Predicting pH-Dependent Uncoupling Toxicity of Organic Acids: A Biophysical Screening Tool

Mitochondria are the cell’s powerhouses. By oxidizing nutrients, they generate a proton gradient across the inner mitochondrial membrane. This electrochemical “battery” is the direct source of ATP, the universal energy currency of life.

What if an “uncoupler” disrupts this finely tuned system?

An uncoupler acts like an electrical short: it shuttles protons back across the membrane, collapsing the gradient. The stored energy is released as heat, and ATP synthesis stalls.

Outcomes depend on dose. At low levels, cells may up‑regulate metabolism to compensate. At higher concentrations, the loss of ATP, excess heat, and gradient collapse can be lethal.

Historically, the uncoupler 2,4‑dinitrophenol (2,4‑DNP) was marketed as an anti‑obesity agent in the 1930s, but severe overdose toxicity—including death—led to its withdrawal. Today, researchers seek milder uncouplers with therapeutic potential, while also recognizing that off‑target uncoupling can arise in unrelated drug candidates. Detecting such toxicity early reduces late‑stage attrition and cuts development costs.

A Mechanistic Model to Predict Uncoupling Activity

Existing predictive models are largely empirical and limited to compounds structurally similar to those in their training set. Moreover, they rarely account for environmental factors such as pH, which can markedly alter uncoupling potency.

To address these gaps, scientists at the Institute of Toxicology, Friedrich Schiller University (UFZ), developed a biophysical model that forecasts pH‑dependent uncoupling toxicity of organic acids directly from their chemical structure. The approach combines BIOVIA COSMOtherm and TURBOMOLE calculations to generate key parameters: pKa values, membrane permeability, and dimer stability constants. These descriptors feed into a mechanistic framework grounded in quantum chemistry and the COSMO‑RS continuum solvation model.

Because the model is based on first‑principles calculations rather than fitted data, it offers a universal screening tool applicable to diverse chemical classes and experimental conditions, enabling early identification of potential uncoupling liabilities.