2015A030313285). We also express our thanks to the Supercomputing Center of the Chinese Academy of Science for allowing us to use the scientific computing grid (ScGrid).
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Wu, X., Fu, Y., Wang, Y. et al. Gaining insight into crizotinib resistance mechanisms caused by L2026M and G2032R mutations in ROS1 via molecular dynamics simulations and free-energy calculations. J Mol Model 23, 141 (2017). https://doi.org/10.1007/s00894-017-3314-z
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DOI: https://doi.org/10.1007/s00894-017-3314-z