Biomedical subjects
Publications and source records attributed to Michael Kattah.
Disease-oriented, introductory medical curricula can help overcome educational and institutional barriers that separate aspiring translational scientists in PhD programs from the world of medicine.
Several proteomics platforms have emerged in the past decade that show great promise for filling in the many gaps that remain from earlier studies of the genome and from the sequencing of the human genome itself. This review describes applications of proteomics technologies to the study of autoimmune diseases. We focus largely on biased technology platforms that are capable of analyzing a large panel of known analytes, as opposed to techniques such as two-dimensional gel electrophoresis (2DIGE) or mass spectroscopy that represent unbiased approaches (as reviewed in 1). At present, the main analytes that can be systematically studied in autoimmunity include autoantibodies, cytokines and chemokines, components of signaling pathways, and cell-surface receptors. We review the most commonly used platforms for such studies, citing important discoveries and limitations that exist. We conclude by reviewing advances in biomedical informatics that will eventually allow the human proteome to be deciphered.
We have utilized a computational structure-based approach to identify nonpeptidic small organic compounds that bind to a human leukocyte antigen (HLA) DR1301 molecule (HLA-DR1301 or DR1301) and block the presentation of myelin basic protein peptide 152-165 (MBP 152-165) to T cells. A three-dimensional (3D) structure of DR1301 was derived by homology modeling followed by extensive molecular dynamics simulation for structural refinement. Computational structure-based database searching was performed to identify nonpeptidic small-molecule candidates from the National Cancer Institute (NCI) database containing over 150 000 compounds that can effectively interact with the peptide-binding groove of the HLA molecule. By in vitro testing of 106 candidate small molecules, two lead compounds were confirmed to specifically block IL-2 secretion by DR1301-restricted T cells in a dose-dependent and reversible manner. The specificity of blocking DR1301-restricted MBP presentation was further validated in a binding assay using an analogue of the most potent lead compound. Computational docking was performed to predict the three-dimensional binding model of these confirmed small molecule blockers to the DR1301 molecule and to gain structural insight into their interactions. Our results suggest that computational structure-based searching is an effective approach to discover nonpeptidic small organic compounds to block the interaction between DR1301 and T cells. The nonpeptidic small organic compounds identified in this study are useful pharmacological tools to study the interactions between HLA molecules and T cells and a starting point for the development of a novel therapeutic strategy for the treatment of multiple sclerosis (MS) or other immune-related disorders.
Triggering receptors expressed on myeloid cells (TREM) are a family of recently discovered receptors that play important roles in innate immune responses, such as to activate inflammatory responses and to contribute to septic shock in response to microbial-mediated infections. To date, two TREM receptors in human and several homologs in mice have been identified. We report the 2.6 A resolution crystal structure of the extracellular domain of human TREM-1. The overall fold of the receptor resembles that of a V-type immunoglobulin domain with differences primarily located in the N-terminal strand. TREM-1 forms a "head-to-tail" dimer with 4100 A(2) interface area that is partially mediated by a domain swapping between the first strands. This mode of dimer formation is different from the "head-to-head" dimerization that existed in V(H)V(L) domains of antibodies or V domains of T cell receptors. As a result, the dimeric TREM-1 most likely contains two distinct ligand binding sites.
NKG2D recognizes multiple diverse ligands. Despite recent efforts in determining the crystal structures of NKG2D-ligand complexes, the principle governing this receptor-ligand recognition and hence the criteria for identifying unknown ligands of NKG2D remain central issues to be resolved. Here we compared the molecular recognition between NKG2D and three of the known ligands, UL16 binding protein (ULBP), MHC class I-like molecule, and retinoic acid early inducible gene as observed in the ligand-complexed crystal structures. The comparison shows that while the receptor uses a common interface region to bind the three diverse ligands, each ligand forms a distinct, but overlapping, set of hydrogen bonds, hydrophobic interactions, and salt bridges, illustrating the underlying principle of NKG2D-ligand recognition being the conservation in overall shape complementarity and binding energy while permitting variation in ligand sequence through induced fit recognition. To further test this hypothesis and to distinguish between diverse recognition and promiscuous ligand binding, four ULBP3 interface mutations, H21A, E76A, R82M, and D169A, were generated to each disrupt a single hydrogen bond or salt bridge. All mutant ULBP3 displayed reduced receptor binding, suggesting a specific, rather than promiscuous, receptor-ligand recognition. Mutants with severe loss of binding affect the receptor interactions that are mostly buried. Finally, a receptor-ligand recognition algorithm was developed to assist the identification of diverse NKG2D ligands based on evaluating the potential hydrogen bonds, hydrophobic interactions, and salt bridges at the receptor-ligand interface.
Screening for heavy-atom derivatives remains a time-consuming and cumbersome process that often results in non-isomorphous derivatives whose phases cannot be combined. Using lysozyme and FcgammaRIII receptor crystals as test cases, an improved soaking method for the generation of conventional heavy-atom derivatives has been developed. The method is based on soaking crystals in heavy-atom compounds for a very brief time at near-saturation concentrations. Compared with the current heavy-atom soaking method, which often takes days to achieve a derivatization, the quick-soak method completes a derivatization within 10 min to 2 h. The bound heavy-atom sites display higher peak heights from quick soaks than from overnight soaks in all cases tested. The quick-soak derivatives also preserved native-like diffraction resolution and data quality that was better than the prolonged-soak derivatives. Furthermore, derivatives generated by brief soaks are more isomorphous to the native than those generated by overnight soaks. Short soaks not only increase the likelihood of success in heavy-atom screening by reducing the pitfalls associated with prolonged soaks, such as lack of isomorphism and overall lattice disorder, but also have the potential to transform a time-consuming derivative screening into an 'on-the-fly' real-time derivatization process.