In Silico Biophysical Characterization of PFAS Toxicokinetics: From Passive Membrane Permeation to Active Transport Modulation at Renal and Placental Barriers

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants whose toxicokinetics (TK) and mechanisms of action remain poorly understood, particularly regarding their passage through critical biological barriers. This PhD project aims to decipher the molecular mechanisms governing the interactions of PFAS with the placental and renal barriers at the atomic scale. The objective is to overcome the limitations of current models by simulating the precise physicochemical events underlying both passive permeation and active transport.

The project will rely on advanced computational chemistry and molecular dynamics (MD) techniques, structured around three key axes:

• Passive Permeation Modeling: Using the Memcross protocol and the Accelerated Weight Histogram (AWH) algorithm, the student will calculate the free energy profiles (Potential of Mean Force - PMF) of various PFAS crossing lipid bilayers. This will allow the prediction of key biophysical parameters such as partition coefficients and permeation rates for a broad library of PFAS and their metabolites.
• Structural Reconstruction of Transporters: The student will refine in house existing 3D structural models of key membrane transporters involved in PFAS influx (OAT1, OAT3, OATPs) and efflux (P-gp, MATE1, MRP2). This will involve using either cryo-EM structures or AI-based prediction tools (AlphaFold2) followed by MD simulations in physiological lipid environments to stabilize relevant conformations (Inward/Outward-facing).
• Molecular Interactions and Transport Mechanisms: Through molecular docking and unbiased MD simulations, the project will characterize the binding modes of PFAS to these transporters. The student will investigate whether PFAS act as substrates (transported) or inhibitors (blocking endogenous transport), analyzing induced-fit mechanisms and allosteric perturbations within the protein structures.

The thesis will provide a detailed mechanistic description of how the fluorocarbon chain length and headgroup chemistry of PFAS influence their ability to cross cell membranes and interact with transporter binding pockets.

The project will further validate the Memcross protocol for complex, surfactant-like environmental pollutants, establishing it as a reliable tool for high-throughput in silico screening. The generated kinetic parameters (permeability coefficients, affinity constants) will feed into and validate the experimental results obtained from Organ-on-Chip models (developed in parallel Work Packages), moving away from animal testing. The developed mechanistic models will be transferred to the partner company InSilibio, enriching their service portfolio for predictive environmental health toxicology.

Research Environment

Inserm Unit U1248 P&T, located within the Biology and Health Research Center (CBRS) in Limoges, is a multidisciplinary unit specializing in personalized medicine. The laboratory focuses on optimizing therapeutic strategies, particularly in the fields of transplantation and immunology, by bridging the gap between clinical pharmacology and innovative technologies.

Focus on Modeling and Micro-Physiology

The unit has developed a strong expertise in integrating computational and experimental approaches to better understand drug-organ interactions:

Pharmacometrics & Mechanistic Modeling: Our research involves the development of multi-scale PK/PD models and the use of artificial intelligence to predict individual drug responses. We aim to move beyond traditional statistics toward predictive, individualized pharmacology.

Organ-on-Chip (OoC) & In Vitro Engineering: To complement our in silico activities, we develop microphysiological systems. These Organ-on-Chip models serve as advanced platforms to simulate human physiological barriers and organ functions, providing a robust alternative to animal testing for drug metabolism and toxicity studies.

Positioning & Objectives

Working at the interface of the Limoges University Hospital and the University of Limoges, U1248 P&T provides a translational research environment. PhD candidates will benefit from a culture of pharmacology, AI modeling and bio-engineering, supported by high-level technical facilities. Our goal is to provide students with the tools to address the current challenges of modern pharmacology through a rigorous, technology- and data-driven scientific approach.

A good knowledge in computational chemistry methods is highly recommended, together with a physical-chemistry or biological background. Basic knowledge in machine learning OR biological processes will be considered as a real asset. Skills in using informatic tools is recommended, or at least a strong interest for computing and learning new softwares or computer codes is mandatory.

• Applicants must hold a Master’s degree in chemistry, biochemistry, biophysics or a related field.
• Experience in molecular modelling is required, MD simulations being considered as a strong advantage
• Experience in basic scripting is required, the use of python being considered as a strong advantage
• Background in physical chemistry is considered as an advantage
• Knowledge in machine learning is considered as a strong advantage

Good oral and written communication skill in English is highly recommended.