Exploring the Impact of Protein Chain Selection in Binding Energy Calculations with DFT.

Calculation of binding free energies between a protein and a ligand are highly desired for computer-aided drug design. Here we approximate the binding energies of ABL1, an enzyme which is the target for drugs used in the treatment of chronic myeloid leukaemia, with minimal models and density functional theory (DFT). Starting from the crystal structures of protein-drug complexes, we estimated the binding free energies having used all available individual molecules (protein chains) within each structure, not only a single one as commonly used, in order to see if the choice of the protein chain is important in such calculations. Differences were observed between chains in the same file. Energy decomposition analysis (EDA) revealed that the most important factors for binding were exchange, repulsion and electrostatics. The desolvation term varied dramatically between the inhibitors (between 4.2 and 92.3 kcal/mol). All functionals showed similar patterns in the EDA and in discriminating between the ligands. Non-covalent interactions (NCI) analysis was used to further explain the differences between protein chains and functionals. Overall, it is shown that small minimal models of a drug binding site can be useful to infer on the suitability of an initial crystal structure for further analysis such as EDA.