About

Chad M. Rienstra is a Professor of Biochemistry and Co-Investigator at the National Magnetic Resonance Facility at Madison (NMRFAM) at the University of Wisconsin–Madison. He holds a B.S. from Macalester College, a Ph.D. from the Massachusetts Institute of Technology, and completed postdoctoral training at Columbia University. His professional role involves leading research in the development and application of nuclear magnetic resonance (NMR) methods to study biological systems. The Rienstra Lab focuses on advancing solid-state NMR spectroscopy techniques and their use in structural biology, particularly in understanding complex biomolecular structures and interactions. Professor Rienstra's work supports the study of proteins and other biomolecules relevant to health and disease, including neurodegenerative disorders such as Parkinson's disease.

Research topics

• Biology
• Biochemistry
• Computational biology
• Computer Science
• Virology
• Microbiology
• Pharmacology
• Botany
• Genetics
• Chemistry
• Medicine

Selected publications

• A structural model of toxic amyloid oligomers involved in type 2 diabetes

  Proceedings of the National Academy of Sciences · 2026-01-26 · 2 citations

  articleOpen access

  Amyloid oligomers of the human islet amyloid polypeptide (hIAPP) are a likely cytotoxic species driving β-cell death in type 2 diabetes, but their transient nature has precluded atomic-level structural characterization. We obtained a high-resolution structure of a physiologically relevant hIAPP oligomer. Using 2D IR spectroscopy, we identified three substitutions that slowed aggregation sufficiently for comprehensive 2D/3D NMR analysis while retaining the key wild-type structural features and cytotoxicity. The structural model reveals a dimeric assembly with N-terminal helices and a kink that facilitates an intermolecular β-sheet. The β-sheet spans the famous FGAILS portion of the sequence, helping to explain species-specific diabetes susceptibility and the origin of early-onset familial mutations. The integrated 2D IR/NMR strategy provides a unique approach to obtaining high-resolution structures of amyloid oligomers.

  PublisherDOI

• Probing Solution Dynamics of Tissue Factor Using Molecular Dynamics Simulations Guided by NMR Chemical Shifts

  The Journal of Physical Chemistry B · 2026-03-27

  articleOpen access

  Structure and dynamics of proteins are key to understanding their roles in biological systems and provide a framework for rational development of novel therapeutics. Here, we combine NMR chemical shifts (CSs), X-ray crystal structures, and molecular dynamics (MD) simulations to characterize the extracellular domain of human tissue factor, i.e., soluble tissue factor (sTF), a protein that is involved in the initiation of the blood clotting process by forming a complex with the coagulation factor VIIa (fVIIa). Starting with the X-ray structures, solution NMR CSs were incorporated as restraints in CS-guided MD simulations to obtain structures in agreement with the NMR solution data of the protein. Our results reveal a dynamic ensemble of configurations in a loop that is key to sTF interaction with fVIIa. Key residues have been identified in the fVIIa-binding loop with divergent backbone and/or side-chain configurations to account for the loop dynamics. We demonstrate that the resulting structural ensemble from the incorporation of solution NMR CSs provides a better description of sTF dynamics in solution. The integrated approach used in this study can be applied to provide a better molecular guide for therapeutics that specifically target sTF.

  PublisherOA PDFDOI

• NMRhub: An NMR Data Ecosystem Spanning the Complete Data Lifecycle

  Journal of Molecular Biology · 2026-03-01

  article
  PublisherDOI

• Ultrahigh-resolution solid-state NMR for high–molecular weight proteins on GHz-class spectrometers

  Science Advances · 2025-07-23 · 7 citations

  articleOpen accessSenior authorCorresponding

  Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique with broad impact across the physical and life sciences, and ultrahigh field (UHF), gigahertz-class NMR spectrometers offer exceptional performance, including superior resolution and sensitivity. In solid-state NMR (SSNMR), resolution is primarily constrained by instrumentation rather than molecular tumbling, making it well suited for studying large and complex systems. To fully leverage UHF magnets for SSNMR, it is essential to eliminate line broadening arising from magnetic field drift and couplings among the nuclear spins. We address these challenges using external 2 H lock to compensate for the field drift and long-observation-window band-selective homonuclear decoupling to suppress 13 C homonuclear couplings. We achieve better than 0.2–parts per million resolution in proteins up to 144 kilodalton, enabling unique site resolution for more than 500 amide backbone pairs in two-dimensional experiments. This exceeds the resolution available from solution NMR for large biological molecules, greatly expanding the potential of gigahertz-class NMR for research in life sciences.

  PublisherDOI

• Top-Down Scoring of Spectral Fitness by Image Analysis for Protein Structure Validation

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-06

  preprintOpen accessSenior authorCorresponding

  ABSTRACT Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for protein structure determination, but traditional approaches require extensive manual assignment of hundreds to thousands of resonances. Here we present NMRFAM-BPHON, a novel “top-down” approach that treats experimental NMR spectra as continuous grayscale images and quantitatively scores the agreement with simulated spectra generated from candidate protein structures. This method does not require complete resonance assignments, though it can incorporate experimental chemical shifts when available to improve performance. The simulated spectra are generated from postulated resonance assignments, which can be derived either from empirical database predictions, direct interpretation, or a hybrid combination. BPHON employs a physics-based approximate polarization transfer model to predict cross-peak intensities from the internuclear distances in the decoy structure, and models the peak lineshapes using empirical, bulk T 2 relaxation rates and literature values for scalar couplings. The resulting simulated spectra are scored relative to the experimental data by normalized cross correlation, yielding a fitness score between 0 and 1. We demonstrate BPHON’s ability to discriminate structural models, particularly in the case of 13 C-detected magic angle spinning solid-state NMR spectra. The software is packaged with a user-friendly graphical user interface for ChimeraX, enabling advanced NMR analysis accessible without requiring extensive manual analysis.

  PublisherOA PDFDOI

• Abstract 2440 The Biophysical Interaction Between (-)-epi-gallocatechin gallate and Alpha-Synuclein Fibrils

  Journal of Biological Chemistry · 2025-05-01

  articleOpen accessSenior author

  The cellular lipid landscape serves as a critical determinant of cellular health, particularly in neurons where precise regulation of membrane composition is essential for proper function.This presentation will explore how alterations in cellular lipid composition and distribution influence the formation and function of membrane contact sites -specialized regions where organelles come into proximity to exchange materials and information.We will discuss how alteration of these essential cellular interfaces can lead to compromised organelle function, altered calcium signaling, and ultimately contribute to neurodegeneration.By understanding the fundamental relationship between lipids, membrane contact sites, and organelle communication, we gain crucial insights into potential therapeutic strategies for neurodegenerative disorders.Our findings highlight the importance of maintaining proper lipid homeostasis for neuronal health and survival.

  PublisherOA PDFDOI

• Binding Sites of a Positron Emission Tomography Radioligand with Nanomolar Affinity to Alpha-Synuclein Fibrils

  Microscopy and Microanalysis · 2025-07-01

  articleOpen access
  PublisherOA PDFDOI

• Top–Down Scoring of Spectral Fitness by Image Analysis for Protein Structure Validation

  Journal of Chemical Information and Modeling · 2025-12-19 · 1 citations

  articleOpen accessSenior authorCorresponding

  Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for protein structure determination, but traditional approaches require extensive manual assignments of hundreds to thousands of resonances. Here, we present NMRFAM-BPHON, a novel “top–down” approach that treats experimental NMR spectra as continuous grayscale images and quantitatively scores the agreement with simulated spectra generated from candidate protein structures. This method does not require complete resonance assignments, although it can incorporate experimental chemical shifts when available to improve performance. The simulated spectra are generated from postulated resonance assignments, which can be derived from empirical database predictions, direct interpretations, or a hybrid combination. BPHON employs a physics-based approximate polarization transfer model to predict cross-peak intensities from the internuclear distances in the decoy structure and models the peak line shapes using empirical, bulk T2 relaxation rates and literature values for scalar couplings. The resulting simulated spectra are scored relative to the experimental data by normalized cross correlation, yielding fitness scores between 0 and 1. We demonstrate BPHON’s ability to discriminate structural models, particularly in the case of 13C-detected magic angle spinning solid-state NMR spectra. The software is packaged with a user-friendly graphical user interface for ChimeraX, enabling advanced NMR analysis accessible without requiring extensive manual analysis.

  PublisherDOI

• Backbone assignment of a 28.5 kDa class A extended spectrum β-lactamase by high-field, carbon-detected solid-state NMR

  Biomolecular NMR Assignments · 2025-07-27 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• NMR Spectral Alignment Utilizing a CryoEM Motion Correction Algorithm

  Analytical Chemistry · 2025-12-15

  articleOpen accessCorresponding

  With recent advances in magic-angle spinning (MAS) solid-state NMR (SSNMR) resolution, precise spectral alignment has become a critical bottleneck in data processing workflows. While solution NMR employs deuterium lock systems, most SSNMR probes still lack this capability; though a lock corrects for magnet drift and instabilities, it is not alone sufficient to account for field gradients, sample temperature differences, and pulse sequence effects that can contribute to referencing errors among several data sets. These offsets become particularly problematic in the lengthy multidimensional experiments that provide the foundation for resonance assignment and structure determination procedures. Currently, researchers rely on manual alignment through visual peak inspection─a qualitative approach that often overemphasizes prominent, outlying peaks while overlooking subtle, global patterns. This subjective process becomes increasingly impractical for use cases with lower sensitivity, such as large proteins with thousands of peaks. To address these challenges, here we present Automated NMR Spectral Alignment (ANSA), a program that adapts cryo-electron microscopy motion correction principles to NMR spectroscopy. ANSA treats NMR spectra as images and applies cross-correlation functions to determine optimal alignment, improving cross-correlation scores from 0.33 to 1.00 in controlled tests and achieving 0.96 correlation in real-world applications with previously misaligned spectra. The algorithm successfully aligns spectra across varying experimental conditions, corrects shifts in long-duration experiments, and works with 2D and 3D data sets, with approaches that can be readily extended to additional dimensions. By eliminating human bias and providing objective, consistent spectral alignment, ANSA enhances scientific rigor, improves reproducibility between experiments, and enables automation of critical data processing steps. The software is freely available as an open-source tool, ready for integration into existing NMR workflows.

  PublisherDOI

Recent grants

• NMR User Program at NMRFAM

  NIH · $5.4M · 2021–2027

• NIH Grant R01GM075937

  NIH · $1.4M · 2011

• NIH Grant R01GM073770

  NIH · $2.6M · 2015

• CAREER: Multidimensional High Field Solid-State NMR Methods for Protein Structure Determination

  NSF · $735k · 2004–2011

• NIH Grant R01GM123455

  NIH · $5.0M · 2023

Frequent coauthors

• Robert G. Griffin

  Massachusetts Institute of Technology

  38 shared

• Charles D. Schwieters

  National Institute of Diabetes and Digestive and Kidney Diseases

  38 shared

• Benjamin J. Wylie

  Texas Tech University

  32 shared

• Donghua H. Zhou

  National Institute for Viral Disease Control and Prevention

  30 shared

• Leonard J. Mueller

  University of California, Riverside

  29 shared

• Martin D. Burke

  28 shared

• Andrew J. Nieuwkoop

  Rutgers, The State University of New Jersey

  28 shared

• Taras V. Pogorelov

  National Center for Supercomputing Applications

  27 shared

Labs

• Chad Rienstra LabPI

  NMR Methods and Biological Applications

Education

• B.S., Biochemistry

  University of Wisconsin–Madison

  1994

• Ph.D., Biochemistry

  University of Wisconsin–Madison

  1999