No description available.

The human protein kinase superfamily consists of over 500 members that individually control specific aspects of cell behavior and collectively control the complete range of cellular processes. That such a large group of proteins is able to uniquely diversify and establish individual identities while retaining common enzymatic function and significant sequence/structural conservation is remarkable. The means by which this is achieved is poorly understood, and we have begun to examine the issue by performing a comparative analysis of the catalytic domain of protein kinases. A novel approach for protein structural alignment has revealed a high degree of similarity found across the kinase superfamily, with variability confined largely to a single region thought to be involved in substrate binding. The similarity detected is not limited to amino acids, but includes a group of conserved water molecules that play important structural roles in stabilizing critical residues and the fold of the kinase domain. The development of a novel technique for identifying kinase substrates on a large scale directly from cell lysate has revealed that substrate specificity is not what discriminates the closely related p38α and β mitogen-activated protein kinases. Instead cellular localization appears to be their distinguishing characteristic, at least during myoblast differentiation. Together these results highlight the extent of conservation, as well as the minimal variability, that is found in the catalytic domain of all protein kinase superfamily members, and that while distantly related kinases may be distinguished by substrate specificity, closely related kinases are likely to be distinguished by other factors. Although these results focus on representative members of the kinase superfamily, they give insight as to how all protein kinases likely diversified and established unique non-redundant identities. In addition, the novel techniques developed and presented here for structural alignment and substrate discovery offer new tools for studying molecular biology and cell signaling.

The human protein kinase superfamily consists of over 500 members that individually control specific aspects of cell behavior and collectively control the complete range of cellular processes. That such a large group of proteins is able to uniquely diversify and establish individual identities while retaining common enzymatic function and significant sequence/structural conservation is remarkable. The means by which this is achieved is poorly understood, and we have begun to examine the issue by performing a comparative analysis of the catalytic domain of protein kinases. A novel approach for protein structural alignment has revealed a high degree of similarity found across the kinase superfamily, with variability confined largely to a single region thought to be involved in substrate binding. The similarity detected is not limited to amino acids, but includes a group of conserved water molecules that play important structural roles in stabilizing critical residues and the fold of the kinase domain. The development of a novel technique for identifying kinase substrates on a large scale directly from cell lysate has revealed that substrate specificity is not what discriminates the closely related p38α and β mitogen-activated protein kinases. Instead cellular localization appears to be their distinguishing characteristic, at least during myoblast differentiation. Together these results highlight the extent of conservation, as well as the minimal variability, that is found in the catalytic domain of all protein kinase superfamily members, and that while distantly related kinases may be distinguished by substrate specificity, closely related kinases are likely to be distinguished by other factors. Although these results focus on representative members of the kinase superfamily, they give insight as to how all protein kinases likely diversified and established unique non-redundant identities. In addition, the novel techniques developed and presented here for structural alignment and substrate discovery offer new tools for studying molecular biology and cell signaling.

A topic of research that is frequently studied in Structural Biology is the problem of determining the degree of similarity between two protein structures. The most common solution is to perform a three dimensional structural alignment on the two structures. Rigid structural alignment algorithms have been developed in the past to accomplish this but treat the protein molecules as immutable structures. Since protein structures can bend and flex, rigid algorithms do not yield accurate results and as a result, flexible structural alignment algorithms have been developed. The problem with these algorithms is that the protein structures are represented using thousands of atomic coordinate variables. This results in a great computational burden due to the large number of degrees of freedom required to account for the flexibility. Past research in dimensionality reduction techniques has shown that a linear dimensionality reduction technique called Principal Component Analysis (PCA) is well suited for high dimensionality reduction. This thesis introduces a new flexible structural alignment algorithm called FlexSADRA, which uses PCA to perform flexible structural alignments. Test results show that FlexSADRA determines better alignments than rigid structural alignment algorithms. Unlike existing rigid and flexible algorithms, FlexSADRA addresses the problem in a significantly lower dimensionality problem space and assesses not only the structural fit but the structural feasibility of the final alignment.

A topic of research that is frequently studied in Structural Biology is the problem of determining the degree of similarity between two protein structures. The most common solution is to perform a three dimensional structural alignment on the two structures. Rigid structural alignment algorithms have been developed in the past to accomplish this but treat the protein molecules as immutable structures. Since protein structures can bend and flex, rigid algorithms do not yield accurate results and as a result, flexible structural alignment algorithms have been developed. The problem with these algorithms is that the protein structures are represented using thousands of atomic coordinate variables. This results in a great computational burden due to the large number of degrees of freedom required to account for the flexibility. Past research in dimensionality reduction techniques has shown that a linear dimensionality reduction technique called Principal Component Analysis (PCA) is well suited for high dimensionality reduction. This thesis introduces a new flexible structural alignment algorithm called FlexSADRA, which uses PCA to perform flexible structural alignments. Test results show that FlexSADRA determines better alignments than rigid structural alignment algorithms. Unlike existing rigid and flexible algorithms, FlexSADRA addresses the problem in a significantly lower dimensionality problem space and assesses not only the structural fit but the structural feasibility of the final alignment.

The human protein kinase superfamily consists of over 500 members that individually control specific aspects of cell behavior and collectively control the complete range of cellular processes. That such a large group of proteins is able to uniquely diversify and establish individual identities while retaining common enzymatic function and significant sequence/structural conservation is remarkable. The means by which this is achieved is poorly understood, and we have begun to examine the issue by performing a comparative analysis of the catalytic domain of protein kinases. A novel approach for protein structural alignment has revealed a high degree of similarity found across the kinase superfamily, with variability confined largely to a single region thought to be involved in substrate binding. The similarity detected is not limited to amino acids, but includes a group of conserved water molecules that play important structural roles in stabilizing critical residues and the fold of the kinase domain. The development of a novel technique for identifying kinase substrates on a large scale directly from cell lysate has revealed that substrate specificity is not what discriminates the closely related p38α and β mitogen-activated protein kinases. Instead cellular localization appears to be their distinguishing characteristic, at least during myoblast differentiation. Together these results highlight the extent of conservation, as well as the minimal variability, that is found in the catalytic domain of all protein kinase superfamily members, and that while distantly related kinases may be distinguished by substrate specificity, closely related kinases are likely to be distinguished by other factors. Although these results focus on representative members of the kinase superfamily, they give insight as to how all protein kinases likely diversified and established unique non-redundant identities. In addition, the novel techniques developed and presented here for structural alignment and substrate discovery offer new tools for studying molecular biology and cell signaling.

The human protein kinase superfamily consists of over 500 members that individually control specific aspects of cell behavior and collectively control the complete range of cellular processes. That such a large group of proteins is able to uniquely diversify and establish individual identities while retaining common enzymatic function and significant sequence/structural conservation is remarkable. The means by which this is achieved is poorly understood, and we have begun to examine the issue by performing a comparative analysis of the catalytic domain of protein kinases. A novel approach for protein structural alignment has revealed a high degree of similarity found across the kinase superfamily, with variability confined largely to a single region thought to be involved in substrate binding. The similarity detected is not limited to amino acids, but includes a group of conserved water molecules that play important structural roles in stabilizing critical residues and the fold of the kinase domain. The development of a novel technique for identifying kinase substrates on a large scale directly from cell lysate has revealed that substrate specificity is not what discriminates the closely related p38α and β mitogen-activated protein kinases. Instead cellular localization appears to be their distinguishing characteristic, at least during myoblast differentiation. Together these results highlight the extent of conservation, as well as the minimal variability, that is found in the catalytic domain of all protein kinase superfamily members, and that while distantly related kinases may be distinguished by substrate specificity, closely related kinases are likely to be distinguished by other factors. Although these results focus on representative members of the kinase superfamily, they give insight as to how all protein kinases likely diversified and established unique non-redundant identities. In addition, the novel techniques developed and presented here for structural alignment and substrate discovery offer new tools for studying molecular biology and cell signaling.