Binding Affinity via Docking: Fact and Fiction

Abstract

In 1982, Kuntz et al. published an article with the title “A Geometric Approach to Macromolecule-Ligand Interactions”, where they described a method “to explore geometrically feasible alignment of ligands and receptors of known structure”. Since then, small molecule docking has been employed as a fast way to estimate the binding pose of a given compound within a specific target protein and also to predict binding affinity. Remarkably, the first docking method suggested by Kuntz and colleagues aimed to predict binding poses but very little was specified about binding affinity. This raises the question as to whether docking is the right tool to estimate binding affinity. The short answer is no, and this has been concluded in several comprehensive analyses. However, in this opinion paper we discuss several critical aspects that need to be reconsidered before a reliable binding affinity prediction through docking is realistic. These are not the only issues that need to be considered, but they are perhaps the most critical ones. We also consider that in spite of the huge efforts to enhance scoring functions, the accuracy of binding affinity predictions is perhaps only as good as it was 10–20 years ago. There are several underlying reasons for this poor performance and these are analyzed. In particular, we focus on the role of the solvent (water), the poor description of H-bonding and the lack of the systems’ true dynamics. We hope to provide readers with potential insights and tools to overcome the challenging issues related to binding affinity prediction via docking.

Evaluating kratom alkaloids using PHASE

“…Despite recent advances, molecular docking models often fail to accurately relate docking scores to experimental observables (e.g. binding affinity) due to methodological limitations such as the lack of active site dynamics, poorly described solvent interactions, and a crude description of hydrogen bonding [45]. However, the mu opioid regression model was able to correctly relate key modifications of the fentanyl core to experimentally measured binding affinity with r = 0.86 for eight congeners [1].…”

Synthesis, Molecular Docking and Antimicrobial Activity of α, β‐Unsaturated Ketone Exchange Moiety for Chalcone and Pyrazoline Derivatives

“…[51] Hydrogen bond strength contributed significantly to increase binding affinity between protein and target molecules. [52] Unsubstituted compounds 1 a, 1 d, 3 a and 3 d were chosen for molecular docking interaction to demonstrate the effect of unsaturated keto exchange towards biological activity ( Table 1). S. aureus N-terminal domain of DNA binding protein (PDB entry: 4pql) was utilized as a receptor to evaluate the binding interaction with 1 a, 1 d, 3 a and 3 d.…”

Understanding the Hsp90 N-Terminal Dynamics: Structural and Molecular Insights into the Therapeutic Activities of Anticancer Inhibitors Radicicol (RD) and Radicicol Derivative (NVP-YUA922)

“…The IC50 is not a direct indicator of affinity, although the indirectly related to confirm that NVP has more potency towards Hsp90 compared to RD. Entropy effects play an important role in drug-target interactions, but the entropic contribution to ligand-binding affinity is often omitted by endpoint binding free energy calculation methods such as MM/GBSA and MM/PBSA due to the high computational expense of normal mode analysis (NMA) [57,58]. The binding free energies estimated by including the truncated-NMA entropies based on the MD trajectories have been reported to give the lowest average absolute deviations against the experimental data among all the tested strategies for both MM/GBSA and MM/PBS [57,58].…”