Using Hybrid Solvent Model to Explore the Bound Ions Effects
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. It is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions because the Ncd and tubulin dimer are highly charged. The widely used implicit solvent models treat ions implicitly in the continuous solvent environment, without focusing on the individual ions’ effects. But the highly charged biomolecules such as the Ncd and tubulin dimer, may capture some ions at the highly charged regions as bound ions. Such bound ions are restricted to their binding sites; thus, they can be treated as part of the biomolecules. It follows that treating the bound ions explicitly may result in more accurate calculations. By applying multi-scale computational methods, including Molecular Dynamics (MD) simulation, machine learning based Hybridizing Ions Treatment-2 (HIT-2) program, DelPhi and DelPhiForce, we studied the interaction between the Ncd motor domain and tubulin dimer using a hybrid solvent model, which considers the bound ions explicitly while the other ions implicitly in the solvent environment. We found that the calculations of the electrostatic features differ significantly between those of the hybrid solvent model and the pure implicit solvent model. The analyses show that treating bound ions at highly charged regions explicitly is crucial for electrostatic calculations. This work proposes a machine learning based approach to handle the bound ions using the hybrid solvent model. Such an approach is not only capable to handle kinesin-tubulin complexes, but also appropriate for other highly charged biomolecules.