About

Timothy Grant is a Morgridge Institute Investigator and an Assistant Professor of Biochemistry in the UW–Madison College of Agricultural and Life Sciences. Tim’s expertise is in developing and applying new methods for studying protein structure and function, with a focus on understanding the molecular basis of human disease.

Research topics

• Biology
• Artificial Intelligence
• Computer Science
• Biological system
• Biochemistry
• Cell biology
• Biophysics
• Optics
• Chemistry
• Computer vision
• Physics

Selected publications

• Improved cryo-EM reconstruction of sub-50 kDa complexes using 2D template matching

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-09-16 · 1 citations

  preprintOpen access

  Visualizing the structures of small proteins and complexes has been a longstanding challenge in single-particle cryo-EM. Some of these targets have been successfully resolved by binding to antibody fragments (Fabs) or fusing with external scaffolds to increase their size. Recent advances in conventional single-particle techniques have enabled the determination of an increasing number of structures smaller than 100 kDa, achieving resolutions relevant to drug research. Compared to X-ray crystallography, cryo-EM preserves the near-native states of biomolecules, can resolve structural heterogeneity, and has the potential to apply to a wide range of targets. In this work, we demonstrate that the alignment and reconstruction of small macromolecular complexes can be improved using high-resolution structures as priors combined with 2D template matching. Using this method, we reconstructed a previously intractable ∼ 43 kDa protein kinase and improved the density of its ligand-binding site. Our theoretical analysis predicts that this method can further extend single-particle cryo-EM to important drug-binding complexes well below 50 kDa.

  PublisherOA PDFDOI

• Is LIWC reliable, efficient, and effective for the analysis of large online datasets in forensic and security contexts?

  Applied Corpus Linguistics · 2025-01-09 · 10 citations

  articleOpen accessSenior author

  This article evaluates the reliability, efficiency, and effectiveness of Linguistic Inquiry and Word Count (LIWC; Boyd et al., 2022) for the analysis of a white nationalist forum. This is important because LIWC has been the computational tool of choice for scores of studies generally and many examining extremist content in a forensic or security context. Our purpose, therefore, is to understand whether LIWC can be depended upon for large-scale analyses; we initially examine this here using a small sample of posts from a set of just eight users and manually checking the program's automated codings of a subset of categories. Our results show that the LIWC coding cannot be relied upon – precision falls to as low as 49.6% and recall as low as 41.7% for some categories. It would be possible to engage in considerable manual correction of these results, but this undermines its purported efficiency for large datasets.

  PublisherDOI

• NMR Spectral Alignment Utilizing a CryoEM Motion Correction Algorithm

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

  preprintOpen accessSenior author

  ABSTRACT 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 datasets, 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.

  PublisherOA PDFDOI

• Diametr: A Cryo-Em Tool for Diameter Sorting of Tubular Samples

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• NMR Spectral Alignment Utilizing a CryoEM Motion Correction Algorithm

  Analytical Chemistry · 2025-12-15

  articleOpen accessSenior authorCorresponding

  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

• A single residue in the yellow fever virus envelope protein modulates virion architecture and antigenicity

  Nature Communications · 2025-09-26 · 4 citations

  articleOpen access

  Abstract Yellow fever virus (YFV) is a re-emerging flavivirus that causes severe hepatic disease and mortality in humans. Despite being researched for over a century, the structure of YFV has remained elusive. Here we use a chimeric virus platform to resolve the first high resolution cryo-EM structures of YFV. Stark differences in particle morphology and homogeneity are observed between vaccine and virulent strains of YFV, and these are found to have significant implications on antibody recognition and neutralisation. We identify a single residue (R380) in the YFV 17D envelope protein that stabilises the virion surface, and leads to reduced exposure of the cross-reactive fusion loop epitope. The differences in virion morphology between YFV strains also contribute to the reduced sensitivity of the virulent YFV virions to vaccine-induced antibodies. These findings have significant implications for YFV biology, vaccinology and structure-based flavivirus antigen design.

  PublisherOA PDFDOI

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

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

  preprintOpen access

  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

• 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 accessCorresponding

  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

• Laser-Induced Rehydration of Cryo-Landed Proteins Restores Native Structure

  Molecular & Cellular Proteomics · 2025-05-09 · 4 citations

  articleOpen access

  The use of native mass spectrometry (MS) to land biological molecules for subsequent cryogenic electron microscopy (cryoEM) imaging and three-dimensional reconstruction has gained momentum in recent years as a means to overcome long-standing challenges posed by traditional cryoEM sample preparation. However, recent results obtained with this approach have been constrained by low resolution and the compaction of cryo-landed particles, likely due to dehydration during exposure to vacuum. Here, we describe a new sample preparation method that uses a laser integrated into a cryogenic soft-landing apparatus to liquefy precisely deposited amorphous ice, rehydrating particles, and restoring their solution structure prior to rapid revitrification via the thermal mass of the grid. With this technique, we demonstrate the reconstruction of cryo-landed, rehydrated, and revitrified β-galactosidase that is comparable in resolution to that achieved with plunge freezing. Furthermore, these particles are not compacted, matching the known structure and conformation obtained with traditionally plunge-frozen particles. These results establish the viability of coupling native MS with cryoEM for high-resolution structural determination without the limitations imposed by conventional sample preparation, and they open a path to solving previously inaccessible molecules and to integrating MS capabilities such as gas-phase purification to complex samples such as cell lysates.

  PublisherOA PDFDOI

• Small LEA proteins mitigate air-water interface damage to fragile cryo-EM samples during plunge freezing

  Structural Dynamics · 2025-09-01

  articleOpen access

  Air-water interface (AWI) interactions during cryo-electron microscopy (cryo-EM) sample preparation cause significant sample loss, hindering structural biology research. Organisms like nematodes and tardigrades produce Late Embryogenesis Abundant (LEA) proteins to withstand desiccation stress. Here we show that these LEA proteins, when used as additives during plunge freezing, effectively mitigate AWI damage to fragile multi-subunit molecular samples. The resulting high-resolution cryo-EM maps are comparable to or better than those obtained using existing AWI damage mitigation methods. Cryogenic electron tomography reveals that particles are localized at specific interfaces, suggesting LEA proteins form a barrier at the AWI. This interaction may explain the observed sample-dependent preferred orientation of particles. In summary, we show LEA proteins can offer a simple, cost-effective, and adaptable approach for cryo-EM structural biologists to overcome AWI- related sample damage, potentially revitalizing challenging projects and advancing the field of structural biology.

  PublisherDOI

Frequent coauthors

• Nikolaus Grigorieff

  Howard Hughes Medical Institute

  118 shared

• Joshua J. Coon

  Morgridge Institute for Research

  28 shared

• Áine Merwick

  Cork University Hospital

  26 shared

• Orla C. Sheehan

  Johns Hopkins University

  26 shared

• Niamh Hannon

  University Hospital Galway

  26 shared

• Michael Marnane

  26 shared

• Joan T. Moroney

  26 shared

• Peter J. Kelly

  Cork University Hospital

  26 shared