In the previous blog, I wrote about directed evolution for the discovery of variants of proteins with desirable properties (and that this is a multiobjective combinatorial optimisation problem). The usual metaphor for understanding the relationship between sequence and structure is that of a ‘landscape’, in which one moves about through sequence space seeking a high peak (of fitness). A danger here is of premature convergence, where one rushes up the nearest hill (‘Snowdon’) while failing to search in regions that might ultimately prove more fruitful (‘Mont Blanc’ or ‘Everest’). Because the number of experiments one can typically do at one time (a batch or ‘generation’) is very small relative to the size of sequence spaces, it is common to favour the selection of ‘good’ variants, which means that mutations that on their own are deleterious (as most are) will be lost before helping one get across a valley to a higher mountain range (very high mutation rates may help here). A very nice paper by Tokuriki and Tawfik provides one possible solution that ‘keeps alive’ otherwise deleterious mutation long enough for them to produce what would then become much fitter variants among their own offspring (‘reculer pour mieux sauter’). The trick is to express a molecular chaperone such as GroEL/GroES. This improved ten-fold the ease of finding high activity in new variants, a substantial improvement. Interestingly, the same group have also suggested biophysical bases for the relationships between dynamism and evolvability, indicating for instance that loosely packed cores of viral proteins (such as that of influenza A) contribute to their rapid evolution.

Last week, I was pleased to open a new Centre of Excellence in Mass Spectrometry at the University of York. This is a really excellent partnership between the Departments of Biology and Chemistry at the University, the local RDA, and Science City York, that recognises the important of technologies to modern bioscience and is the latest addition to the impressive Technology Facility there.

Economies, like proteins, are also subject to evolutionary processes. I also attended and spoke at an interesting discussion hosted at the Institute of Physics and organised by the UK Resource Centre for women in Science, Engineering and Technology. The focus was the question of whether we were maximising the opportunities ‘offered’ by the economic downturn for making best use of the scientifically trained workforce, and especially of its female component. I spoke on both the role of S&T in driving economic growth – if you doubt it look at the agricultural revolution, the industrial revolution and now the knowledge economy – and the role of women in BBSRC’s Scientific activities. In biology most ‘A’ level students (and indeed undergraduates, postgraduates and researchers) are female, but this fraction drops off substantially at the levels of Senior Lecturer and Professor (for reasons that are complex and uncertain). Evidently there is the possibility that we are losing a considerable amount of scientific talent in this process. This said, there are many encouraging role models, and I would point readers at the 64 case studies of scientists who are mothers available on the Royal Society website.

Other speakers included Ann Pettifor (a prescient economist who had foretold of the instability of our financial systems in a couple of books published well before the credit crunch, and who runs a blog called debtonation), Mandy Clarke (Group Director of Human Resources at Halcrow), Ursula Martin (a Vice Principal, and Chair of Computer Science, at QMUL) and Annette Wiliams (Director of the Resource Centre for women in Science, Engineering and Technology). The session was introduced and chaired most effectively by Ruth Sunderland, Business Editor of the Observer newspaper.

I have not yet read Ann Pettifor’s books (but will be doing so), but they raise the general issue, on which I have blogged before, of how one should best manage the flood of complex data and information that exists in order to optimise decision making, much as in science. Clearly part of the problem was the high-risk-based reward culture of the City in which numerate employees were allowed to create financial instruments of Byzantine complexity by managers who did not understand them (and who probably still cannot value all their assets, whether ‘toxic’ or otherwise). In this sense, an understanding of ecology and evolution, as well as systems science, might beneficially be part of the training of any economist and manager. I still consider that solving the Two Cultures problem remains a key goal, as it is for our promotion of multi- and inter-disciplinary science generally.

Finally, some of the papers I read included a super one on the (generally applicable) use of computational structural biology to infer likely off-target effects of small molecules, as well as a somewhat related one using a threading method. And on the Open Access front, Smith describes the significance of making data (and their attendant metadata) freely available, as per BBSRC’s data sharing policy., while Pfeiffer and Hoffmann caution about the perils of groupthink. That too may have been a particular problem underlying the origins of the credit crunch.

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