UMR 5224

Brigitte Bidégaray-Fesquet — Molecular dynamics


LJK Brigitte Bidégaray-Fesquet
LJK, INRIA-NANO-D Stéphane Redon, Maël Bosson

Previous work

Modeling and simulation of natural or artificial nanosystems is still a challenging problem, however, for at least three reasons:

  • (a) the number of involved atoms may be extremely large (liposomes, proteins, viruses, DNA, cell membrane, etc.);
  • (b) some chemical, physical or biological phenomena have large durations (e.g. the folding of some proteins); and
  • (c) the underlying physico-chemistry of some phenomena can only be described by quantum chemistry (local chemical reactions, isomerizations, metallic atoms, etc.).

The NANO-D team aims at developing efficient computational methods for modeling and simulation of complex nanosystems, both natural (e.g. the ATPase engine and other complex molecular mechanisms found in biology) and artificial (e.g. NEMS - Nano Electro-Mechanical Systems).

In particular, the group develops novel multiscale, adaptive modeling and simulation methods, which automatically focus computational resources on the most relevant parts of the nanosystems under study.

These adpative models are based on a divide and conquer algorithm which allows to determine and update only relevant parts of the systems. They were first designed by Stéphane Redon on mechanical systems [RL06], [RGL05]. They were then applied to biological systems with CHARMM potentials [RIM+07], [GR10].

The NANO-D group develops SAMSON, a software platform for modeling and simulation of nanosystems (SAMSON stands for "System for Adaptive Modeling and Simulation Of Nano-objects"). SAMSON integrates all the algorithms developed in the group [BCRR09].

Maël Bosson defended his PhD in October 2012. He has been working on

  • adapting the previous model to Brenner potentials [BRPGR12] which allows to model the creation and deletion of chemichal bonds,
  • using quantum mechanical potentials (ASED-MO model) , with the same approach [BGR12],
  • developping many applications, such as graphene sheets [BGBR12],
  • and interfaces for education.


[BCRR09] Aude Bolopion, Barthélemy Cagneau, Stéphane Redon, and Stéphane Régnier. Haptic feedback for adaptive molecular simulation. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009).
[BRPGR12] Maël Bosson, Caroline Richard, Antoine Plet, Sergei Grudinin, and Stéphane Redon. Interactive quantum chemistry: a divide-and-conquer ASED-MO method. Journal of Computational Chemistry, 33, 77–790, 2012.
[BGR12] Maël Bosson, Sergei Grudinin, and Stéphane Redon. Block-Adaptive Quantum Mechanics: an adaptive divide-and-conquer approach to interactive quantum chemistry. Journal of Computational Chemistry, 34, 492–504, 2013.
[BGBR12] Maël Bosson, Sergei Grudinin, Xavier Bouju, and Stéphane Redon. Interactive physically-based structural modeling of hydrocarbon systems. Journal of Computational Physics, 231, 2581–2598, 2012.
[GR10] Sergei Grudinin and Stéphane Redon. Practical modeling of molecular systems with symmetries. Journal of Computational Chemistry, 31, 1799–1814, 2010.
[MR07] Sandy Morin and Stéphane Redon. A Force-Feedback Algorithm for Adaptive Articulated-Body Dynamics Simulation. IEEE International Conference on Robotics and Automation (ICRA 2007), 3245–3250, Roma, Italy, IEEE, 2007.
[RGL05] Stéphane Redon, Nico Galoppo, and Ming C. Lin. Adaptive Dynamics of Articulated Bodies. ACM Transactions on Graphics (SIGGRAPH 2005), 24(3), 936–945, 2005.
[RIM+07] Romain Rossi, Mathieu Isorce, Sandy Morin, Julien Flocard, Karthik Arumugam, Serge Crouzy, Michel Vivaudou, and Stéphane Redon. Adaptive torsion-angle quasi-statics: a general simulation method with applications to protein structure analysis and design. Bioinformatics, 23(13), i408–i417, 2007.
[RL06] Stéphane Redon and Ming C. Lin. An Efficient, Error-Bounded Approximation Algorithm for Simulating Quasi-Statics of Complex Linkages. Computer-Aided Design, 38(4), 300–314, 2006.
(Last updated January 2015)