How robust is the ligand binding transition state?

For many drug targets, it has been shown that the kinetics of drug binding (e.g. on rate and off rate) is more predictive of drug efficacy than thermodynamic quantities alone. This motivates the development of predictive computational models that can be used to optimize compounds on the basis of their kinetics. The structural details underpinning these computational models are not only found in the bound state, but also in the short-lived ligand binding transition state: the highest free energy point along the (un)binding pathway. Although this transition state cannot be directly observed experimentally, due to its extremely short lifetime, recent successes have demonstrated that modeling of the ligand binding transition state is possible with the help of enhanced sampling methods for molecular dynamics. In our previous work we analyzed the transition state ensemble for an inhibitor of soluble epoxide hydrolase (sEH) with a residence time of 11 minutes. Here we computationally modeled unbinding events for five additional inhibitors of sEH with residence times ranging from 14.25 to 31.75 minutes, with our results recapitulating these experimental residence times to within an order of magnitude. The unbinding ensembles are analyzed in detail, focusing on features of the ligand binding transition state. We find that ligands with similar structures and similar bound poses can show significant differences in their ligand binding transition states, in terms of their spatial location and their interactions with specific protein residues. However we also find similarities across the transition state ensembles when examining more general features such as ligand degrees of freedom. Together these findings show significant challenges for rational, kinetics-based drug design.