# NMRFx: An Integrated software suite for macromolecular NMR analysis

> **NIH NIH R01** · ADVANCED SCIENCE RESEARCH CENTER · 2022 · $323,420

## Abstract

Knowing the structure, dynamics and ligand binding specificity of proteins and nucleic acids is essential to
understanding the mechanisms of human disease and to the optimal design of molecules that can intervene
therapeutically in disease processes. Nuclear Magnetic Resonance (NMR) Spectroscopy is one of the most
versatile techniques for obtaining this molecular information. This tremendous value of NMR in biomedical
science is only realized through the application of powerful computational tools. Our goal in this project is to
continue the development of, and add powerful new features to, an integrated software application for the
computational analysis of NMR data. Having this effective software, NMRFx, for NMR is especially critical as
we realize that deep insight into macromolecular structure and function comes not from a single technique like
NMR, but from the complementary information from various techniques including NMR, X-ray crystallography,
and Cryo-electron microscopy. Scientists are no longer seeing these techniques as specialized techniques
usable by only domain experts, but as a collection of techniques that can and should be applied together.
Without this NMRFx software, researchers must otherwise use a variety of tools from different labs that have
different programming languages, scripting tools, naming conventions, graphical interfaces, documentation
styles etc. The NMRFx software that is the subject of this project integrates signal processing, data analysis,
visualization and macromolecular structure calculations based on NMR data. In the current project this
software will be enhanced with the addition of an integrated deep learning library that will allow new types of
data analyses using these new tools that are making major advances in scientific research. The performance
of the software will be dramatically enhanced by the addition of a software library that allows computations to
be dispatched to high-performance hardware like GPUs (graphical processing units) and FPGAs (Field
Programmable Gate Arrays). This performance enhancement will allow much faster computations and allow
use of algorithms that were previously too slow to use in interactive analyses. We will also complete the
implementation of the remaining features necessary for the full analysis of NMR data. We propose that by
providing new and experienced users with an enhanced version of our software application that has a common
installation protocol, interface style, data structures, and overall design, we can substantially lower barriers to
the use of NMR. NMRFx is making the use of NMR techniques more accessible to a wider population of
researchers. The software, including the addition of the deep learning and acceleration libraries, will increase
the contributions of NMR in a broad range of biological research areas that impact on human health.

## Key facts

- **NIH application ID:** 10367499
- **Project number:** 2R01GM123012-05
- **Recipient organization:** ADVANCED SCIENCE RESEARCH CENTER
- **Principal Investigator:** Bruce A Johnson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $323,420
- **Award type:** 2
- **Project period:** 2017-09-15 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10367499

## Citation

> US National Institutes of Health, RePORTER application 10367499, NMRFx: An Integrated software suite for macromolecular NMR analysis (2R01GM123012-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10367499. Licensed CC0.

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