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Thursday Seminars - From quantum computational physics to the origins of life

Thursday, March 24 2022, 11.00 am

by A. Marco Saitta,
Professor at IMPMC - Sorbonne Université, CNRS, MNHN, Paris

¡¡¡¡Seminar postponed to a later date  !!!!

 

Computational approaches are nowadays a full, self-standing branch of chemistry, both for their quantum-based (“ab initio”) accuracy, and for its multiscale extent.

In prebiotic chemistry, however, due to the intrinsic complexity of the chemical problems, ab initio atomistic simulations have so far had a limited impact, with the exception of a few relevant studies [1], including the elucidation of the chemical interactions between biomolecules with surfaces, such as ice and minerals, or the simulation of the effect of the pressure/temperature shock waves induced by meteorite impacts in the early Earth.

Surprisingly, even the celebrated Miller experiments, which historically reported on the spontaneous formation of amino-acids from a mixture of simple molecules reacting under an electric discharge, had never been studied at the quantum atomistic level.

Here we set the general problem of ab initio calculations in prebiotic chemistry by defining chemical networks within a new topology-based definition of reaction coordinates [1]. We thus report on the first ab initio computer simulations, based on quantum physics and a fully atomistic approach, of the celebrated Miller experiment in the condensed phase.

Our study [2] shows that glycine spontaneously form from mixtures of simple molecules once an electric field is switched on. We identify formic acid and formamide [3] as key intermediate products of the early steps of the Miller reactions, and the crucible of formation of complex biological molecules, as confirmed by our recent experimental and theoretical study on high-energy chemistry of formamide [4].

From a broader chemical perspective, we show that formamide plays the role of hub of a complex reaction network in both the gas and the condensed phase [5]. We are now going on a larger scale, studying the atomistic mechanisms of RNA nucleotides synthesis [6], amino acids [7,8] and sugars [9] in fully realistic prebiotic solution environments.

All these results pave the way to novel computational approaches in the research of the chemical origins of life [1], where we are integrating new approaches based on machine learning [10].

Literature References :

[1] Physics of Life : Reviews (2020). [2] PNAS (2014). [3] PNAS (2015a). [4] PNAS (2017). [5] PNAS (2015b). [6] J. Phys. Chem. Lett. (2018). [7] ACS Earth Space Chem (2018). [8] J. Phys. Chem. Lett (2021). [9] Chem Comm (2018). [10] manuscript in preparation