In a drug-target binding equilibrium (Eq. A lower K d corresponds to an increased amount of the drug, which in turn suggests a better medicinal effect of the drug candidate but may trigger off-target interactions. The equilibrium dissociation constant ( K d) of a drug-target complex is a major determinant of the concentration or dose of a drug required for sufficient drug-target interaction. Notwithstanding their importance in determining the potency of a drug candidate, the traditional equilibrium binding affinity parameters, such as the dissociation constant ( K d), inhibition constant ( K i), half-maximal inhibitory concentration (IC 50), and effector concentration (EC 50), are arguable in terms of their effectiveness in vivo 3. Our results build a strong foundation for further improvement of our approach by rationalizing the kinetics of ligand unbinding with the thermodynamics of ligand binding.Ĭonventional lead optimization methods in drug development through high-throughput screening rely on biochemical and biophysical assays of drug-target binding affinity under in vitro thermodynamic equilibrium conditions 1, 2. In the experiment, similar sets of residues were found to be in significant contact with both ligands under study. Subsequently, binding pocket hotspot residues that would be important for further computational mutagenesis studies were identified. Additionally, we calculated the thermodynamics of ligand binding in terms of ligand binding energies and the per-residue contribution of the receptor. However, our predictions were many folds shorter than those determined experimentally. We have predicted the absolute ligand residence times on the timescale of seconds. Here, we have implemented an optimized approach of combining the data derived from steered molecular dynamics simulations and the Bell-Evans model to predict the absolute residence times of the antagonist ZMA241385 and agonist NECA that target the A2A adenosine receptor of the G-protein-coupled receptor (GPCR) protein family. Non-equilibrium molecular simulation approaches are proven to be useful in this purpose. Screening drug candidates in terms of their computationally predicted residence times, which is a measure of drug efficacy in vivo, and simultaneously assessing computational binding affinities are becoming inevitable. Recently, academic and industrial scientific communities involved in kinetics-based drug development have become immensely interested in predicting the drug target residence time.
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