Computational Comparative Study of Tuberculosis Proteomes Using a Model Learned from Signal Peptide Structures

Secretome analysis is important in pathogen studies. A fundamental and convenient way to identify secreted proteins is to first predict signal peptides, which are essential for protein secretion. However, signal peptides are highly complex functional sequences that are easily confused with transmembrane domains. Such confusion would obviously affect the discovery of secreted proteins. Transmembrane proteins are important drug targets, but very few transmembrane protein structures have been determined experimentally; hence, prediction of the structures is essential. In the field of structure prediction, researchers do not make assumptions about organisms, so there is a need for a general signal peptide predictor

Machine Learning Approaches to Modeling the Physiochemical Properties of Small Peptides

Peptide and protein sequences are most commonly represented as a strings: a series of letters selected from the twenty character alphabet of abbreviations for the naturally occurring amino acids. Here, we experiment with representations of small peptide sequences that incorporate more physiochemical information. Specifically, we develop three different physiochemical representations for a set of roughly 700 HIV–I protease substrates. These different representations are used as input to an array of six different machine learning models which are used to predict whether or not a given peptide is likely to be an acceptable substrate for the protease. Our results show that, in general, higher–dimensional physiochemical representations tend to have better performance than representations incorporating fewer dimensions selected on the basis of high information content. We contend that such representations are more biologically relevant than simple string–based representations and are likely to more accurately capture peptide characteristics that are functionally important.Singapore-MIT Alliance (SMA

Peptides and Peptidomimetics for Antimicrobial Drug Design

The purpose of this paper is to introduce and highlight a few classes of traditional antimicrobial peptides with a focus on structure-activity relationship studies. After first dissecting the important physiochemical properties that influence the antimicrobial and toxic properties of antimicrobial peptides, the contributions of individual amino acids with respect to the peptides antibacterial properties are presented. A brief discussion of the mechanisms of action of different antimicrobials as well as the development of bacterial resistance towards antimicrobial peptides follows. Finally, current efforts on novel design strategies and peptidomimetics are introduced to illustrate the importance of antimicrobial peptide research in the development of future antibiotics

The relationship between structure and function in natural surfactant proteins

Surfactant activity is a property more commonly associated with small molecules than biological macromolecules. However, the significant advantages of improved biodegradability and biocompatibility that could be presented by natural surfactant proteins has elevated interest in a group of only a few proteins where intrinsic surfactant activity appears to be the primary function. Two examples of this group, ranaspumin-2 (Rsn-2) from the foam nests of the tungara frog and latherin, the surface active protein component of horse sweat, appear to be different from other surfactant proteins in the form of their activity. However, the exact molecular basis of this activity is poorly understood. This thesis describes work to rationalise surface activity and related properties in these unusual proteins. The properties of Rsn-2 and latherin including surface activity, interaction with lipid membranes and behaviour in solution were investigated to provide further insight into the characteristics that distinguish the surfactant proteins from both conventional surfactants and other proteins. A second protein component of the foam nests, ranaspumin-1 (Rsn-1), of previously unknown function was also found to be highly surface active and is proposed to function in a similar manner to Rsn-2. A model whereby Rsn-2 functions via a clamshell-like opening was tested through a combination of specialised NMR techniques and site-directed mutagenesis. The results identified features associated with surfactant activity, all of which were consistent with the model. The potential of Rsn-2 as a recombinant fusion partner for the production of functional surfactants or foams was proven by construction of a fluorescent conjugate. Solution state NMR was used to determine the structure of latherin. Information on the dynamic processes taking place in the molecule were derived by analysis of NMR relaxation data. The structure revealed is a super roll fold, similar to a single domain of the BPI-like proteins. A model is proposed whereby latherin recognises the air-water interface via three dynamic, hydrophobic loops at one end of its long cylindrical structure and then unfolds to expose its hydrophobic core at the air-water interface

A positively selected mutation in the WNV 2K peptide confers resistance to superinfection exclusion in vivo

AbstractMolecular epidemiologic studies of North American (NA) West Nile virus (WNV; Flaviviridae, Flavivirus) have documented the displacement of the introduced NY99 genotype with WN02. In addition, these studies have shown that particular substitutions are under positive selection. One occurs in the C-terminus of the NS4A coding sequence and results in a valine to methionine substitution at position nine of the 2K peptide. 2K-V9M confers the ability to overcome superinfection exclusion in vitro. We hypothesized that WNV strains bearing 2K-V9M have higher fitness than wildtype in Culex quinquefasciatus mosquitoes. Although infection rates and viral titers were not significantly different, virus dissemination rates were significantly higher with WNV 2K-V9M. As a super-infecting virus, WNV 2K-V9M was more successful than wildtype, however, in a mixed infection, 2K-V9M was not. These data support observations that 2K-V9M confers a context-specific selective advantage in mosquitoes and provides an in vivo mechanism for its positive selection

DE NOVO DESIGN OF ANTIMICROBIAL PEPTIDES FOR APPLICATION AS ANTI-INFECTIVE AGENTS

Ph.DNUS-ICL JOINT PH.D. (FoS