Residence time is a well-established concept in drug discovery and the belief that off-rate is more important than affinity has many adherents in both academia and industry. The concept has been articulated as follows in a Nature Reviews in Drug Discovery article:
“Biochemical and cellular assays of drug interactions with their target macromolecules have traditionally been based on measures of drug–target binding affinity under thermodynamic equilibrium conditions. Equilibrium binding metrics such as the half-maximal inhibitory concentration (IC50), the effector concentration for half-maximal response (EC50), the equilibrium dissociation constant (Kd) and the inhibition constant (Ki), all pertain to in vitro assays run under closed system conditions, in which the drug molecule and target are present at invariant concentrations throughout the time course of the experiment [1 | 2 | 3 | 4 | 5]. However, in living organisms, the concentration of drug available for interaction with a localized target macromolecule is in constant flux because of various physiological processes.”
I used to be highly skeptical about the argument that equilibrium binding metrics relevant are not relevant in open systems in which the drug concentration varies with time. The key question for me was always how the rate of change in the drug concentration compares with the rate of binding/unbinding (if the former is slower than the latter then the openness of the in vivo system would seem to be irrelevant). I also used to wonder why an equilibrium binding measurement made in an open system (e.g., Kd from isothermal titration calorimetry) should necessarily be more relevant to the in vivo system than an equilibrium binding measurement made in a series of closed systems (e.g., Ki from an enzyme inhibition assay). Nevertheless, I always needed to balance my concerns against the stark reality that the journal impact factor of Nature Reviews of Drug Discovery is a multiple of my underwhelming h-index.
Any residual doubts about the relevance of residence time completely vanished recently after I examined a manuscript by Prof Maxime de Monne of the Port-au-Prince Institute of Biogerontology who is currently on secondment to the Budapest Enthalpomics Group (BEG). The manuscript has not yet been made publicly available although, with the help of my associate ‘Anastasia Nikolaeva’ in Tel Aviv, I was able to access it and there is no doubt that this genuinely disruptive study will forever change how we use AI to discover new medicines.
Prof de Monne’s study clearly demonstrates that it is possible to manipulate off-rate independently of on-rate and dissociation constant, provided that binding is enthalpically-driven to a sufficient degree. The underlying mechanism is back-propagation of the binding entropy deficit along the reaction coordinate to the transition state region where the resulting unidirectional conformational changes serve to suppress dissociation of the ligand. The math is truly formidable (my rudimentary understanding of Haitian patois didn’t help either) and involves first projecting the atomic isothermal compressibility matrix into the polarizability tensor before applying the Barone-Samedi transformation for hepatic eigenvalue extraction. ‘Anastasia Nikolaeva’ was also able to ‘liberate’ a prepared press release in which a beaming BEG director Prof Kígyó Olaj explains, “Possibilities are limitless now that we have consigned the tedious and needlessly restrictive Principle of Microscopic Reversibility to the dustbin of history".
