Post doctoral position “Novel approaches for Quantum modeling of large systems” at CEA
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas:
defence and security,
low carbon energies (nuclear and renewable energies),
technological research for industry,
fundamental research in the physical sciences and life sciences.
Contacts: Luigi Genovese, L_Sim laboratory, CEA- Grenoble, email : email@example.com, (bigdft.org)
Host laboratory : L_Sim Laboratory, CEA Grenoble, France. Position available immediately.
Duration: The position is open for up to a four years period.
Theoretical chemistry tools (ab inito methods and DFT) are now largely and routinely used to investigate the properties of small molecular aggregates at the few hundreds atom scale. Investigating larger molecular assemblies (at the many thousands atom scale) is still highly challenging.
As an example, targeting specific monoclonal antibodies can be routinely achieved, however increasing the antigen affinity as much as desired is still a challenging task. Most of the available theoretical tools in this field mainly focus on investigating close contact antibody/antigen (AA) local regions and usually ignore the effect on affinity of more distant domains. Because of the size of AA assemblies only standard pairwise molecular modeling force fields or empirical cost functions are used to quantify the strength of their interactions. However these theoretical approaches are known to be based on crude approximations preventing to reach a level of accuracy which is sufficiently high.
Our aim is to assess the reliability of a recently developed framework, which connects BigDFT, a High Performance Computing code, with a hybrid molecular modeling(MM)/quantum chemistry scheme to investigate the networks of microscopic interactions responsible for the stability of large molecular assemblies. Systems of sizes of at least tens of thousands atoms will be investigated by means of molecular dynamics performed using a polarizable MM approach (http://biodev.cea.fr/polaris/) and representative assembly snapshots identified from clustering the conformations observed along the MM simulations will be post processed using an O(N) efficient DFT tool based on Daubechies wavelets (https://bigdft.org/). We plan to apply that hybrid scheme to large protein assemblies as well as to understand the interactions of organic species (peptide, fatty acid and sugars) at the surface of large aqueous droplets that are pivotal in pollution phenomena.
Our project, awarded by a SANOFI iTech Award 2020, adds two new steps to standard computational protocols used to model AA assemblies (like for instance the popular one based on the Rosetta package of programs) to further evaluate and refine their solutions. These two steps consist in: (1) investigating the AA potential energy surface from molecular dynamics Replica Exchange simulations based on a polarizable multi-scale molecular modeling approach; (2) refining the simulation results using the complexity reduction framework of BigDFT, that enables to compute the quantum interaction energy of full AA assemblies.
The candidate will be of particular help in coupling the above new modeling approaches with standard docking ones in order to build a numerical tool that will be used routinely in pharmaceutical industry R&D workflows.
The proposed work is based on competences in molecular modeling and/or quantum chemistry, docking and/or molecular dynamics of Antigen/Antibody assemblies, competence in programming of high performance computing codes. The candidate should be willing to learn/enforce his/her skills in all those fields. He/She should prove previous experience in at least one of these competences.