The Office of Dietary Supplements (ODS) of the National Institutes of Health (NIH)

Grant Abstract: NP-MRD: Natural Products Magnetic Resonance Database

Grant Number: 1U24AT010811-01
PI Name: Cort
Project Title: NP-MRD: Natural Products Magnetic Resonance Database

Abstract: This project will develop the Natural Products Magnetic Resonance Database (NP-MRD), the central repository for all NMR data generated by the natural products community. The core of the NP-MRD will be an open-access, web-enabled, community-focused, FAIR-compliant database containing NMR spectra and structures for all known natural products (estimated to be ~350,000 structures). It will contain (i) legacy (curator-backfilled) NMR data of NPs derived from the literature, existing public databases, and “private” data archives, (ii) new NMR data submitted by depositors for novel NPs, and (iii) heuristically calculated NMR chemical shifts for all NPs and, eventually, density functional theory (DFT) calculated chemical shifts all NPs. Data deposition will be both rapid (<5 minutes) and simple. The NP-MRD will be closely integrated (through data exchange agreements) with “sister” databases containing MS, biosynthetic gene cluster, and bioactivity data. It will provide rigorous validation and data checking (QA/QC) to ensure that submitted assignment data is of the highest quality. Validation and analytical summary reports will be provided following data deposition. The NP-MRD will also offer powerful database search, filtering, and querying tools to facilitate spectral, structure and taxonomic searches or selections. In addition to data storage, retrieval, and curation, the NP-MRD will host an extensive suite of software tools for NP research. These will include tools for spectral dereplication, structure validation, and NMR-based profiling of complex mixtures. The NP-MRD will also provide tools for spectral and structural visualization and comparison, as well as chemical-space network visualization and chemo-taxonomic comparisons. Additionally the NP-MRD will offer tools for NMR spectral prediction and simulation. A core principle of the NP-MRD is that availability of high-quality, value-added reporting and interactive tools will encourage user engagement and data deposition. Software produced and hosted by the NP-MRD will be open-source and open-access. To enhance interoperability, portions of the NP-MRD and associated software will be “dockerized” on cloud computing resources and, if needed, converted to web-based APIs. The NP-MRD’s deposition tools will be designed to work with participating journals’ paper-submission software. The NP-MRD team will engage thought leaders, journal editors, and database managers to develop consensus protocols regarding data deposition, data format standards, and data exchange—all compliant with community-established policies and standards. Our proposed work has already gained traction, as shown by many strong letters of support from key stakeholders. The NP- MRD will offer online and on-site (at conferences) training on use of its software for NP dereplication and identification. Resources covering tips, tricks, and techniques in NMR spectroscopy and NMR software will be made available on the NP-MRD website and through web-based “office hours” to help users, depositors, and the general NP community. NP-MRD’s long-term goal is to advance and enable natural products research by archiving and adding real value to natural product NMR data. PUBLIC HEALTH RELEVANCE: The Natural Products Magnetic Resonance Database (NP-MRD) will be an electronically accessible data repository allowing key information about the world’s natural products to be openly shared and rapidly queried by the global scientific community. It will be particularly important for those scientists using Nuclear Magnetic Resonance (NMR) spectroscopy to study natural products to study or discover new natural products that may one day be used to improve health or cure disease. The NP-MRD will become an important hub for all natural product chemists around the world, allowing them to share their data, to learn from each other, and to accelerate the translation of their discoveries to benefit humanity.

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