Structural dynamics: review of time-resolved cryo-EM

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery.

Nanosecond Transient IR Spectroscopy of Halorhodopsin in Living Cells

The ability to track minute changes of a single amino acid residue in a cellular environment is causing a paradigm shift in the attempt to fully understand the responses of biomolecules that are highly sensitive to their environment. Detecting early protein dynamics in living cells is crucial to understanding their mechanisms, such as those of photosynthetic proteins. Here, we elucidate the light response of the microbial chloride pump NmHR from the marine bacterium Nonlabens marinus, located in the membrane of living Escherichia coli cells, using nanosecond time-resolved UV/vis and IR absorption spectroscopy over the time range from nanoseconds to seconds. Transient structural changes of the retinal cofactor and the surrounding apoprotein are recorded using light-induced time-resolved UV/vis and IR difference spectroscopy. Of particular note, we have resolved the kinetics of the transient deprotonation of a single cysteine residue during the photocycle of NmHR out of the manifold of molecular vibrations of the cells. These findings are of high general relevance, given the successful development of optogenetic tools from photoreceptors to interfere with enzymatic and neuronal pathways in living organisms using light pulses as a noninvasive trigger.

Microsecond time-resolved cryo-electron microscopy

Microsecond time-resolved cryo-electron microscopy has emerged as a novel approach for directly observing protein dynamics. By providing microsecond temporal and near-atomic spatial resolution, it has the potential to elucidate a wide range of dynamics that were previously inaccessible and therefore, to significantly advance our understanding of protein function. This review summarizes the properties of the laser melting and revitrification process that underlies the technique and describes different experimental implementations. Strategies for initiating and probing dynamics are discussed. Finally, the microsecond time-resolved observation of the capsid dynamics of cowpea chlorotic mottle virus, an icosahedral plant virus, is reviewed, which illustrates important features of the technique as well as its potential.

VitroJet: new features and case studies

Single-particle cryo-electron microscopy has become a widely adopted method in structural biology due to many recent technological advances in microscopes, detectors and image processing. Before being able to inspect a biological sample in an electron microscope, it needs to be deposited in a thin layer on a grid and rapidly frozen. The VitroJet was designed with this aim, as well as avoiding the delicate manual handling and transfer steps that occur during the conventional grid-preparation process. Since its creation, numerous technical developments have resulted in a device that is now widely utilized in multiple laboratories worldwide. It features plasma treatment, low-volume sample deposition through pin printing, optical ice-thickness measurement and cryofixation of pre-clipped Autogrids through jet vitrification. This paper presents recent technical improvements to the VitroJet and the benefits that it brings to the cryo-EM workflow. A wide variety of applications are shown: membrane proteins, nucleosomes, fatty-acid synthase, Tobacco mosaic virus, lipid nanoparticles, tick-borne encephalitis viruses and bacteriophages. These case studies illustrate the advancement of the VitroJet into an instrument that enables accurate control and reproducibility, demonstrating its suitability for time-efficient cryo-EM structure determination.

Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

Integrative approaches for characterizing protein dynamics: NMR, CryoEM, and computer simulations

Proteins are inherently dynamic and their internal motions are essential for biological function. Protein motions cover a broad range of timescales: 10-14-10 s, spanning from sub-picosecond vibrational motions of atoms via microsecond loop conformational rearrangements to millisecond large amplitude domain reorientations. Observing protein dynamics over all timescales and connecting motions and structure to biological mechanisms requires integration of multiple experimental and computational techniques. This review reports on state-of-the-art approaches for assessing dynamics in biological systems using recent examples of virus assemblies, enzymes, and molecular machines. By integrating NMR spectroscopy in solution and the solid state, cryo electron microscopy, and molecular dynamics simulations, atomistic pictures of protein motions are obtained, not accessible from any single method in isolation. This information provides fundamental insights into protein behavior that can guide the development of future therapeutics.

Time resolved applications for Cryo-EM; approaches, challenges and future directions

Developments within the cryo-EM field have allowed us to generate higher-resolution "static" structures and pull out different conformational states which exist at equilibrium within the sample. Moreover, to trap non-equilibrium states and determine conformations that are present after a defined period of time (typically in the ms time frame) new approaches have been developed for the application of time-resolved cryo-EM. Here we give an overview of these different approaches and the limitations and strengths of each whilst identifying some of the current challenges to achieve higher resolutions and trap states within faster time frames. Time-resolved applications may play an important role in the ever-expanding toolkit of cryo-EM and open up new possibilities in both single particle and tomographic studies.

Cell phenotypes can be predicted from propensities of protein conformations

Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.

Fast viral dynamics revealed by microsecond time-resolved cryo-EM

Observing proteins as they perform their tasks has largely remained elusive, which has left our understanding of protein function fundamentally incomplete. To enable such observations, we have recently proposed a technique that improves the time resolution of cryo-electron microscopy (cryo-EM) to microseconds. Here, we demonstrate that microsecond time-resolved cryo-EM enables observations of fast protein dynamics. We use our approach to elucidate the mechanics of the capsid of cowpea chlorotic mottle virus (CCMV), whose large-amplitude motions play a crucial role in the viral life cycle. We observe that a pH jump causes the extended configuration of the capsid to contract on the microsecond timescale. While this is a concerted process, the motions of the capsid proteins involve different timescales, leading to a curved reaction path. It is difficult to conceive how such a detailed picture of the dynamics could have been obtained with any other method, which highlights the potential of our technique. Crucially, our experiments pave the way for microsecond time-resolved cryo-EM to be applied to a broad range of protein dynamics that previously could not have been observed. This promises to fundamentally advance our understanding of protein function.

Modeling conformational states of proteins with AlphaFold

Many proteins exert their function by switching among different structures. Knowing the conformational ensembles affiliated with these states is critical to elucidate key mechanistic aspects that govern protein function. While experimental determination efforts are still bottlenecked by cost, time, and technical challenges, the machine-learning technology AlphaFold showed near experimental accuracy in predicting the three-dimensional structure of monomeric proteins. However, an AlphaFold ensemble of models usually represents a single conformational state with minimal structural heterogeneity. Consequently, several pipelines have been proposed to either expand the structural breadth of an ensemble or bias the prediction toward a desired conformational state. Here, we analyze how those pipelines work, what they can and cannot predict, and future directions.

Structural and mechanistic insights into the CAND1-mediated SCF substrate receptor exchange

Modular SCF (SKP1-CUL1-Fbox) ubiquitin E3 ligases orchestrate multiple cellular pathways in eukaryotes. Their variable SKP1-Fbox substrate receptor (SR) modules enable regulated substrate recruitment and subsequent proteasomal degradation. CAND proteins are essential for the efficient and timely exchange of SRs. To gain structural understanding of the underlying molecular mechanism, we reconstituted a human CAND1-driven exchange reaction of substrate-bound SCF alongside its co-E3 ligase DCNL1 and visualized it by cryo-EM. We describe high-resolution structural intermediates, including a ternary CAND1-SCF complex, as well as conformational and compositional intermediates representing SR- or CAND1-dissociation. We describe in molecular detail how CAND1-induced conformational changes in CUL1/RBX1 provide an optimized DCNL1-binding site and reveal an unexpected dual role for DCNL1 in CAND1-SCF dynamics. Moreover, a partially dissociated CAND1-SCF conformation accommodates cullin neddylation, leading to CAND1 displacement. Our structural findings, together with functional biochemical assays, help formulate a detailed model for CAND-SCF regulation.

An Unsupervised Classification Algorithm for Heterogeneous Cryo-EM Projection Images Based on Autoencoders

Heterogeneous three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is an important but very challenging technique for recovering the conformational heterogeneity of flexible biological macromolecules such as proteins in different functional states. Heterogeneous projection image classification is a feasible solution to solve the structural heterogeneity problem in single-particle cryo-EM. The majority of heterogeneous projection image classification methods are developed using supervised learning technology or require a large amount of a priori knowledge, such as the orientations or common lines of the projection images, which leads to certain limitations in their practical applications. In this paper, an unsupervised heterogeneous cryo-EM projection image classification algorithm based on autoencoders is proposed, which only needs to know the number of heterogeneous 3D structures in the dataset and does not require any labeling information of the projection images or other a priori knowledge. A simple autoencoder with multi-layer perceptrons trained in iterative mode and a complex autoencoder with residual networks trained in one-pass learning mode are implemented to convert heterogeneous projection images into latent variables. The extracted high-dimensional features are reduced to two dimensions using the uniform manifold approximation and projection dimensionality reduction algorithm, and then clustered using the spectral clustering algorithm. The proposed algorithm is applied to two heterogeneous cryo-EM datasets for heterogeneous 3D reconstruction. Experimental results show that the proposed algorithm can effectively extract category features of heterogeneous projection images and achieve high classification and reconstruction accuracy, indicating that the proposed algorithm is effective for heterogeneous 3D reconstruction in single-particle cryo-EM.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules. However, as important as they are, molecular dynamics studies focused on DNA repair pathways are still becoming more widespread. Currently, there are no review articles compiling the advancements made in molecular dynamics approaches applied to NER and discussing: (i) how this technique is currently employed in the field of DNA repair, focusing on NER proteins; (ii) which technical setups are being employed, their strengths and limitations; (iii) which insights or information are they providing to understand the NER pathway or NER-associated proteins; (iv) which open questions would be suited for this technique to answer; and (v) where can we go from here. These questions become even more crucial considering the numerous 3D structures published regarding the NER pathway's proteins in recent years. In this work, we tackle each one of these questions, revising and critically discussing the results published in the context of the NER pathway.

Recent structural advances in bacterial chemotaxis signalling

Bacterial chemosensory arrays have served as a model system for in-situ structure determination, clearly cataloguing the improvement of cryo-electron tomography (cryoET) over the past decade. In recent years, this has culminated in an accurately fitted atomistic model for the full-length core signalling unit (CSU) and numerous insights into the function of the transmembrane receptors responsible for signal transduction. Here, we review the achievements of the latest structural advances in bacterial chemosensory arrays and the developments which have made such advances possible.

Pump-like channelrhodopsins: Not just bridging the gap between ion pumps and ion channels

Channelrhodopsins are microbial rhodopsins that work as light-gated ion channels. Their importance has become increasingly recognized due to their ability to control the membrane potential of specific cells in a light-dependent manner. This technology, termed optogenetics, has revolutionized neuroscience, and numerous channelrhodopsin variants have been isolated or engineered to expand the utility of optogenetics. Pump-like channelrhodopsins (PLCRs), one of the recently discovered channelrhodopsin subfamilies, have attracted broad attention due to their high sequence similarity to ion-pumping rhodopsins and their distinct properties, such as high light sensitivity and ion selectivity. In this review, we summarize the current understanding of the structure-function relationships of PLCRs and discuss the challenges and opportunities of channelrhodopsin research.

Biological function investigated by time-resolved structure determination

Inspired by recent progress in time-resolved x-ray crystallography and the adoption of time-resolution by cryo-electronmicroscopy, this article enumerates several approaches developed to become bigger/smaller, faster, and better to gain new insight into the molecular mechanisms of life. This is illustrated by examples where chemical and physical stimuli spawn biological responses on various length and time-scales, from fractions of Ångströms to micro-meters and from femtoseconds to hours.

Exploring the Structural Variability of Dynamic Biological Complexes by Single-Particle Cryo-Electron Microscopy

Biological macromolecules and assemblies precisely rearrange their atomic 3D structures to execute cellular functions. Understanding the mechanisms by which these molecular machines operate requires insight into the ensemble of structural states they occupy during the functional cycle. Single-particle cryo-electron microscopy (cryo-EM) has become the preferred method to provide near-atomic resolution, structural information about dynamic biological macromolecules elusive to other structure determination methods. Recent advances in cryo-EM methodology have allowed structural biologists not only to probe the structural intermediates of biochemical reactions, but also to resolve different compositional and conformational states present within the same dataset. This article reviews newly developed sample preparation and single-particle analysis (SPA) techniques for high-resolution structure determination of intrinsically dynamic and heterogeneous samples, shedding light upon the intricate mechanisms employed by molecular machines and helping to guide drug discovery efforts.