ANR-JCJC In Silico Models of drug Transport to Enhance Personalized medicine
Contact - Information
Florent DI MEO
Patrick TROUILLAS
UMR-1248 INSERM
CBRS – Université de Limoges
2, rue du Pr Bernard Descottes
87000 Limoges
Deadline: CLOSED
Documents:
- Resume
- Cover Letter
- Contact for recommandation letter(s)
Funding Source:
ANR – JCJC IMOTEP
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PhD Project - Computational Chemistry
Recent improvements of supercomputer capacities and of theoretical models have significantly broadened the field of applications in molecular modelling. Key sites of drug disposition and/or effects can now be modelled by molecular dynamics (MD) simulations, supporting understanding of pharmacokinetics (PK), pharmacodynamics (PD), as well as pharmacogenetics (PGx).
In organ transplantation, the transplant community has learned to do better with the same drugs, owing to the lack of new immunosuppressive drugs. Various PK tools for improved dose individualisation, risk scores and biomarkers have proposed, and, to some extent, have been adopted by transplant physicians. However, an unexplained variability in the immunosuppressive drug (ISD) response and related toxicity still remains. This is likely due to the combination of low-penetrance or rare variability factors (e.g., drug-drug interactions – DDI – or low-penetrance polymorphisms).
There is a need for a better evaluation of local concentration of drugs in the vicinity of their biological target(s), which requires a thorough understanding of drug-membrane crossing events. In silico pharmacology may help model, understand and predict drug-membrane crossing involved in the relationship between systemic and local PK. Besides, PGx drives both PK and PD. The investigation of PGx/PK and PGx/PD interactions would benefit from the atomic and dynamic description of drug transport, using MD simulations.
In this perspective, the ANR JCJC IMOTEP focuses on human membrane transporters that are involved in PK and PD of drugs used in organ transplantation (e.g., ISD, antivirals, antibiotics) and located in the kidney and the liver (namely MRP2/4, OATP1B1/1B3, OAT1/3). These in silico transporter models will be built including membrane in physiological conditions to simulate (i) the dynamics of the transport cycle, (ii) the influence of different polymorphisms or rare mutations, and (iii) DDI/PGx interactions.
So far, whole molecular structures have not been experimentally resolved. In silico models will be built using homology modelling techniques refined by MD simulations. We recently applied this dual approach to build MRP4, elucidating the former unresolved flexible domains as well as the impact of SNPs on the protein conformation. The molecular understanding of MRP4-like transport cycle is currently under investigation by using the state of the art of MD techniques.
The PhD candidate will focus on a limited but relevant number of SLC transporters (namely OATs) as well as their interactions with drugs used in organ transplantation. Using similar procedures as those used with MRP4, he will construct models of the human OAT1 and OAT3 transporters, embedded in membrane models. The candidate will use the MD techniques to refine the structures and to capture the conformational flexibility of these transporters. Once both structure and, at least partially, transport cycle are elucidated for a given transporter, drug-transporter interactions and DDI will be investigated at the molecular level. The impact of rare mutations and polymorphisms of clinical interest will be systematically assessed, thus predicting the influence of PGx on transporter functions. The development of atomic-based in silico pharmacological models of membrane transporters may represent a step forward in the understanding of drug PK and PD by adding a new size- and timescale to PK/PD and PGx tools. The main goal of this PhD project is to provide a comprehensive overview of drug membrane transporter to support experimental and clinical data as a complement to already existing predictive tools. The candidate will benefit from the multidisciplinary framework of the INSERM U1248 including in vitro experiments as well as clinical data from patients treated with different drug combinations and different doses.
A good knowledge in theoretical chemistry methods is highly recommended, together with a physical-chemistry background. Basic knowledge in biological processes or pharmaceutical issues will be considered as a real asset for this project. Skills in using informatic tools is recommended, or at least a strong interest for computing and learning new softwares or computer codes is mandatory.
Applications and informal queries should be addressed to Florent Di Meo (). Interested candidates should send their CV, a cover letter describing their research interests and the names of maximum 2 persons willing to write a recommendation letter.