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1. Mix-and-inject XFEL crystallography reveals gated conformational dynamics during enzyme catalysis

   https://doi.org/10.1073/pnas.1901864116  

   Dasgupta, Medhanjali; Budday, Dominik; de_Oliveira, Saulo_H P; Madzelan, Peter; Marchany-Rivera, Darya; Seravalli, Javier; Hayes, Brandon; Sierra, Raymond G; Boutet, Sébastien; Hunter, Mark S; et al (December 2019, Proceedings of the National Academy of Sciences)

   How changes in enzyme structure and dynamics facilitate passage along the reaction coordinate is a fundamental unanswered question. Here, we use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL), ambient-temperature X-ray crystallography, computer simulations, and enzyme kinetics to characterize how covalent catalysis modulates isocyanide hydratase (ICH) conformational dynamics throughout its catalytic cycle. We visualize this previously hypothetical reaction mechanism, directly observing formation of a thioimidate covalent intermediate in ICH microcrystals during catalysis. ICH exhibits a concerted helical displacement upon active-site cysteine modification that is gated by changes in hydrogen bond strength between the cysteine thiolate and the backbone amide of the highly strained Ile152 residue. These catalysis-activated motions permit water entry into the ICH active site for intermediate hydrolysis. Mutations at a Gly residue (Gly150) that modulate helical mobility reduce ICH catalytic turnover and alter its pre-steady-state kinetic behavior, establishing that helical mobility is important for ICH catalytic efficiency. These results demonstrate that MISC can capture otherwise elusive aspects of enzyme mechanism and dynamics in microcrystalline samples, resolving long-standing questions about the connection between nonequilibrium protein motions and enzyme catalysis. 

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2. Predicting protein conformational motions using energetic frustration analysis and AlphaFold2

   https://doi.org/10.1073/pnas.2410662121  

   Guan, Xingyue; Tang, Qian-Yuan; Ren, Weitong; Chen, Mingchen; Wang, Wei; Wolynes, Peter G; Li, Wenfei (August 2024, Proceedings of the National Academy of Sciences)

   Proteins perform their biological functions through motion. Although high throughput prediction of the three-dimensional static structures of proteins has proved feasible using deep-learning-based methods, predicting the conformational motions remains a challenge. Purely data-driven machine learning methods encounter difficulty for addressing such motions because available laboratory data on conformational motions are still limited. In this work, we develop a method for generating protein allosteric motions by integrating physical energy landscape information into deep-learning-based methods. We show that local energetic frustration, which represents a quantification of the local features of the energy landscape governing protein allosteric dynamics, can be utilized to empower AlphaFold2 (AF2) to predict protein conformational motions. Starting from ground state static structures, this integrative method generates alternative structures as well as pathways of protein conformational motions, using a progressive enhancement of the energetic frustration features in the input multiple sequence alignment sequences. For a model protein adenylate kinase, we show that the generated conformational motions are consistent with available experimental and molecular dynamics simulation data. Applying the method to another two proteins KaiB and ribose-binding protein, which involve large-amplitude conformational changes, can also successfully generate the alternative conformations. We also show how to extract overall features of the AF2 energy landscape topography, which has been considered by many to be black box. Incorporating physical knowledge into deep-learning-based structure prediction algorithms provides a useful strategy to address the challenges of dynamic structure prediction of allosteric proteins. 

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3. High-Throughput Computation of Anharmonic Low-Frequency Protein Vibrations

   https://doi.org/10.1021/acs.jpcb.5c04622  

   Sauer, Michael A; Mondal, Souvik; Cano, Madeline; Heyden, Matthias (October 2025, The Journal of Physical Chemistry B)

   At room temperature, low frequency vibrations at far-infrared frequencies are thermally excited (kBT > hν) and not restricted to harmonic fluctuations around a single potential energy minimum. For folded proteins, these intrinsically anharmonic vibrations can contain information on slow conformational transitions. Recently, we have developed FREquency-SElective ANharmonic (FRESEAN) mode analysis, a method based on time correlation functions that isolates low-frequency vibrational motions from molecular dynamics simulation trajectories without relying on harmonic approximations. We recently showed that low-frequency vibrations obtained from FRESEAN mode analysis are effective collective variables in enhanced sampling simulations of conformational ensembles. However, FRESEAN mode analysis is based on velocity time correlations between all degrees of freedom, which creates computational challenges for large biomolecules. To facilitate future applications, we demonstrate here how coarse-graining of all-atom simulation trajectories can be combined with FRESEAN mode analysis to extract information on low-frequency vibrations at minimal computational cost. 

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4. Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

   https://doi.org/10.7554/eLife.07574  

   Keedy, Daniel A; Kenner, Lillian R; Warkentin, Matthew; Woldeyes, Rahel A; Hopkins, Jesse B; Thompson, Michael C; Brewster, Aaron S; Van Benschoten, Andrew H; Baxter, Elizabeth L; Uervirojnangkoorn, Monarin; et al (September 2015, eLife)

   Proteins are the workhorses of the cell. The shape that a protein molecule adopts enables it to carry out its role. However, a protein’s shape, or 'conformation', is not static. Instead, a protein can shift between different conformations. This is particularly true for enzymes – the proteins that catalyze chemical reactions. The region of an enzyme where the chemical reaction happens, known as the active site, often has to change its conformation to allow catalysis to proceed. Changes in temperature can also make a protein shift between alternative conformations. Understanding how a protein shifts between conformations gives insight into how it works. A common method for studying protein conformation is X-ray crystallography. This technique uses a beam of X-rays to figure out where the atoms of the protein are inside a crystal made of millions of copies of that protein. At room temperature or biological temperature, X-rays can rapidly damage the protein. Because of this, most crystal structures are determined at very low temperatures to minimize damage. But cooling to low temperatures changes the conformations that the protein adopts, and usually causes fewer conformations to be present. Keedy, Kenner, Warkentin, Woldeyes et al. have used X-ray crystallography from a very low temperature (-173°C or 100 K) to above room temperature (up to 27°C or 300 K) to explore the alternative conformations of an enzyme called cyclophilin A. These alternative conformations include those that have previously been linked to this enzyme’s activity. Starting at a low temperature, parts of the enzyme were seen to shift from having a single conformation to many conformations above a threshold temperature. Unexpectedly, different parts of the enzyme have different threshold temperatures, suggesting that there isn’t a single transition across the whole protein. Instead, it appears the way a protein’s conformation changes in response to temperature is more complex than was previously realized. This result suggests that conformations in different parts of a protein are coupled to each other in complex ways. Keedy, Kenner, Warkentin, Woldeyes et al. then performed X-ray crystallography at room temperature using an X-ray free-electron laser (XFEL). This technique can capture the protein’s structure before radiation damage occurs, and confirmed that the alternative conformations observed were not affected by radiation damage. The combination of X-ray crystallography at multiple temperatures, new analysis methods for identifying and measuring alternative conformations, and XFEL crystallography should help future studies to characterize conformational changes in other proteins. 

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5. Characterization and modulation of human insulin degrading enzyme conformational dynamics to control enzyme activity.

   https://doi.org/10.7554/eLife.105761.4  

   Mancl, Jordan M; Liang, Wenguang G; Bayhi, Nicholas L; Wei, Hui; Budell, William C; Mendez, Joshua H; Sosnick, Tobin R; Carragher, Bridget; Potter, Clinton S; Tang, Wei-Jen (June 2026, eLife)

   Insulin degrading enzyme (IDE) is a dimeric M16A zinc metalloprotease that degrades amyloidogenic peptides diverse in shape and sequence, including insulin and amyloid-β, to prevent toxic amyloid fibril formation. IDE has a hollow catalytic chamber formed by two ~55 kDa N- and C- domains (IDE-N and IDE-C, respectively), in which peptides bind, unfold, and are repositioned for proteolysis. IDE is known to transition between a closed state, poised for catalysis, and an open state, able to release cleavage products and bind a new substrate. Here, we present six cryo-EM structures of the IDE dimer at 3.0–5.1 Å resolution, obtained in the presence of a sub-saturating concentration of insulin. Combining cryo-EM heterogeneity analysis with all-atom molecular dynamics (MD) simulations, we identified the structural basis and key residues for IDE conformational dynamics that were not previously revealed by IDE static structures. Notably, R668 serves as a molecular latch mediating the open-close transition and facilitates key protein motions through charge-swapping interactions at the IDE-N/C interface. Our small-angle X-ray scattering analysis and enzymatic assays of an R668A mutant indicate a profound alteration of conformational dynamics and catalytic activity. By integrating coarse-grained MD simulations, our analysis reveals that IDE unfolds its substrates through the coordinated motion between IDE-N and IDE-C, as well as β-sheet formation between IDE and insulin. Additionally, our time-resolved cryo-EM analysis uncovers IDE allostery within the IDE dimer. Collectively, our findings demonstrate the strength of combining experimental and computational approaches to probe protein dynamics and pave the way for developing substrate-specific modulators of IDE activity. 

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