Proteins play critical roles in cellular processes of living organisms. It is therefore important to identify and characterize their key properties associated with their functions. Correlating protein’s structural, sequence and physicochemical properties of its amino acids (aa) with protein functions could identify some of the critical factors governing the specific functionality. We point out that not all functions of even well studied proteins are known. This, complemented by the huge increase in the number of newly discovered and predicted proteins, makes challenging the experimental characterization of the whole spectrum of possible protein functions for all proteins of interest. Consequently, the use of computational methods has become more attractive. Here we address two questions. The first one is how to use protein aa sequence and physicochemical properties to characterize a family of proteins. The second one focuses on how to use transcription factor (TF) protein’s domains to enhance accuracy of predicting TF DNA binding sites (TFBSs). To address the first question, we developed a novel method using computational representation of proteins based on characteristics of different protein regions (N-terminal, M-region and C-terminal) and combined these with the properties of protein aa sequences. We show that this description provides important biological insight about characterization of the protein functional groups. Using feature selection techniques, we identified key properties of proteins that allow for very accurate characterization of different protein families. We demonstrated efficiency of our method in application to a number of antimicrobial peptide families. To address the second question we developed another novel method that uses a combination of aa properties of DNA binding domains of TFs and their TFBS properties to develop machine learning models for predicting TFBSs. Feature selection is used to identify the most relevant characteristics of the aa for such modeling. In addition to reducing the number of required models to only 14 for several hundred TFs, the final prediction accuracy of our models appears dramatically better than with other methods. Overall, we show how to efficiently utilize properties of proteins in deriving more accurate solutions for two important problems of computational biology and bioinformatics.

Doctor of Philosophy / Department of Biological and Agricultural Engineering / Donghai Wang / Sorghum distillers dried grains with solubles (DDGS), canola and camelina meals are the main co-products resulting from grain-based ethanol or oil production. The main objective of this research was to study physicochemical properties of proteins isolated from DDGS, canola and camelina meals and their adhesion performance. Acetic acid-extracted sorghum protein (PI) from DDGS had superior adhesion performance in terms of dry, wet and soak adhesion strength compared to acetic acid-extracted sorghum protein (PF) from sorghum flour and aqueous ethanol-extracted sorghum protein (PII) from DDGS. PI had a significantly higher wet strength (3.15 MPa) than PII (2.17 MPa), PF (2.59 MPa), and soy protein without modification (1.63 MPa). The high content of hydrophobic amino acids in PI (57%) was likely the key factor responsible for high water resistance. Canola protein was extracted from canola meal and modified with different concentrations of NaHSO3 (0 to 15 g/L) during protein isolation. Unmodified canola protein showed the highest wet shear strength of 3.97 MPa cured at 190 °C. Adhesion strength of canola protein fractions extracted at pH 5.5 and pH 3.5 (3.9-4.1 MPa) was higher than the fraction extracted at pH 7.0. NaHSO3 slightly weakened adhesion performance of canola protein; however, it improved handling and flow-ability due to breaking of disulfide bonds in proteins. Albumin, globulin, and glutelins were isolated from camelina meal. Adhesion performance of globulin fraction behaved better than glutelin fraction. The greatest wet shear strength of globulin was 3.3 MPa at curing a temperature of 190 °C. Glutelin had a more protein aggregation compared with globulin, as indicated by higher crystallinity and thermal stability, and dense protein aggregate. This compact structure of glutelins may partially contribute to lower adhesion strength as compared to globulin.

The bacterium Streptococcus pneumoniae (pneumococcus), is considered to be a leading cause of morbidity and mortality globally, particularly in infants and the elderly. It is one of the most frequent causes of respiratory tract infections, which sporadically have the potential to develop into serious invasive symptoms including sepsis and meningitis. The development of effective vaccination against this pathogen is essential for reducing the morbidity and mortality it causes since the currently available vaccines can protect against only a limited number of the 100 pneumococci serotypes which target the polysaccharidic capsule of the bacterium. The potential use of conserved protein antigens could provide a defense to a wider range of serotypes and clonal types. The immunogenic properties of the proteins MalX and PrsA as well as their role in vital biological functions of S. pneumoniae have made them stand out as potential targets. MalX is a crucial membrane protein involved in the metabolism of maltose, whereas PrsA is a chaperone-like protein that is connected to the cell envelope. To understand these proteins' potential as vaccine candidates, it is essential to understand their immunogenic characteristics and physiological roles. In this project, we tried to characterize the two antigens to determine the functional significance of different regions and domains in antigen recognition and their expression dynamics in bacterial host. A better understanding of the antigenic properties of the PrsA and MalX proteins will drive the construction of improved versions of antigens for vaccine prototypes. Some approaches were used to clarify the structural characteristics and antigenic determinants associated with these proteins including, protein expression, purification, and structural characterization. Additionally, their expression in E. coli was examined using immunological assays including ELISA and Western blot. The identification of antigenic regions of these proteins also provides insight into how to develop epitope-based vaccinations that specifically target S. pneumoniae. This project discusses the possibility of using membrane vesicles (MVs) as a platform for vaccination. Membrane vesicles made from bacterial cells have innate immunogenic qualities that expose the immune system to a wide variety of antigens. Incorporating MalX and PrsA into such vesicles can improve the vaccine candidate's overall immunogenicity and effectiveness and trigger a stronger immune response against S. pneumoniae.