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.