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

The tertiary (3D) structure of a protein contains the essential information for understanding the biological function of the protein at the molecular and cellular levels. 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 as a result of worldwide genome sequencing and bioinformatics efforts. 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: (1) preprocessing to identify protein domains in the input sequence, (2) compilation of functional and structural information about a target protein through database search, (3) protein triage to determine which process an