Darwin and Fisher meet at biotech: On the potential of computational molecular evolution in industry
Today computational molecular evolution and bioinformatics are vibrant research areas that flourish on large amounts of complex datasets generated by new generation technologies – from full genomes and proteomes to microbiomes, metabolomes and epigenomes. Yet the foundations for successful mining and the analyses of such data were established long before the structure of the DNA was discovered. Darwin's theory of evolution by means of natural selection not only remains relevant today, but also
... nt today, but also provides solid ground for computational research with a variety of applications. The data size and its complexity require empirical scientists to work in close collaboration with experts in computational science, modeling and statistics, as Sir R. Fisher has beautifully demonstrated in early 20th century. Particularly, modern computational methods for evaluating selection in molecular sequences are very useful for generating biological hypotheses and candidate gene sets for follow-up experiments. Evolutionary analyses of selective pressures in genomic data have high potential for applications, since natural selection is a leading force in function conservation, in adaptation to emerging pathogens, new environments, and plays key role in immune and resistance systems. At this stage, pharma and biotech industries can successfully use this potential, taking the initiative to enhance their research and development with the state-of the art bioinformatics approaches. This mini-review provides a quick "why-and-how" guide to the current approaches that apply the evolutionary principles of natural selection to real life problems – from drug target validation, vaccine design and protein engineering to applications in agriculture, ecology and conservation.