Kinks are functionally important structural features found in the alpha-helices of many proteins, particularly membrane proteins. Structurally, they are points at which a helix abruptly changes direction. Previous kink definition and identification methods often disagree with one another. Here I describe three novel methods to characterise kinks, which improve on existing approaches. First, Kink Finder, a computational method that consistently locates kinks and estimates the error in the kink angle. Second the B statistic, a statistically robust method for identifying kinks. Third, Alpha Helices Assessed by Humans, a crowdsourcing approach that provided a gold-standard data set on which to train and compare existing kink identification methods. In this thesis, I show that kinks are a feature of long -helices in both soluble and membrane proteins, rather than just transmembrane -helices. Characteristics of kinks in the two types of proteins are similar, with Proline being the dominant feature in both types of protein. In soluble proteins, kinked helices also have a clear structural preference in that they typically point into the solvent. I also explored the conservation of kinks in homologous proteins. I found examples of conserved and non-conserved kinks in both the helix pairs and the helix families. Helix pairs with non-conserved kinks generally have less similar sequences than helix pairs with conserved kinks. I identified helix families that show highly conserved kinks, and families that contain non-conserved kinks, suggesting that some kinks may be flexible points in protein structures.

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on this, we extend the mapping of protein sequence not only to a fixed stable structure but also to an ensemble of protein conformations, which help us explain the complex interaction within a cell that was otherwise obscured. The objective of this dissertation is to develop effective ab initio methods and tools for protein un/structure prediction by developing effective statistical energy function, conformational search method, and disulfide connectivity patterns predictor. The key outcomes of this dissertation research are: i) a sequence and structure-based energy function for structured proteins that includes energetic terms extracted from hydrophobic-hydrophilic properties, accessible surface area, torsion angles, and ubiquitously computed dihedral angles uPhi and uPsi, ii) an ab initio protein structure predictor that combines optimal energy function derived from sequence and structure-based properties of proteins and an effective conformational search method which includes angular rotation and segment translation strategies, iii) an SVM with RBF kernel-based framework to predict disulfide connectivity pattern, iv) a hydrophobic-hydrophilic property based energy function for unstructured proteins, and v) an ab initio conformational ensemble generator that combines energy function and conformational search method for unstructured proteins which can help understand the biological systems involving IDPs and assist in rational drugs design to cure critical diseases such as cancer or cardiovascular diseases caused by challenging states of IDPs.

Protein sequences contain the information in order for a protein to fold to a unique compact, three-dimensional native structure. The forces that drive protein structures to form compact folds are largely dominated by burial of hydrophobic amino acids, which results in non-specific packing of amino acid side-chains. The knob-socket model attempts to organize side-chain packing into tetrahedral packing motifs. This tetrahedral motif is characterized with a three residues on the same secondary structure forming the base of the tetrahedron packing with a side-chain from a separate secondary structure. The base of the motif is termed the socket, and the other side-chain is called the knob. Here, we focus on extending the knob-socket model to understand tertiary and quaternary structure. First, single knobs sometimes pack into more than one socket in real structures. We focus on understanding the topology and amino acid preferences of these tertiary packing surfaces. The main results from the study of tertiary packing surfaces is that they have a preferred handedness, some interactions are ancillary to the packing interaction, there are specific amino preferences for specific positions in packing surfaces, and there is no relationship between side-chain rotamer of the knob packing into the tertiary packing surface. Next, we examine the application of the knob-socket to irregular and mixed packing in protein structure. The main conclusions from these efforts show canonical packing modes between secondary structures and highlight the important of coil secondary structure in providing many of the knobs for packing. Third, we investigate protein quaternary structure with a clique analysis of side-chain interactions. We identify a possible pseudo knob-socket interaction, and compare knob-socket interactions between tertiary and quaternary structure. Lastly, we discuss the workflow used in CASP12 to predict side-chain contacts and atomic coordinates of proteins.