Variable-length Fragment Assembly within a Probabilistic Protein Structure Prediction Framework Variable-length Fragment Assembly within a Probabilistic Protein Structure Prediction Framework

VARIABLE-LENGTH FRAGMENT ASSEMBLY WITHIN A PROBABILISTIC PROTEIN STRUCTURE PREDICTION FRAMEWORK Kevin Molloy, M.S. George Mason University, 2011 Thesis Director: Amarda Shehu It is widely accepted that a protein’s biological function is highly correlated to the three-dimensional shape the protein assumes under physiological/native conditions. Predicting this three-dimensional structure, known as the native structure, from the protein’s amino-acid sequence is known as the protein structure prediction problem. This problem is regarded by many to be one of the grand challenges of computational biology. Fragment-based assembly is a widely used technique in ab-initio structure prediction methods that seek to predict structure from sequence. Essentially, a protein structure is pieced together with configurations of fragments extracted from databases of deposited protein native structures. Fragment length is an important consideration. The shorter the fragment, the more complex the protein conformational space where the native structure resides and the more rugged the energy surface associated with that space. The longer the fragment, the simpler the conformational space and the smoother the energy surface; hence, the higher the risk of missing important regions of space that may lead to the native structure. In this thesis, we explore the idea of varying the employed fragment lengths to alter the protein conformational space explored during a probabilistic search for the native structure. Varying fragment lengths allows for manipulating the dimensions of the search space during the process of sampling protein conformations. Essentially, longer fragments are used in early stages of the search to simplify the search space and smooth the energy surface. Shorter fragments are then utilized in later stages to provide visibility to the more complex and realistic conformational space. This approach is validated on four protein systems of diverse sizes and native topologies. The results show that employing variable-length fragments enhance the sampling of the conformational space for each protein, producing higher-quality native-like structures as compared to using a single fragment length. These promising results lay the foundations for exploring additional research directions in equipping a probabilistic search framework with the ability to make on-the-fly decisions and adaptively change the dimensionality of the conformational space it explores. Chapter 1: Introduction Proteins play a central role in many biochemical processes in the living cell. A protein’s function is largely determined by its three-dimensional structure [4–6]. If available, structural information would provide insight into various diseases and assist in the design of novel drugs [7]. Wet-lab techniques to capture a protein’s biologically-active structure have not been able to keep up with the millions of protein sequences being cataloged by biologists [8]. Computational methods are called upon to provide this information for protein sequences with no available structural information. The Anfinsen experiments concluded that it is possible to determine the biologicallyactive structure of a protein, also known as the native structure, in silico. The sequence of amino acids that make up a protein chain determines to a great extent (provided “a physiological milieu”) the spatial arrangement of these amino acids where the protein is biologically active and carries out its biological function [9]. The terms structure and conformation are interchangeably used to refer to a spatial arrangement of amino acids. In this thesis, we will reserve employing the term structure when referring to the native structure. If a protein has n amino acids, and the position of each one in space demands x degrees of freedom (dofs), the conformational space has size “xn”. Figure 1.1 illustrates a short chain of 3 amino acids. A simplified model of a protein may restrict the dofs to only the φ and ψ backbone angles (annotated in Figure 1.1), resulting in 2n dofs. Proteins can extend for hundreds of amino acids in length. Therefore, facing a high-dimensional conformational space in the search for the native structure, two strategies are often employed: (i) simplifying the conformational space and/or (ii) designing effective search algorithms.