As we know, the heritable mutations that create variation within a population occur in genetic material, but natural selection operates according to the changes that they produce in translated protein products. As such, the genetic code plays a fundamental role in steering the pathways of molecular evolution. However, to date, there are only few studies have explicitly considered code/genome co-evolution in order to study the properties of codes.

Therefore, the major research component of my research work will consist of a series of simulations to investigate a fundamental reinterpretation of the adaptive genetic code in terms of the influence of coding rules on the rate of adaptive protein sequence evolution.

By exploring the role of different genetic codes in influencing the evolutionary dynamic of natural selection operating on both linear genes sequences and protein 3D structure, I seek to test:

1. If the standard genetic code outperforms random alternatives in terms of the speed of adaptive protein sequence evolution?
2. What features of the standard genetic code produce this effect?
3. If error minimizing genetic code offers a selective advantage in terms of speed up the dynamic evolution of protein sequence? (The effects predicted by Fisher’s geometric theorem)
4. If the basic results established is robust in “Red Queen” evolutionary scenario, in which the precise nature of the optimal protein itself changes over time, and selective pressure acts to keep the evolving sequences adapting to this moving optimal protein.

Software associated with my research works will be made available as an online bioinformatics toolkit, and as downloadable freeware.