Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology

Abstract

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT.

Biodynamics: A novel quasi-first principles theory on the fundamental mechanisms of cellular function/dysfunction and the pharmacological modulation thereof

“…We proposed in our previous work [1] that time-dependent cellular function is derived from a 5 molecular form of analog computing [2,3], in which sets of coupled ordinary differential equations and their integral solutions are modeled physically by changes in the rates of buildup and decay) among the populations of biomolecular species to/from specific intra- and intermolecular states (the hardware and software are one and the same) (Fig 1). We referred to these constructs as “molecular differential equations” (MDEs) [1], the major forms of which include:…”

“…Enzyme-substrate: where dγ k ( t )/ dt represents the rates of non-equilibrium occupancy buildup and decay of state k from one or more predecessor to one or more successor states. State transition rates are governed by adjustable barriers originating from intra- or intermolecular interactions (which we referred to as “intrinsic rates”) and time-dependent changes in the concentrations or number densities of the participating species (which we referred to as “extrinsic rates”) [1]. Molecular populations “flow” over time in a transient (Markovian) fashion from one specific structural state to another (Fig 1) in response to production/degradation or translocation-driven changes in the levels of the participating species.…”

“…{γ k (t), k = 1, n} and Γ a (t) manifest as transient stimulus-response-driven “action potential-like” waveforms, in which the intrinsic or extrinsic rates of one or more MDEs are sped or slowed in response to Γ a (t). [1].…”

“…The six branches of biodynamics theory, which span the intra-/peri-cellular (micro-cellular) and macro-cellular levels (see text). Such processes can be simulated using multiscale modeling approaches, ranging from atomistic molecular dynamics-based [1] to “atom-less” time-dependent ODE-based simulations (“MDE mimetics”) [1]. …”

“…In our previous work, we described the putative mechanisms by which free energy is transduced into non-equilibrium conditions and kinetic barriers (i.e. which we refer to here as “energy dynamics”) [1,4,12–15], and exemplified cellular computing by way of the cardiac AP [4] and a generic MAP kinase-phosphatase system [1]. Here, we focus on binding as a key “integrator” of MDE systems, and in particular, the specific implications of non-equilibrium conditions on occupancy of the bound states of both endogenous molecules and drugs (i.e.…”