Chemistry in silico1

Key Words Computatinal chemistry

The discovery of new effective drugs or the design of novel materials with interesting properties used to be a long process requiring large team efforts, state-of-the-art equipment and a conspicuous amount of funding. Nowadays, there is potentially a cheaper and simpler alternative: computational chemistry.

Computational chemistry is a field of chemistry where computers are used to calculate, simulate and predict the properties of matter. The idea behind computational sciences is the assumption that a given chemical or physical phenomenon can be described with a set of complicated mathematical equations, which are way too difficult to solve with pen and paper. To solve such complex equations, computational chemists (with physicists, engineers and bioscientists) write software that does it in an automated and straightforward way.

Figure 1 Calculated energy as a function of the torsion of butene, obtained using computational chemistry software. Form such calculation one can predict the stable configurations (picks represent unstable structures while valleys represent stable structures) and the energy needed to go from one configuration to another.

If one is interested in the properties of matter at the atomic level, the behavior of nuclei and electrons have to be described explicitly, therefore the theory of quantum mechanics is used (figure 1). Equations of quantum mechanics are so complicated that even modern supercomputers (computers with the computational power of hundreds or thousands of laptops) struggle to solve them, and approximations are needed. A good slice of today’s 1 In silico: (of scientific experiment or research) conducted or produced by means of a computer modelling or computer simulation.

research in the field is focused on finding new approximations, or better and faster ways of using the approximations already available.

In my PhD I am currently working on embedding approximations. The idea behind ‘embedding’ is that often interesting phenomena occur in a local part of the molecule or system. It is often possible to describe these in a precise (and computationally expensive) way, while the surroundings of that region (the environment) are described less accurately. This approach allows to obtain good results of the phenomenon of interest whilst keeping the computational costs low. Computational costs are determined by: the length of the calculation, the number of processors involved, the amount of RAM memory and the amount of disk memory used.

New approximations need validation: this is often done by comparing computational data with experiments. In turn, validated approximations can shed light on experimental work. Computational work can help experimental chemists understand what’s happening in their studies, or even produce novel predictions that can be experimentally tested on a later stage. This interplay between computations and experiments is becoming more and more important in modern chemistry. For example, computational methods are routinely applied in drug discovery and drug design, where possible drugs are studied in silico and only interesting candidates are tested in laboratory. The same applies to high-throughput screening of novel materials: the properties of many different compounds are computed and the ones with interesting properties are tentatively made in the laboratory. This saves expense.

As the tools of computational chemistry are becoming very powerful, easy to use and more widespread, they will help to shape the future of chemistry and material sciences.

Rocco Meli joined Prof. Fred Manby’s group in the Centre of Computational Chemistry (CCC) at the University of Bristol as PhD student, funded through EPSRC Centre of Doctoral Training in Theory and Modelling in Chemical Sciences. He is working on a new electronic structure software, entos, developed within the group as the vehicle of recently developed embedding theories.

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