Technology and Research Development Project #3: Bioinformatics is responsible for the development of tools and methods for the analysis of data from the other technology projects that are part of this proposal. This takes advantage of the data analytics and informatics strengths of UTSW and UCSC to help produce a broad-scale molecular and chemical annotation of large libraries of natural products and botanicals. Our deliverable will be a data and data analytics pipeline that will help define a cytological signature to chemical entities, map chemical entities to signaling pathways they interrupt, help identify principal nodes in normal and diseased biological networks that natural products and botanicals target, and help indicate potential therapeutic/dietary applications for these compounds. This will be accomplished by using a series of data analysis methods including 1) Clustering analysis of natural products fractions and botanical activity by the affinity propagation clustering (APC) algorithm. This algorithm can be applied to data features generated by cytological profiling, unbiased metabolomics and FUSION. 2) Use of Euclidean distance distribution to generate a similarity matrix for all of the chemical and genetic perturbagens in FUSION to obtain ?guilt by association correlations. 1) Develop tools for intuitive data visualization based on phylogenetic tree algorithms. These tools will be developed for visualization of not only the data generated by TRD#1 and TRD#2, but by other large scale methods looking at natural product mechanisms of action. The ultimate goal of the bioinformatics component of this grant is to drive the generation of hypotheses on the biological activity of the chemical being evaluated and provide this information to the scientific community.

Public Health Relevance

statement: The overarching goal of this CANPIT proposal is use innovative phenotypic screening approaches to identify the mechanisms of action of botanicals and natural products. The key to successful implementation of these approaches relies on the development and use of sophisticated bioinformatics platforms to analyze the data and provide meaningful correlations to provide mechanistic insight into natural products and botanicals.

Agency
National Institute of Health (NIH)
Institute
National Center for Complementary & Alternative Medicine (NCCAM)
Type
Biotechnology Resource Cooperative Agreements (U41)
Project #
5U41AT008718-06
Application #
9736630
Study Section
Special Emphasis Panel (ZAT1)
Project Start
Project End
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
6
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California Santa Cruz
Department
Type
DUNS #
125084723
City
Santa Cruz
State
CA
Country
United States
Zip Code
95064
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Pye, Cameron R; Bertin, Matthew J; Lokey, R Scott et al. (2017) Reply to Skinnider and Magarvey: Rates of novel natural product discovery remain high. Proc Natl Acad Sci U S A 114:E6273
Vaden, Rachel M; Oswald, Nathaniel W; Potts, Malia B et al. (2017) FUSION-Guided Hypothesis Development Leads to the Identification of N?,N?-Dimethyladenosine, a Marine-Derived AKT Pathway Inhibitor. Mar Drugs 15:
Pye, Cameron R; Bertin, Matthew J; Lokey, R Scott et al. (2017) Retrospective analysis of natural products provides insights for future discovery trends. Proc Natl Acad Sci U S A 114:5601-5606
Kalwat, Michael A; Wichaidit, Chonlarat; Nava Garcia, Alejandra Y et al. (2016) Insulin promoter-driven Gaussia luciferase-based insulin secretion biosensor assay for discovery of ?-cell glucose-sensing pathways. ACS Sens 1:1208-1212