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Computers play an important role in the development of new chemical compounds

today, writes Siân Harris in the first of two articles on computational chemistry


f you asked people on the street to describe their image of chemists working on new compounds, there would likely be some common themes: lab coats, safety glasses,

glassware with colourful solutions bubbling away, fume cupboards… What they might be less likely to describe is a

scientist sitting at a computer, big datasets at his or her fingertips, and images of virtual reactions on the screen. Yet, increasingly, chemical discovery involves

both types of approach to research. Earlier this year, scientists and engineers at

Harvard University in the USA made headlines aſter publishing a paper in the journal Nature, describing a new battery technology based on a group of organic compounds known as quinones. Te flow-battery system reported in the paper promises cheap, clean and reversible energy storage when it is needed, oſten seen as a missing piece in the quest for widespread renewable energy. But a key part of this research was selecting

the compounds to use in the first place. Although quinones have been known for a long time to be promising for electrochemical applications – many occur naturally and carry out similar functions in plants – not all will work well in a flow battery. As Michael Aziz, a professor of materials and energy technologies at Harvard School of Engineering and Applied Sciences and one of the research team, noted, to be suitable for the group’s flow battery technology, quinones needed good reduction potential, solubility, and stability. Tis posed a challenge: there are many

thousands of potential compounds and nowhere near enough hours to make each one and then fabricate a battery using them. Fortunately, the interdisciplinary team included a theoretical chemist, Alán Aspuru-Guzik, professor of chemistry and chemical biology at the university, who was able to whittle down the l Experiments were not enough in Harvard’s flow battery research



list using virtual screening. Aspuru-Guzik ran computational studies

on 10,000 quinones to identify a much smaller subset of compounds likely to meet the criteria. Te synthetic chemists involved in the project then made these compounds for the engineers to test. Te result was that, a year into a grant from the US Department of Energy, the team was able to publish its Nature paper reporting promising early findings. What’s more, the team anticipates having a prototype storage system to test with wind turbines within three years.

Drug design Tis type of interdisciplinary project spanning the boundaries between laboratory and computer has become increasingly important in both academia and industry. It has become particularly significant in the pharmaceutical industry. ‘15 years ago, the ability of modelling to


influence drug discovery was very limited. Today chemists routinely use predictive tools. Tey’ve become routine and ubiquitous,’ noted Adrian Stevens, senior manager, predictive sciences marketing, life sciences for Accelrys, which develops modelling soſtware based on its Pipeline Pilot graphical programming language. ‘Modellers are much more integrated.

Typically a modeller [in a pharmaceutical team] will support three to five research teams and projects, with perhaps a day to turn around a model.’ (See the next issue of Scientific Computing World for more on modelling in drug discovery).

New materials In addition to saving time, modelling can reveal many things not possible experimentally. Chris Greenwell, of the Department of Earth Sciences at the University of Durham, UK, for example, uses molecular modelling to study the structure, properties, and chemical reactions occurring on mineral surfaces. ‘We use computational methods as they allow us insight at a level that would otherwise be impossible to achieve, and to probe different possible structures with exquisite control,’ he explained. Tis might mean, for example,

understanding how organic molecules interact FEBRUARY/MARCH 2014 31

Eliza Grinnell, Harvard School of Engineering and Applied Sciences

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