CEXS-UPF: Scientists reveal for the first time the details of protein association at the atomic level

CEXS-UPF: Scientists reveal for the first time the details of protein association at the atomic level

News from CEXS-UPF

Scientists from Freie Universität Berlin (FU Berlin) and UPF have, for the first time, simulated the association and dissociation of protein molecules in atomic detail. The results were published in Nature Chemistry and were validated with experimental data.

The groups of Frank Noé, at FU Berlin, and Gianni De Fabritiis, ICREA research professor at UPF, have now collaborated to produce what is the first atomic-detail computer simulation of the process of protein-protein association and dissociation. The main challenge was that atomic-detail molecular dynamics are incredible expensive to simulate. The interactions of about 100,000 atoms need to be computed, and the force felt by every atom is evaluated. Then, the simulation moves every atom by a small distance in the direction of the force while it advances the simulated time by a femtosecond - a tiny fraction of a second. Each such step is computationally expensive, but a billion times a billion of such steps need to be performed in order to simulate the time of one hour that is the typical time the proteins stay bound before they dissociate again.

The simulation in molecular dynamics of protein association was thought to be impossible to perform at the computational level due to the amount of time needed to take samples of the biochemical process: even using a supercomputer, it is estimated that the process would have required 10,000 years to complete. "It is the type of high-risk project that is very difficult to get funding for, because when we started, no-one would believe that it's even possible", says Noé.

More information:
CEXS-UPF website 

Reference work:
Nuria Plattner, Stefan Doerr, Gianni De Fabritiis, Frank Noé. Complete protein-protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling. Nature Chemistry, Junio 2017. DOI: 10.1038/NCHEM.2785