Improving the preclinical and clinical success rates of LMW drugs depends on radical revisions to the status quo scientific foundations of medicinal chemistry: a case study on COVID Mproinhibition

Abstract

AbstractThe poor preclinical and clinical success rates of low molecular weight (LMW) compounds can be partially attributed to the inherent trial-and-error nature of pharmaceutical research, which is limited largely toretrospectivedata-driven, rather thanprospectiveprediction-driven human relevant workflows stemming from: 1) inadequate scientific understanding of structure-activity, structure-property, and structure-free energy relationships; 2) disconnects between empirical models derived from in vitro equilibrium data (e.g., Hill and Michaelis-Menten models) vis-à-vis the native non-equilibrium cellular setting (where the pertinent metrics consist of rates, rather than equilibrium state distributions); and 3) inadequate understanding of the non-linear dynamic (NLD) basis of cellular function and disease. We argue that the limit of understanding of cellular function/dysfunction and pharmacology based onempiricalprinciples (observation/inference) has been reached, and that further progress depends on understanding these phenomena at thefirst principlestheoretical level. Toward that end, we have been developing and applying a theory (called “Biodynamics”) on the general mechanisms by which: 1) cellular functions are conveyed by dynamic multi-molecular/-ionic (multi-flux) systems operating in the NLD regime; 2) cellular dysfunction results from molecular dysfunction; 3) molecular structure and function are powered by covalent/non-covalent forms of free energy; and 4) cellular dysfunction is corrected pharmacologically. Biodynamics represents a radical departure from the status quo empirical science and reduction to practice thereof, replacing: 1) the interatomic contact model of structure-free energy and structure-property relationships with a solvation free energy model; 2) equilibrium drug-target occupancy models with dynamic models accounting for time-dependent drug and target/off-target binding site buildup and decay; and 3) linear models of molecular structure-function and multi-molecular/-ionic systems conveying cellular function and dysfunction with NLD models that more realistically capture the emergent non-linear behaviors of such systems. Here, we apply our theory to COVID Mproinhibition and overview its implications for a holistic, in vivo relevant approach to drug design.