The Laboratoire International Associé between the Centre National de la Recherche Scientifique and the University of Illinois at Urbana-Champaign was launched at the end of 2012. Its primary objective is to develop methods for high-performance molecular simulation with the aim of understanding the function of complex biological assemblies, transcending the frontiers of traditional disciplines by uniting mathematicians, physicists, theoretical chemists and biologists on both sides of the Atlantic. In France, the major contributors are located at the Université de Lorraine, the École des Ponts ParisTech, the Institut de Biologie Structurale and the Laboratoire de Biologie Physico-Chimique. In the United States, the contributors belong to the NIH Resource for Macromolecular Modeling and Bioinformatics. In Nancy, the partner is a theoretical chemistry and biophysics group incepted in 2003. Its expertise lies in describing the structure and the dynamic properties of the biological membrane and elucidating the mechanisms of the cell machinery. To attain this goal, its members leverage numerical simulations over size and timescales commensurate with the biological process at hand. Over the years, the team has gleaned milestone results in such diverse research areas as membrane transport, interaction with the biological membrane, membrane protein structure and function, as well as self-organized molecular systems. They also develop original approaches in the field of free-energy calculations to tackle rare events in biology.
Highlight
Machine learning reveals the critical interactions for SARS-CoV‑2. Spike Protein Binding to ACE2 SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD–ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N. Journal of Physical Chemistry Letters, 2021.
Recent publications
Free Energy Methods for the Description of Molecular Processes
Christophe Chipot;
Annual Review of Biophysics (2023) 52 (1):
A Practical Guide to Recent Advances in Multiscale Modeling and Simulation of BiomoleculesEnhanced Sampling Based on Collective Variables
Yong Wang; Ruhong Zhou; Haohao Fu; Wensheng Cai; Christophe Chipot; Xueguang Shao; (2023) 1-22
Chasing collective variables using temporal data-driven strategies
Haochuan Chen; Christophe Chipot;
QRB Discovery (2023) 413 (242-
