A computational pipeline for protein structure prediction and analysis at genome scale

Traditionally, protein 3D structures are solved using experimental techniques, like X-ray crystallography or nuclear magnetic resonance (NMR). While these experimental techniques have been the main workhorse for protein structure studies in the past few decades, it is becoming increasingly apparent that they alone cannot keep up with the production rate of protein sequences. Fortunately, computational techniques for protein structure predictions have matured to such a level that they can complement the existing experimental techniques. In this paper, we present an automated pipeline for protein structure prediction. The centerpiece of the pipeline is a threading-based protein structure prediction system, called PROSPECT, which we have been developing for the past few years. The pipeline consists of seven logical phases, utilizing a dozen tools. The pipeline has been implemented to run in a heterogeneous computational environment as a client/server system with a web interface. A number of genome-scale applications have been carried out on microbial genomes. Here we present one genome-scale application on Caenorhabditis elegans.