INTERPHOTORECEPTOR RETINOID BINDING PROTEIN: STRUCTURE AND FUNCTION
Ghosh Debashis
State University Of New York At Buffalocity: Buffalo country: United States (us)
Grant 5R01EY009412-17 from National Eye Institute
Abstract: Interphotoreceptor retinoid-binding protein (IRBP), the major soluble protein component of the interphotoreceptor matrix (IPM), has access to M¿ller cells, photoreceptors, and RPE. The mechanism by which IRBP protects retinoids from isomeric and oxidative degradation while targeting their delivery/release between the above cells during the visual cycle is poorly understood. Our long-term goal is to understand at the molecular level how IRBP accomplishes its remarkable functions. The mechanism underlying IRBP´s function or role in disease remains unknown because little is understood about its structure-function relationships. Its structure is unusual being composed of tandem homologous "modules" each ~300 residues in length. Although the individual modules have some functional activity, they are not equivalent, and important interactions take place between them. A critical gap is that little is known about the structure of the full-length protein and quaternary association of the "modules". However, obtaining IRBP at the concentrations needed for X-ray crystallography has been problematic as the protein denatures and precipitates when concentrated above 3 mgs/ml. In the current funding period, we purified to homogeneity full-length bovine, xenopus, human and zebrafish IRBPs in stable and functionally active pristine forms, devoid of fusion tags. These protein solutions can now be readily concentrated without denaturation or precipitation. We have optimized conditions for growing diffraction-quality crystals of these full-length IRBPs. Preliminary structure elucidation analysis for Xenopus IRBP suggests that the single module structure may be substantially modified in the full-length functional protein. Analyses of the expression, purification, stability, crystallization, ligand-binding, anti-oxidant activity, and homology-modeling data on these IRBPs have led to our hypothesis that quaternary association of the "modules" contributes to the structural scaffold(s) that bind and protect retinoids from degradation, and that the "modules" contribute unequally in these roles as well as in target retinoid delivery and release at the cell surface. This hypothesis will be evaluated through the following complementary aims. Aim 1 To determine the crystal structures of IRBPs composed of four modules (human, bovine, Xenopus), and two modules (zebrafish). Aim 2 To define binding-interactions of physiologically relevant ligands with IRBP and elucidate the molecular basis of IRBP´s protective/anti-oxidant roles. Aim 3 To determine how IRBP efficiently targets retinoid removal/delivery. Aim 4 To determine the structural and functional "hot-spots" in IRBP. The mechanism by which IRBP protects retinoids from isomeric and oxidative degradation while targeting their delivery/release between photoreceptors, retinal pigmented epithelium and M¿ller cells during the visual cycle is poorly understood. A critical gap is that little is known about the structure of the full-length protein and quaternary association of the "modules" that comprise the structure of IRBP. Analyses of the expression, purification, stability, crystallization, ligand-binding, anti-oxidant activity, and homology-modeling data on these IRBPs have led to our hypothesis that quaternary association of the "modules" contributes to the structural scaffold(s) that bind and protect retinoids from degradation, and that the "modules" contribute unequally in these roles as well as in targeting retinoid delivery and release at the cell surface
Keywords: 11 cis Retinal; 11-cis-Retinol; Address; Amino Acids; Antioxidants; base; Binding (Molecular Function); Biochemical; Cattle; Cell surface; Cells; Crystallization; Data; Disease; Docosahexaenoic Acids; Excision; Funding; Goals; Homology Modeling; Hot Spot; Human; Impairment; Individual; interstitial retinol-binding protein; Lead; Length; Ligand Binding; Ligands; Methods; Modification; Molecular; Molecular Structure; Mutation; Oleic Acids; Phase; Photoreceptors; Physiological; Precipitation; prevent; Protein Binding; protein structure function; Proteins; public health relevance; receptor; Recombinants; Resolution; Retina; Retinal Degeneration; Retinoids; Role; scaffold; Solutions; Spatial Distribution; Structure; Structure of retinal pigment epithelium; Structure-Activity Relationship; Testing; visual cycle; X-Ray Crystallography; Xenopus; Zebrafish
Project start date: 1993-07-01
Project end date: 2012-08-31
Budget start date: 1-SEP-2011
Budget end date: 31-AUG-2012
PFA/PA: PA-07-070
5R01EY009412-17 (2011): $378621
Sponsored Links Excellgen http://Excellgen.com
Grants awarded to Ghosh Debashis
STATISTICAL METHODS FOR THE ANALYSIS OF FUNCTIONAL GENOMIC DATA
Ghosh Debashis, Associate Professor Of Statistics
Pennsylvania State University-univ Parkcity: University Park country: United States (us)
Grant 5R01GM072007-05 from National Institute Of General Medical Sciences
Abstract: With the advent of high-throughput molecular assay technologies, biologists are having to deal with the analysis of high-dimensional genomic datasets. While statistical methods have been proposed for issues such as differential expression with these data, relatively little work has been done in terms of incorporating biological knowledge in the statistical analysis of high-throughput biological data in human disease settings. In this grant, we propose the development of statistical procedures for modeling of complex highdimensional biological data with an emphasis towards incorporating functional biological knowledge. The methods we propose will be implemented and distributed in software available to biologists. While the major biological data example in this grant is from a microarray experiment in cancer, the methods proposed here are general and can be developed for studying high-dimensional genotype-phenotype associations in other contexts. Given this, we propose the following aims 1. Development of hierarchical models for modelling of high-dimensional data in complex cell systems. 2. Development of statistical methodology for the identification of disease progressor genes. 3. Development of statistical methodology for assessing the role of functional pathways based on integration of gene expression and pathway data. 4. Development of statistical methodology for determining regions of overexpression and underexpression based on integration of gene expression and chromosomal location data. 5. Dissemination of these results in user-friendly statistical software
Keywords: Assay; base; Bio-Informatics; Bioassay; Bioinformatics; Biologic Assays; Biological; Biological Assay; Biology; Biometrics; Biometry; Biometry and Biostatistics; Biostatistics; Cancers; Cells; Collaborations; Complex; computer program/software; Computer Programs; Computer software; Data; Data Analysis, Statistical; Data Interpretation, Statistical; Data Set; Dataset; Development; Disease; disease/disorder; Disorder; experiment; experimental research; experimental study; functional genomics; Gene Expression; Genes; Genomics; Genotype; Grant; high throughput analysis; human disease; Investigators; Knowledge; Literature; Location; malignancy; Malignant Neoplasms; Malignant Tumor; member; method development; Method LOINC Axis 6; Methodology; Methods; Modeling; Molecular; neoplasm/cancer; overexpress; Overexpression; pathway; Pathway interactions; Performance; Phenotype; post-doc; post-doctoral; Postdoc; Postdoctoral Fellow; Principal Investigator; Procedures; Protein Overexpression; Research Associate; Research Personnel; Research Proposals; research study; Researchers; Role; Simulate; social role; Software; Specific qualifier value; Specified; Statistical Data Analyses; Statistical Data Interpretation; Statistical Methods; statistics/biometry; Students; System; System, LOINC Axis 4; Technology; user-friendly; Work
Project start date: 2004-09-01
Project end date: 2011-08-31
Budget start date: 1-SEP-2008
Budget end date: 31-AUG-2011
5R01GM072007-05 (2008): $203275
STATISTICAL METHODS FOR CANCER BIOMARKERS
Ghosh Debashis
University Of Michigan At Ann Arborcity: Ann Arbor country: United States (us)
Grant 2R01CA129102-04 from National Cancer Institute
Abstract: Biomarkers in cancer research are considered a central component of the expected improvements in prevention, detection, treatment and monitoring. There are potentially useful in many different types of studies and for many different purposes. Critical questions are whether they are valid to use, how can they be utilized in a valid and efficient way, and then if they are used how confident is one in the conclusions that are obtained. The use of biomarkers to advance understanding in cancer science has great potential, but also has some risks. Biomarkers are subject to uncertainty in their measurement, they may not be measuring exactly the quantity of interest, and since they are not explicitly measures of symptoms their use to aid in decision making or evaluation of therapies in a clinical setting is subject to uncertainty. Thus careful analysis of data from studies that involve biomarkers is crucial. There are many statistical challenges that arise in such studies. This application is concerned with developing, evaluating and applying statistical methods for data that involves biomarkers. The first aim is concerned with adding biomarkers to prediction models that may be used to stratify or classify patients. In this aim we develop approaches for integrating data from other sources to improve the prediction models. This research will have broad applicability. Innovative aspects involve the use of targeted ridge regression, multi-kernel machine modeling, and importance sampling to incorporate information from the literature. The second aim is concerned with clinical trials where the biomarker is to be used to evaluate a therapy as a surrogate endpoint. Because of the nature of the scientific question causal modeling is very natural in this context. We propose to develop both potential outcomes and structural causal models. We will investigate both single trial and multi trial settings with different endpoint types. The third aim is concerned with therapies that may be effective only for a subgroup of patients, and to be useful this subgroup is determined by a small number of predictive biomarkers. For data from randomized clinical trials we suggest a unified modeling approach, and will investigate the use of single index models with variable selection and multivariate partial least squares to aid in the subgroup identification. Inference following subgroup identification is challenging, we suggest an innovative scheme to simulate data under an appropriate null distribution. All 3 aims in this proposal address fundamental and significant problems in translational oncology research. Successful completion of the aims will have an impact both in understanding and utilizing biomarkers and also in developing statistical methodology that can be more broadly applicable to other fields. Biomarkers are considered a central component of the expected improvements in prevention, detection, treatment and monitoring in cancer. Critical questions about biomarkers are when and whether they are valid to use, how can they be utilized in a valid and efficient way, and then if they are used how confident is one in the conclusions that are obtained. This proposal is concerned with developing proper and efficient statistical methods for evaluation of biomarker data
Keywords: Address; anticancer research; biomarker; Cancer Science; Clinical; Clinical Trials; Data; Data Analyses; Data Set; Decision Making; Detection; Drug Formulations; Evaluation; frailty; Genes; Goals; improved; indexing; innovation; interest; Joints; Knowledge; Least-Squares Analysis; Literature; Malignant Neoplasms; Measurement; Measures; Methodology; Methods; Metric; Modeling; Monitor; Nature; novel; oncology; Outcome; Patients; predictive modeling; Prevention; prognostic; Proteins; Randomized Clinical Trials; randomized trial; Research; Research Design; Risk; Risk Factors; Sampling; Scheme; Simulate; simulation; Source; Statistical Methods; Subgroup; surrogacy; Surrogate Endpoint; Symptoms; Technology; Therapy Evaluation; Uncertainty; Validation
Relevance: Biomarkers are considered a central component of the expected improvements in prevention, detection, treatment and monitoring in cancer. Critical questions about biomarkers are when and whether they are valid to use, how can they be utilized in a valid and efficient way, and then if they are used how confident is one in the conclusions that are obtained. This proposal is concerned with developing proper and efficient statistical methods for evaluation of biomarker data
Project start date: 2007-07-01
Project end date: 2015-12-31
Budget start date: 1-JAN-2012
Budget end date: 31-DEC-2012
2R01CA129102-04 (2012): $209518
STRUCTURE AND FUNCTION OF INTEGRAL MEMBRANE ENZYME HUMAN AROMATASE
Ghosh Debashis, Professor
Upstate Medical Universitycity: Syracuse country: United States (us)
Grant 5R01GM086893-04 from National Institute Of General Medical Sciences
Keywords: (17Beta)-17-hydroxyandrost-4-en-3-one; 15q21.1; 16-alpha-Hydroxy-Estradiol; 16-Hydroxyestradiol; 17-beta-Hydroxy-4-Androsten-3-one; 2, 2`-(5-(1H-1, 2, 4-triazol-1-ylmethyl)-1, 3-phenylene)bis(2-methylpropionitrile); 2, 2`-[5-(1H-1, 2, 4-Triazol-1-ylmethyl)-1, 3-phenylene]di(2-methylpropionitrile); 2-(p-Aminophenyl)-2-ethylglutarimide; 3-(4-Aminophenyl)-3-ethyl-2, 6-piperidinedione; 3-Ethyl-3-(p-aminophenyl)-2, 6-dioxopiperidine; 4, 4`-(1H-1, 2, 4-triazol-1-yl-methylene)-bis(benzonitrile); 4-(5, 6, 7, 8-Tetrahydroimidazo(1, 5-a)pyridin-5-yl)benzonitrile; 4-Androstene-3, 17-dione; 4-hydroxy-4-androstene-3, 17-dione; 4-hydroxyandrost-4-ene-3, 17-dione; 4-hydroxyandrostene-3, 17-dione; 4-Hydroxyandrostenedione; 4-OHA; 4-OHAD; 6-methyleneandrosta-1, 4-diene-3, 17-dione; Active Sites; Adenosine 5`-(trihydrogen diphosphate), 2`-(dihydrogen phosphate), P`-5`-ester with 3-(aminocarbonyl)-1-beta-D-ribofuranosylpyridinium, inner salt; Adverse effects; Affinity; Alpha, alpha, alpha`, alpha`-tetramethyl-5-(1H-1, 2, 4-triazol-1-ylmethyl)-1, 3-benzenediacetonitrile; Amino Acids; aminoacid; Aminoglutethimid; Aminoglutethimide; Anabolism; anastrazole; anastrozole; Anastrozole (Arimidex); Androgenic Agents; Androgenic Compounds; Androgens; Androst-4-en-17beta-ol-3-one; Androst-4-ene-3, 17-dione; Androstenedione; Androstenedione Aromatase; Androstenedione Aromatase Inhibitor; Anti-Cancer Agents; Anti-Tumor Agents; Anti-Tumor Drugs; anticancer agent; anticancer drug; Antineoplastic Agents; Antineoplastic Drugs; Antineoplastics; Antiproliferative Agents; Antiproliferative Drugs; Aquadiol; Arensin; Arimidex; ARO; ARO1; Aromasin; Aromasine; Aromatase; Aromatase Cytochrome P450; Aromatase Inhibitors; Astra brand of anastrozole; AstraZeneca brand of anastrozole; base; Benzonitrile, 4, 4`-(1H-1, 2, 4-triazol-1-ylmethylene)bis-; Binding; Binding (Molecular Function); Biochemical; biosynthesis; Cancer Drug; Cancer of Breast; Catalysis; chemical structure function; Chemotherapeutic Agents, Neoplastic Disease; Chemotherapy-Hormones/Steroids; Chromosomes; clinical data repository; clinical data warehouse; Coenzyme II; Collaborations; Complex; CPV1; Crystallization; CYAR; CYP; CYP 19; CYP19; CYP19 Protein; CYP19A1; CYP19A1 gene; CYPXIX; Cytochrome P-450; Cytochrome P-450 CYP19; Cytochrome P-450 Enzyme System; Cytochrome P-450 Oxidase; Cytochrome P-450 Reductase; Cytochrome P-450(AROM); Cytochrome P450; Cytochrome P450 19; Cytochrome P450 19A1; Cytochrome P450 Reductase; Cytochrome P450, Family 19, Subfamily A, Polypeptide 1; Cytochrome P450, Subfamily XIX; Cytochrome P450, Subfamily XIX (Aromatization of Androgens); Cytochromes; Data; Data Banks; Data Bases; data repository; Data Set; Databank, Electronic; Databanks; Database, Electronic; Databases; Dataset; Dehydrogenases; delta-4-Androstenedione; Delta4-androsten-17beta-ol-3-one; design; designing; Dimenformon; Diogyn; Diogynets; Docking; Dose; EC 1.6.2.4; effective therapy; electron transfer; Electron Transport; Embryonic Tissue, Placenta; Endocrine Gland Secretion; Endocrine Therapy; Endoplasmic Reticulum; enzyme mechanism; enzyme substrate complex; Enzymes; Ergastoplasm; Estra-1, 3, 5(10)-trien-17-one, 3-hydroxy-; Estra-1, 3, 5(10)-triene-3, 16, 17-triol, (16alpha, 17beta)-; Estra-1, 3, 5(10)-triene-3, 17-diol (17beta)-; Estrace; Estradiol; Estradiol-17 beta; Estradiol-17beta; Estraldine; Estriol; Estrogen Synthase; Estrogen Synthase Inhibitor; Estrogen Synthetase; Estrogen Synthetase Inhibitor; Estrogenic Agents; Estrogenic Compounds; Estrogens; Estrone; Exemestane; experiment; experimental research; experimental study; Fadrozole; Femara; Ferrihemoprotein P-450 Reductase; Ferrihemoprotein P450 Reductase; Flavoproteins; Formestane; Future; gene product; Genes; Goals; Health; heavy metal lead; heavy metal Pb; Heme Proteins; Hemeproteins; hemoprotein; Hormonal Therapy; hormone therapy; Hormones; Human; Human body; Human Figure; Human, General; Hydrophobicity; improved; In Situ; inhibitor; inhibitor/antagonist; Investigation; Laboratories; Lead; Length; Lentaron; Letrozole; Ligands; lipid bilayer membrane; Lipid Bilayers; Macromolecular Structure; malignant breast neoplasm; Malignant neoplasm of breast; Malignant Tumor of the Breast; Man (Taxonomy); Man, Modern; member; Membrane; membrane structure; Methods; methyl group; Molecular; Molecular Interaction; Molecular Structure; Monitor; NAD phosphate; NAD(H) phosphate; NADH phosphate; NADP; NADPH; NADPH Cytochrome c Reductase; NADPH Cytochrome P-450 Oxidoreductase; NADPH Cytochrome P-450 Reductase; NADPH Cytochrome P450 Oxidoreductase; NADPH-Cytochrome P450 Reductase; NADPH-Ferrihemoprotein Reductase; NADPH-P450 Reductase; NADPH-Specific Cytochrome C Reductase; NADPH[{..}]ferrihemoprotein oxidoreductase; Nature; Nicotinamide-Adenine Dinucleotide Phosphate; Novartis Brand of Letrozole; novel; Ovocyclin; Ovocylin; oxidation reduction reaction; Oxidation-Reduction; Oxidoreductase; P-450AROM; P450; P450AROM; pathway; Pathway interactions; Pb element; Pharmacia brand of exemestane; Placenta; Placenta-Tissue, Cells; Placentoma, Normal; Placentome; POR; Predisposition; prevent; preventing; Process; Progynon; Property; Property, LOINC Axis 2; Proteins; Radiation, X-Rays; Radiation, X-Rays, Gamma-Rays; Reaction; Recombinants; Redox; Reductases; relational database; Reporting; Research; research study; Resolution; Roentgen Rays; Role; side effect; social role; Solutions; Specificity; Structure; structure function relationship; Structure-Activity Relationship; Substrate Specificity; Susceptibility; Temperature; Testing; Testosterone; Therapeutic Androgen; Therapeutic Androstenedione; Therapeutic Estradiol; Therapeutic Estrogen; Therapeutic Estrone; Therapeutic Hormone; Therapeutic Testosterone; therapy adverse effect; Trans-Testosterone; treatment adverse effect; Treatment Side Effects; Triphosphopyridine Nucleotide; Tumor-Specific Treatment Agents; Work; X-Radiation; X-Rays; Xrays; Zeneca brand of anastrozole
Relevance: Aromatase is a unique enzyme that makes all estrogens in the human body. We propose a research plan to unravel the molecular details of how aromatase works and how aromatase inhibitors prevent it from making estrogens. Results from this investigation will form the basis for future discovery of novel breast cancer drugs that are highly specific for aromatase but cause minimal side effects
Project start date: 2009-01-01
Project end date: 2012-12-31
Budget start date: 1-JAN-2011
Budget end date: 31-DEC-2011
PFA/PA: PA-07-253
5R01GM086893-04 (2011): $379346
7R01GM086893-03 (2010): $194683