# Computational Core

> **NIH NIH U2C** · BATTELLE PACIFIC NORTHWEST LABORATORIES · 2020 · $494,853

## Abstract

COMPUTATIONAL CORE SUMMARY
The capability to chemically identify thousands of metabolites and other chemicals in clinical samples will revolutionize
the search for environmental, dietary, and metabolic determinants of disease. Through innovations in computational
chemistry, we propose to overcome a significant, long-standing obstacle in the field of metabolomics: the absence of
methods for accurate and comprehensive identification of small molecules without relying on data from analysis of authentic
chemical standards. A paradigm shift in metabolomics, we will use gas-phase molecular properties, collision cross section,
MS/MS spectra, accurate mass, and isotopic distribution that can be both accurately predicted computationally and
consistently measured experimentally, and which can thus be used for comprehensive identification of the metabolome. The
outcomes of this proposal directly advance the mission and goals of the NIH Common Fund by: (i) accurately calculating
chemical properties using an integrated, scalable high-performance computational chemistry pipeline, (ii) generating in
silico reference data for an initial target of 500,000 molecules comprising both known and novel metabolites, (iii) developing
and validating a multi-property feature matching approach for unambiguous chemical identification in biomedical samples,
and (iv) disseminating the computational tools, algorithms, and resources . This work is significant because it enables
comprehensive and confident chemical measurement of the metabolome. This work is innovative because it utilizes a high-
throughput, high-accuracy, quantum-chemistry-based computational and chemical informatics platform to predict physical-
chemical properties of metabolites.

## Key facts

- **NIH application ID:** 9968357
- **Project number:** 5U2CES030170-03
- **Recipient organization:** BATTELLE PACIFIC NORTHWEST LABORATORIES
- **Principal Investigator:** David Wishart
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $494,853
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9968357

## Citation

> US National Institutes of Health, RePORTER application 9968357, Computational Core (5U2CES030170-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9968357. Licensed CC0.

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