Free energy landscape for the binding process of Huperzine A to acetylcholinesterase

Drug-target residence time (t = 1/k_off, where k_off is the dissociation rate constant) has become an important index in discovering betteror best-in-class drugs. However, little effort has been dedicated to developing computational methods that can accurately predict this kinetic parameter or related parameters, k_off and activation free energy of dissociation (ΔG_off^≠). In this paper, energy landscape theory that has been developed to understand protein folding and function is extended to develop a generally applicable computational framework that is able to construct a complete ligand-target binding free energy landscape. This enables both the binding affinity and the binding kinetics to be accurately estimated.We applied this method to simulate the binding event of the anti-Alzheimer's disease drug (-)-Huperzine A to its target acetylcholinesterase (AChE). The computational results are in excellent agreement with our concurrent experimental measurements. All of the predicted values of binding free energy and activation free energies of association and dissociation deviate from the experimental data only by less than 1 kcal/mol. The method also provides atomic resolution information for the (-)-Huperzine A binding pathway, which may be useful in designing more potent AChE inhibitors. We expect thismethodology to be widely applicable to drug discovery and development.