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A computational study of three frequent mutations of EGFR and their effects on protein dimer formation and non-small cell lung cancer drug resistance
Abstract
Drug resistance is a major problem for non-small cell lung cancer (NSCLC) treatment due to mutations in patients’ DNA sequences. It is now possible to obtain the human genome information easily based on the high-throughput sequencing technology, so personalized medicine can become a reality.
Based on mutation data of 168 patients with stage IIIB and IV NSCLC. We use computational method to predict the homo-dimers and hetero-dimers formation and compute the binding free energy of complexes (between drugs and proteins). For the gefitinib and erlotinib as two common drugs used in patient's therapy, we compute the possible 3D structure of epidermal growth factor receptor (EGFR) mutant- inhibitor complex. Rosetta and Amber are used for molecular dynamics analysis and simulation. The PRISM protocol is used to predict the binding energy based on similar protein-protein interaction surfaces. Multiple factors, including the mutant proteins surface geometry change, the number of hydrogen bonds change and the electronic change of the surface, are taken into account when in evaluating the binding free energy.
Our results suggest that the mutation position is very important for dimer formation and it affects the drug’s binding strength with EGFR. Mutations such as L858R and T790M which do not happen on the protein interaction surface can hardly affect the formation of dimers. Patients with the delE746_A750 mutation can obtain a good therapy by using gefitinib instead of erlotinib. By comparing the binding free energy to form a homo- or heterodimers, we find that the L858R mutant will incline to form a hetero-dimer rather than a homo-dimer.
Keywords: Dimer formation, EGFR, drug resistance, mutation, hetero-dimer, homo-dimer.
Results
Figure 1. The relationship between mutation types of patients with progression-free survival (PFS) time under different drug therapy. (A) Three major mutation types (L858R: 19 man cases, 49 woman cases, delE746_A750: 7 man cases, 23 woman cases, delL747_P753insS: 4 man cases, 4 woman cases) of patients with gefitinib therapy. (B) Three major mutation types (L858R: 5 man cases, 7 woman cases, delE746_A750: 6 man cases, 2 woman cases, delL747_P753insS: 1 man case, 1 woman case) of patients with erlotinib therapy. We can see that patients who use gefitinib can have a long PFS time than those patients who use erlotinib.
Table 1. Hetero-dimer affinity prediction results by PRISM based on 2jitAB template.
| Part1 | Part2 | Binding free energy | Dimer type |
|---|---|---|---|
| 2ity | equil_T790M.pdb | -96.48 | ERBB1/ERBB1 |
| 3pp0 | equil_L858R.pdb | -80.35 | ERBB1/ERBB2 |
| 2ity | equil_L858R.pdb | -75.93 | ERBB1/ERBB1 |
| 2ity | equil_T790M_L858R.pdb | -74.74 | ERBB1/ERBB1 |
| 2ity | equil_L858R_T790M_V948R.pdb | -68.81 | ERBB1/ERBB1 |
| 3pp0 | equil_V948R.pdb | -63.22 | ERBB1/ERBB2 |
| dell | equil_T790M_L858R.pdb | -62.19 | ERBB1/ERBB1 |
| 2ity | equil_V948R.pdb | -55.98 | ERBB1/ERBB1 |
| 3bce | equil_T790M_L858R.pdb | -53.63 | ERBB1/ERBB4 |
| 3pp0 | equil_T790M_L858R.pdb | -48.74 | ERBB1/ERBB2 |
| 3pp0 | equil_T790M.pdb | -50.77 | ERBB1/ERBB2 |
Table 2. Hydrogen bond distribution in each dimer structure.
Methods
Figure 2. The flowchart of our computational method.
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