A toolset for the solid-state NMR-based 3D structure calculation of proteins

Mehdi Rahimi; Yeongjoon Lee; Huong Nguyen; Abigail Chiu; Woonghee Lee

doi:10.1016/j.jmr.2022.107214

A toolset for the solid-state NMR-based 3D structure calculation of proteins

J Magn Reson. 2022 Jun:339:107214. doi: 10.1016/j.jmr.2022.107214. Epub 2022 Apr 2.

Authors

Mehdi Rahimi¹, Yeongjoon Lee², Huong Nguyen³, Abigail Chiu⁴, Woonghee Lee⁵

Affiliations

¹ Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA. Electronic address: mehdi.rahimi@ucdenver.edu.
² Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA.
³ Computer Science Department, University of Wisconsin-Madison, Madison, WI 53706, USA; URS Program, University of Wisconsin-Madison, Madison, WI 53706, USA. Electronic address: htnguyen23@wisc.edu.
⁴ Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA. Electronic address: abigail.chiu@ucdenver.edu.
⁵ Department of Chemistry, University of Colorado Denver, Denver, CO 80204, USA. Electronic address: woonghee.lee@ucdenver.edu.

PMID: 35490563
DOI: 10.1016/j.jmr.2022.107214

Abstract

Proteins are the building blocks of life. The shape of the protein determines its functionality. This understanding of the 3D structure of proteins has applications in study of diseases, medicine, body functions, and other aspects of life. Nuclear magnetic resonance (NMR) has been a powerful tool for researchers to get insight into the metabolome of cells, tissues, biofluids, secretions, and overall etiology of the disease state. Solid-state NMR (ssNMR) spectroscopy is used for samples that have low solubility in common NMR solvents. The use of ssNMR for 3D structure determination of proteins has been on the rise in the recent years especially for such samples. Still, one of the challenges that researchers face in this area is a shortage of easy and user-friendly computational aids. To address this, we are introducing our comprehensive software solution by automating every step of the process and essentially transforming the task into a few clicks of the mouse. The workflow for 3D structure determination has been simplified down to only a few procedures. Starting with selection of an ssNMR spectrum, user can receive its 3D structure along with an abundance of statistical information and validation tools using our software. We have tested this toolset to test the usefulness and user-friendliness with different data sets available on biological magnetic resonance bank (BMRB).

Keywords: AUDASA; Automation; POKY; PONDEROSA-C/S; SPARKY; Solid-state NMR; Structure calculation.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.
Research Support, Non-U.S. Gov't

MeSH terms

Magnetic Resonance Spectroscopy
Nuclear Magnetic Resonance, Biomolecular / methods
Proteins* / chemistry
Software*
Workflow

Substances

Proteins