Using quantum mechanics for better simulations

The problem with classical simulations of molecules is what’s known as quantum dynamics – the way objects move when they’re on a very very tiny scale.

Classical dynamics describes the motion of most things that we can see. For example, classical mechanics says that objects that are moving tend to stay moving, in the same direction and at the same speed, unless an external force acts on them. The laws of classical dynamics can predict and explain how most of the things you’re likely to encounter in day-to-day life will move.

However, once things get extremely small – for example the size of an electron – they no longer behave in a classical way, and the laws of classical dynamics break down. A different set of rules, known as quantum mechanics, come into effect.

The basic theory of quantum mechanics is that very tiny things have a property called wave–particle duality. For example, Isaac Newton though that light was made of lots of very tiny particles, whereas a later scientist – Christiaan Huygens – thought it was made of waves. Scientists carried out a series of experiments to determine which was true, and found that light could behave as both a particle and a wave.

Physicists later discovered that everything has wave–particle duality, not just light, but the effect is only noticeable in very small particles such as electrons. It is only when we get down to this scale that we have to worry about this behaviour.

Michele Ceotto and his team have applied quantum considerations to their simulations of a particular type of molecule – called protonated glycine supramolecular systems. "We demonstrate that some peculiar motions of systems of biological interest involving the simplest amino acid – glycine – and detected by experiments, can be explain correctly only if quantum effects are considered", he says. By including quantum mechanics in their simulations, the team have been able to make them much more accurate.

Computer simulations like these are predictive – that is they can be used to predict the behaviour of molecules that haven’t been studied yet, or even the existence of molecules that haven’t been discovered yet. By making these simulations as accurate as possible, scientists can save huge amounts of time and money that would otherwise have been spent on repetitively carrying out lab experiments. This makes it far easier and cheaper to discover new medicines.

This article is free to read in our open access, flagship journal Chemical Science: Fabio Gabas et al., Chem. Sci., 2018, Advance Article. DOI: 10.1039/C8SC03041C. You can access all of our ChemSci Picks in this article collection.