Protein Folding Simulation by Particle Swarm Optimization

ABSTRACT

This work introduces Particle Swarm Optimization (PSO) to protein structure prediction as a new field of application. Finding the global optimum in the free energy landscape of protein structures is a challenging, non-trivial task and has been subject of research for decades, resulting in many different approaches and methods until today. Here we show that a standard implementation of PSO is capable of optimizing backbone geometries and generating good solutions in refolding studies, yielding near native structures for two small sample proteins. We present a straightforward approach to include secondary structure information in the optimization process and show that results improve. Finally, a first predicted structure from ab initio folding by PSO is shown where native topology could be captured with a basic energy function, giving a promising outlook on future research.