By Penny Carmichael, on 8 November 2013
Article by Enrico Berardo
This year’s Nobel Prize in Chemistry was awarded to Martin Karplus, Michael Levitt and Arieh Warshel, who played a crucial role in the development and application of methods for the simulation of complex chemical reactions. The Nobel laureates have been recognized for their effort in developing computer programs that simulate the behaviour of chemical systems at various length scales, from simple molecules to proteins, enabling the study of phenomena such as catalysis, protein folding and drug design.
Originally chemists used to create molecular models using plastic balls and sticks, but since the 1960s the modelling is carried out more and more on computers, allowing the calculation of important molecular properties such as stability and reactivity. Throughout the years, a continuous increase in the computational resources and more efficient algorithms enabled the application of calculations to larger and more realistic systems, such as proteins, drugs and materials. The work of Karplus, Levitt and Warshel, focuses on the development of methods that made Newtonian classical physics work side by side with the inherently different quantum theory. This Nobel Prize not only rewards the lifetime achievements of the three laureates, but it also recognizes the relevance of computational chemistry as a support and explanation for many experimental results.
In the classical approach atoms and bonds are approximated as balls and springs, making the calculations easy to solve and allowing the study of very large systems (up to thousands of atoms). However, since electrons are not considered explicitly, this method cannot be used to simulate reactions that cannot be easily parameterized with experimental data. For that purpose, an unbiased quantum mechanical approach needs to be used instead. In this approach electrons are considered explicitly, leading to a very detailed description of chemical processes. Its weakness is that the calculations require enormous computing power, limiting the size of the systems that can be studied.
The ground-breaking work of the three laureates revolutionized the field of computational chemistry, where combining quantum with classical mechanics (“QM/MM”), allowed the study of systems that were not even remotely conceivable before the 1970s. The use of those “hybrid” methods made the study of biomolecules such as enzymes possible, treating the reactive atoms of the molecule (core) with quantum mechanics, while the less demanding classical mechanical approach is used to describe the remaining part of the system.
The work behind this year’s Nobel Prize has been the starting point for further theoretical developments of more realistic models and for applied studies. Nowadays, hybrid methods are not only employed in the study of molecules of biological interest or complex organic reactions, but also for the optimization of solar cells or the study of materials used for catalytical applications.
Computational chemistry at UCL is represented by a grouping of international strength characterized by successful academic and industrial collaborations. It accounts for up to twenty different research groups where, thanks to the UCL and UK national computational resources, a breadth of different topics and methodologies are investigated. UCL’s computational chemistry has a strong tradition on the simulation of materials where Prof. Catlow’s, Prof. de Leeuw’s and Prof. Michaelides’ extended groups focus mainly on the study of catalytical applications of metal and metal oxides systems. Prof. Kaltsoyannis’ group employs quantum chemical investigations on actinide and lanthanide systems, with the focus on nuclear waste materials. Members of Prof. Price’s group investigate the thermodynamic stability of organic crystal polymorphs through the use of a classical mechanical approach. In the groups of Prof. Coveney and Prof. Gervasio large scale computational methods are developed and used for the modelling of systems like complex fluids, and molecules of biological interests.
Today simulations became so powerful that such a large variety of topics and methodologies can be employed to predict the outcomes of traditional experiments. However, no simulations will ever be able to predict if a future Nobel Prize winner is hiding in the UCL chemistry corridors. This is for the future to decide.
Further information on the work being carried out by UCL Chemistry’s computational groups can be found here
Sources for text and images:
1) Popular science background
2) Scientific background
3) Interesting annual review by Prof. Martin Karplus