Molecular dynamics flexible fitting: a practical guide to combine cryo-electron microscopy and X-ray crystallography

Elucidating structural variability in p53 conformers using combinatorial refinement strategies and molecular dynamics

Low molecular weight proteins and protein assemblies can now be investigated using cryo-electron microscopy (EM) as a complement to traditional structural biology techniques. It is important, however, to not lose sight of the dynamic information inherent in macromolecules that give rise to their exquisite functionality. As computational methods continue to advance the field of biomedical imaging, so must strategies to resolve the minute details of disease-related entities. Here, we employed combinatorial modeling approaches to assess flexible properties among low molecular weight proteins (~100 kDa or less). Through a blend of rigid body refinement and simulated annealing, we determined new hidden conformations for wild type p53 monomer and dimer forms. Structures for both states converged to yield new conformers, each revealing good stereochemistry and dynamic information about the protein. Based on these insights, we identified fluid parts of p53 that complement the stable central core of the protein responsible for engaging DNA. Molecular dynamics simulations corroborated the modeling results and helped pinpoint the more flexible residues in wild type p53. Overall, the new computational methods may be used to shed light on other small protein features in a vast ensemble of structural data that cannot be easily delineated by other algorithms.

Vimentin filaments integrate low-complexity domains in a complex helical structure

Intermediate filaments (IFs) are integral components of the cytoskeleton. They provide cells with tissue-specific mechanical properties and are involved in numerous cellular processes. Due to their intricate architecture, a 3D structure of IFs has remained elusive. Here we use cryo-focused ion-beam milling, cryo-electron microscopy and tomography to obtain a 3D structure of vimentin IFs (VIFs). VIFs assemble into a modular, intertwined and flexible helical structure of 40 α-helices in cross-section, organized into five protofibrils. Surprisingly, the intrinsically disordered head domains form a fiber in the lumen of VIFs, while the intrinsically disordered tails form lateral connections between the protofibrils. Our findings demonstrate how protein domains of low sequence complexity can complement well-folded protein domains to construct a biopolymer with striking mechanical strength and stretchability.

Chromatin image-driven modelling

The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.

Differential Behavior of Conformational Dynamics in Active and Inactive States of Cannabinoid Receptor 1

The cannabinoid receptor CB1 is a G protein-coupled receptor that regulates critical physiological processes including pain, appetite, and cognition. Understanding the conformational dynamics of CB1 associated with transitions between inactive and active signaling states is imperative for developing targeted modulators. Using microsecond-level all-atom molecular dynamics simulations, we identified marked differences in the conformational ensembles of inactive and active CB1 states in apo conditions. The inactive state exhibited substantially increased structural heterogeneity and plasticity compared to the more rigidified active state in the absence of stabilizing ligands. Transmembrane helices TM3 and TM7 were identified as distinguishing factors modulating the state-dependent dynamics. TM7 displayed amplified fluctuations selectively in the inactive state simulations attributed to disruption of conserved electrostatic contacts anchoring it to surrounding helices in the active state. Additionally, we identified significant reorganization of key salt bridge and hydrogen bond networks known to control CB1 activation between states. For instance, a conserved D213-Y224 hydrogen bond and D184-K192 salt bridge interactions showed marked rearrangements between the states. Collectively, these findings reveal the specialized role of TM7 in directing state-dependent CB1 dynamics through electrostatic switch mechanisms. By elucidating the intrinsic enhanced flexibility of inactive CB1, this study provides valuable insights into the conformational landscape enabling functional transitions. Our perspective advances understanding of CB1 activation mechanisms and offers opportunities for structure-based drug discovery targeting the state-specific conformational dynamics of this receptor.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Differences between bacteria and eukaryotes in clamp loader mechanism, a conserved process underlying DNA replication

Clamp loaders are pentameric ATPases that place circular sliding clamps onto DNA, where they function in DNA replication and genome integrity. The central activity of a clamp loader is the opening of the ring-shaped sliding clamp and the subsequent binding to primer-template (p/t)-junctions. The general architecture of clamp loaders is conserved across all life, suggesting that their mechanism is retained. Recent structural studies of the eukaryotic clamp loader replication factor C (RFC) revealed that it functions using a crab-claw mechanism, where clamp opening is coupled to a massive conformational change in the loader. Here we investigate the clamp loading mechanism of the Escherichia coli clamp loader at high resolution using cryo-electron microscopy. We find that the E. coli clamp loader opens the clamp using a crab-claw motion at a single pivot point, whereas the eukaryotic RFC loader uses motions distributed across the complex. Furthermore, we find clamp opening occurs in multiple steps, starting with a partly open state with a spiral conformation, and proceeding to a wide open clamp in a surprising planar geometry. Finally, our structures in the presence of p/t-junctions illustrate how the clamp closes around p/t-junctions and how the clamp loader initiates release from the loaded clamp. Our results reveal mechanistic distinctions in a macromolecular machine that is conserved across all domains of life.

Structural basis of Acinetobacter type IV pili targeting by an RNA virus

Acinetobacters pose a significant threat to human health, especially those with weakened immune systems. Type IV pili of acinetobacters play crucial roles in virulence and antibiotic resistance. Single-stranded RNA bacteriophages target the bacterial retractile pili, including type IV. Our study delves into the interaction between Acinetobacter phage AP205 and type IV pili. Using cryo-electron microscopy, we solve structures of the AP205 virion with an asymmetric dimer of maturation proteins, the native Acinetobacter type IV pili bearing a distinct post-translational pilin cleavage, and the pili-bound AP205 showing its maturation proteins adapted to pilin modifications, allowing each phage to bind to one or two pili. Leveraging these results, we develop a 20-kilodalton AP205-derived protein scaffold targeting type IV pili in situ, with potential for research and diagnostics.

Predictive modeling and cryo-EM: A synergistic approach to modeling macromolecular structure

Over the last 15 years, structural biology has seen unprecedented development and improvement in two areas: electron cryo-microscopy (cryo-EM) and predictive modeling. Once relegated to low resolutions, single-particle cryo-EM is now capable of achieving near-atomic resolutions of a wide variety of macromolecular complexes. Ushered in by AlphaFold, machine learning has powered the current generation of predictive modeling tools, which can accurately and reliably predict models for proteins and some complexes directly from the sequence alone. Although they offer new opportunities individually, there is an inherent synergy between these techniques, allowing for the construction of large, complex macromolecular models. Here, we give a brief overview of these approaches in addition to illustrating works that combine these techniques for model building. These examples provide insight into model building, assessment, and limitations when integrating predictive modeling with cryo-EM density maps. Together, these approaches offer the potential to greatly accelerate the generation of macromolecular structural insights, particularly when coupled with experimental data.

One bead per residue can describe all-atom protein structures

Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.

Differences in clamp loader mechanism between bacteria and eukaryotes

Clamp loaders are pentameric ATPases that place circular sliding clamps onto DNA, where they function in DNA replication and genome integrity. The central activity of a clamp loader is the opening of the ring-shaped sliding clamp, and the subsequent binding to primer-template (p/t)-junctions. The general architecture of clamp loaders is conserved across all life, suggesting that their mechanism is retained. Recent structural studies of the eukaryotic clamp loader Replication Factor C (RFC) revealed that it functions using a crab-claw mechanism, where clamp opening is coupled to a massive conformational change in the loader. Here we investigate the clamp loading mechanism of the E. coli clamp loader at high resolution using cryo-electron microscopy (cryo-EM). We find that the E. coli clamp loader opens the clamp using a crab-claw motion at a single pivot point, whereas the eukaryotic RFC loader uses motions distributed across the complex. Furthermore, we find clamp opening occurs in multiple steps, starting with a partly open state with a spiral conformation, and proceeding to a wide open clamp in a surprising planar geometry. Finally, our structures in the presence of p/t-junctions illustrate how clamp closes around p/t-junctions and how the clamp loader initiates release from the loaded clamp. Our results reveal mechanistic distinctions in a macromolecular machine that is conserved across all domains of life.

Delineating Conformational Variability in Small Protein Structures Using Combinatorial Refinement Strategies

As small protein assemblies and even small proteins are becoming more amenable to cryo-Electron Microscopy (EM) structural studies, it is important to consider the complementary dynamic information present in the data. Current computational strategies are limited in their ability to resolve minute differences among low molecular weight entities. Here, we demonstrate a new combinatorial approach to delineate flexible conformations among small proteins using real-space refinement applications. We performed a meta-analysis of structural data for the SARS CoV-2 Nucleocapsid (N) protein using a combination of rigid-body refinement and simulated annealing methods. For the N protein monomer, we determined three new flexible conformers with good stereochemistry and quantitative comparisons provided new evidence of their dynamic properties. A similar analysis performed for the N protein dimer showed only minor structural differences among the flexible models. These results suggested a more stable view of the N protein dimer than the monomer structure. Taken together, the new computational strategies can delineate conformational changes in low molecular weight proteins that may go unnoticed by conventional assessments. The results also suggest that small proteins may be further stabilized for structural studies through the use of solution components that limit the movement of external flexible regions.

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge-driven or artificial intelligence-driven and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models that contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly while refining them against the density maps. We introduce such an adaptive decision-making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two prototypical protein systems, adenylate kinase and carbon monoxide dehydrogenase. For these test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2-3 Å map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that are inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from the chimpanzee adenovirus. The overhead for decision making remains low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install R-MDFF on different computing environments, from local Linux-based workstations to high-performance computing environments.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.

Molecular architecture and conservation of an immature human endogenous retrovirus

The human endogenous retrovirus K (HERV-K) is the most recently acquired endogenous retrovirus in the human genome and is activated and expressed in many cancers and amyotrophic lateral sclerosis. We present the immature HERV-K capsid structure at 3.2 Å resolution determined from native virus-like particles using cryo-electron tomography and subtomogram averaging. The structure shows a hexamer unit oligomerized through a 6-helix bundle, which is stabilized by a small molecule analogous to IP6 in immature HIV-1 capsid. The HERV-K immature lattice is assembled via highly conserved dimer and trimer interfaces, as detailed through all-atom molecular dynamics simulations and supported by mutational studies. A large conformational change mediated by the linker between the N-terminal and the C-terminal domains of CA occurs during HERV-K maturation. Comparison between HERV-K and other retroviral immature capsid structures reveals a highly conserved mechanism for the assembly and maturation of retroviruses across genera and evolutionary time.

Ionizable Amino Lipids Distribution and Effects on DSPC/Cholesterol Membranes: Implications for Lipid Nanoparticle Structure

Lipid nanoparticles (LNPs) containing ionizable aminolipids are among the leading platforms for the successful delivery of nucleic-acid-based therapeutics, including messenger RNA (mRNA). The two recently FDA-approved COVID-19 vaccines developed by Moderna and Pfizer/BioNTech belong to this category. Ionizable aminolipids, cholesterol, and DSPC lipids are among the key components of such formulations, crucially modulating physicochemical properties of these formulations and, consequently, the potency of these therapeutics. Despite the importance of these components, the distribution of these molecules in LNPs containing mRNA is not clear. In this study, we used all-atom molecular dynamics (MD) simulations to investigate the distribution and effects of the Lipid-5 (apparent pKa of the lipid nanoparticle = 6.56), a rationally designed and previously reported ionizable aminolipid by Moderna, on lipid bilayers [Mol. Ther. 2018, 26, 1509-1519]. The simulations were conducted with half of the aminolipids charged and half neutral approximately to the expected ionization in the microenvironment of the LNP surface. In all five simulated systems in this work, the cholesterol content was kept constant, whereas the DSPC and Lipid-5 concentrations were changed systematically. We found that at higher concentrations of the ionizable aminolipids, the neutral aminolipids form a disordered aggregate in the membrane interior that preferentially includes cholesterol. The rules underlying the lipid redistribution could be used to rationally choose lipids to optimize the LNP function.

Troponin-I-induced tropomyosin pivoting defines thin-filament function in relaxed and active muscle

Regulation of the crossbridge cycle that drives muscle contraction involves a reconfiguration of the troponin-tropomyosin complex on actin filaments. By comparing atomic models of troponin-tropomyosin fitted to cryo-EM structures of inhibited and Ca2+-activated thin filaments, we find that tropomyosin pivots rather than rolls or slides across actin as generally thought. We propose that pivoting can account for the Ca2+ activation that initiates muscle contraction and then relaxation influenced by troponin-I (TnI). Tropomyosin is well-known to occupy either of three meta-stable configurations on actin, regulating access of myosin motorheads to their actin-binding sites and thus the crossbridge cycle. At low Ca2+ concentrations, tropomyosin is trapped by TnI in an inhibitory B-state that sterically blocks myosin binding to actin, leading to muscle relaxation. Ca2+ binding to TnC draws TnI away from tropomyosin, while tropomyosin moves to a C-state location over actin. This partially relieves the steric inhibition and allows weak binding of myosin heads to actin, which then transition to strong actin-bound configurations, fully activating the thin filament. Nevertheless, the reconfiguration that accompanies the initial Ca2+-sensitive B-state/C-state shift in troponin-tropomyosin on actin remains uncertain and at best is described by moderate-resolution cryo-EM reconstructions. Our recent computational studies indicate that intermolecular residue-to-residue salt-bridge linkage between actin and tropomyosin is indistinguishable in B- and C-state thin filament configurations. We show here that tropomyosin can pivot about relatively fixed points on actin to accompany B-state/C-state structural transitions. We argue that at low Ca2+ concentrations C-terminal TnI domains attract tropomyosin, causing it to bend and then pivot toward the TnI, thus blocking myosin binding and contraction.

Structural basis for control of bacterial RNA polymerase pausing by a riboswitch and its ligand

Folding of nascent transcripts can be modulated by the RNA polymerase (RNAP) that carries out their transcription, and vice versa. A pause of RNAP during transcription of a preQ1 riboswitch (termed que-PEC) is stabilized by a previously characterized template consensus sequence and the ligand-free conformation of the nascent RNA. Ligand binding to the riboswitch induces RNAP pause release and downstream transcription termination; however, the mechanism by which riboswitch folding modulates pausing is unclear. Here, we report single-particle cryo-electron microscopy reconstructions of que-PEC in ligand-free and ligand-bound states. In the absence of preQ1, the RNA transcript is in an unexpected hyper-translocated state, preventing downstream nucleotide incorporation. Strikingly, on ligand binding, the riboswitch rotates around its helical axis, expanding the surrounding RNAP exit channel and repositioning the transcript for elongation. Our study reveals the tight coupling by which nascent RNA structures and their ligands can functionally regulate the macromolecular transcription machinery.

Molecular architecture and conservation of an immature human endogenous retrovirus

A significant part of the human genome consists of endogenous retroviruses sequences. Human endogenous retrovirus K (HERV-K) is the most recently acquired endogenous retrovirus, is activated and expressed in many cancers and amyotrophic lateral sclerosis and possibly contributes to the aging process. To understand the molecular architecture of endogenous retroviruses, we determined the structure of immature HERV-K from native virus-like particles (VLPs) using cryo-electron tomography and subtomogram averaging (cryoET STA). The HERV-K VLPs show a greater distance between the viral membrane and immature capsid lattice, correlating with the presence of additional peptides, SP1 and p15, between the capsid (CA) and matrix (MA) proteins compared to the other retroviruses. The resulting cryoET STA map of the immature HERV-K capsid at 3.2 Å resolution shows a hexamer unit oligomerized through a 6-helix bundle which is further stabilized by a small molecule in the same way as the IP6 in immature HIV-1 capsid. The HERV-K immature CA hexamer assembles into the immature lattice via highly conserved dimmer and trimer interfaces, whose interactions were further detailed through all-atom molecular dynamics simulations and supported by mutational studies. A large conformational change mediated by the flexible linker between the N-terminal and the C-terminal domains of CA occurs between the immature and the mature HERV-K capsid protein, analogous to HIV-1. Comparison between HERV-K and other retroviral immature capsid structures reveals a highly conserved mechanism for the assembly and maturation of retroviruses across genera and evolutionary time.

Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels

Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.

Dynamic conformational switching underlies TFIIH function in transcription and DNA repair and impacts genetic diseases

Transcription factor IIH (TFIIH) is a protein assembly essential for transcription initiation and nucleotide excision repair (NER). Yet, understanding of the conformational switching underpinning these diverse TFIIH functions remains fragmentary. TFIIH mechanisms critically depend on two translocase subunits, XPB and XPD. To unravel their functions and regulation, we build cryo-EM based TFIIH models in transcription- and NER-competent states. Using simulations and graph-theoretical analysis methods, we reveal TFIIH's global motions, define TFIIH partitioning into dynamic communities and show how TFIIH reshapes itself and self-regulates depending on functional context. Our study uncovers an internal regulatory mechanism that switches XPB and XPD activities making them mutually exclusive between NER and transcription initiation. By sequentially coordinating the XPB and XPD DNA-unwinding activities, the switch ensures precise DNA incision in NER. Mapping TFIIH disease mutations onto network models reveals clustering into distinct mechanistic classes, affecting translocase functions, protein interactions and interface dynamics.

CryoFold 2.0: Cryo-EM Structure Determination with MELD

Cryo-electron microscopy data are becoming more prevalent and accessible at higher resolution levels, leading to the development of new computational tools to determine the atomic structure of macromolecules. However, while existing tools adapted from X-ray crystallography are suitable for the highest-resolution maps, new tools are needed for lower-resolution levels and to account for map heterogeneity. In this article, we introduce CryoFold 2.0, an integrative physics-based approach that combines Bayesian inference and the ability to handle multiple data sources with the molecular dynamics flexible fitting (MDFF) approach to determine the structures of macromolecules by using cryo-EM data. CryoFold 2.0 is incorporated into the MELD (modeling employing limited data) plugin, resulting in a pipeline that is more computationally efficient and accurate than running MELD or MDFF alone. The approach requires fewer computational resources and shorter simulation times than the original CryoFold, and it minimizes manual intervention. We demonstrate the effectiveness of the approach on eight different systems, highlighting its various benefits.

The structural basis of tRNA recognition by arginyl-tRNA-protein transferase

Arginyl-tRNA-protein transferase 1 (ATE1) is a master regulator of protein homeostasis, stress response, cytoskeleton maintenance, and cell migration. The diverse functions of ATE1 arise from its unique enzymatic activity to covalently attach an arginine onto its protein substrates in a tRNA-dependent manner. However, how ATE1 (and other aminoacyl-tRNA transferases) hijacks tRNA from the highly efficient ribosomal protein synthesis pathways and catalyzes the arginylation reaction remains a mystery. Here, we describe the three-dimensional structures of Saccharomyces cerevisiae ATE1 with and without its tRNA cofactor. Importantly, the putative substrate binding domain of ATE1 adopts a previously uncharacterized fold that contains an atypical zinc-binding site critical for ATE1 stability and function. The unique recognition of tRNA^Arg by ATE1 is coordinated through interactions with the major groove of the acceptor arm of tRNA. Binding of tRNA induces conformational changes in ATE1 that helps explain the mechanism of substrate arginylation.

Myosin loop-4 is critical for optimal tropomyosin repositioning on actin during muscle activation and relaxation

During force-generating steps of the muscle crossbridge cycle, the tip of the myosin motor, specifically loop-4, contacts the tropomyosin cable of actin filaments. In the current study, we determined the corresponding effect of myosin loop-4 on the regulatory positioning of tropomyosin on actin. To accomplish this, we compared high-resolution cryo-EM structures of myosin S1-decorated thin filaments containing either wild-type or a loop-4 mutant construct, where the seven-residue portion of myosin loop-4 that contacts tropomyosin was replaced by glycine residues, thus removing polar side chains from residues 366-372. Cryo-EM analysis of fully decorated actin-tropomyosin filaments with wild-type and mutant S1, yielded 3.4-3.6 Å resolution reconstructions, with even higher definition at the actin-myosin interface. Loop-4 densities both in wild-type and mutant S1 were clearly identified, and side chains were resolved in the wild-type structure. Aside from loop-4, actin and myosin structural domains were indistinguishable from each other when filaments were decorated with either mutant or wild-type S1. In marked contrast, the position of tropomyosin on actin in the two reconstructions differed by 3 to 4 Å. In maps of filaments containing the mutant, tropomyosin was located closer to the myosin-head and thus moved in the direction of the C-state conformation adopted by myosin-free thin filaments. Complementary interaction energy measurements showed that tropomyosin in the mutant thin filaments sits on actin in a local energy minimum, whereas tropomyosin is positioned by wild-type S1 in an energetically unfavorable location. We propose that the high potential energy associated with tropomyosin positioning in wild-type filaments favors an effective transition to B- and C-states following release of myosin from the thin filaments during relaxation.

Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike

Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.

Uncovering structural ensembles from single-particle cryo-EM data using cryoDRGN

Single-particle cryogenic electron microscopy (cryo-EM) has emerged as a powerful technique to visualize the structural landscape sampled by a protein complex. However, algorithmic and computational bottlenecks in analyzing heterogeneous cryo-EM datasets have prevented the full realization of this potential. CryoDRGN is a machine learning system for heterogeneous cryo-EM reconstruction of proteins and protein complexes from single-particle cryo-EM data. Central to this approach is a deep generative model for heterogeneous cryo-EM density maps, which we empirically find is effective in modeling both discrete and continuous forms of structural variability. Once trained, cryoDRGN is capable of generating an arbitrary number of 3D density maps, and thus interpreting the resulting ensemble is a challenge. Here, we showcase interactive and automated processing approaches for analyzing cryoDRGN results. Specifically, we detail a step-by-step protocol for the analysis of an existing assembling 50S ribosome dataset, including preparation of inputs, network training and visualization of the resulting ensemble of density maps. Additionally, we describe and implement methods to comprehensively analyze and interpret the distribution of volumes with the assistance of an associated atomic model. This protocol is appropriate for structural biologists familiar with processing single-particle cryo-EM datasets and with moderate experience navigating Python and Jupyter notebooks. It requires 3-4 days to complete. CryoDRGN is open source software that is freely available.

MDSPACE: Extracting Continuous Conformational Landscapes from Cryo-EM Single Particle Datasets Using 3D-to-2D Flexible Fitting based on Molecular Dynamics Simulation

This article presents an original approach for extracting atomic-resolution landscapes of continuous conformational variability of biomolecular complexes from cryo electron microscopy (cryo-EM) single particle images. This approach is based on a new 3D-to-2D flexible fitting method, which uses molecular dynamics (MD) simulation and is embedded in an iterative conformational-landscape refinement scheme. This new approach is referred to as MDSPACE, which stands for Molecular Dynamics simulation for Single Particle Analysis of Continuous Conformational hEterogeneity. The article describes the MDSPACE approach and shows its performance using synthetic and experimental datasets.

LongBondEliminator: A Molecular Simulation Tool to Remove Ring Penetrations in Biomolecular Simulation Systems

We develop a workflow, implemented as a plugin to the molecular visualization program VMD, that can fix ring penetrations with minimal user input. LongBondEliminator, detects ring piercing artifacts by the long, strained bonds that are the local minimum energy conformation during minimization for some assembled simulation system. The LongBondEliminator tool then automatically treats regions near these long bonds using multiple biases applied through NAMD. By combining biases implemented through the collective variables module, density-based forces, and alchemical techniques in NAMD, LongBondEliminator will iteratively alleviate long bonds found within molecular simulation systems. Through three concrete examples with increasing complexity, a lignin polymer, an viral capsid assembly, and a large, highly glycosylated protein aggrecan, we demonstrate the utility for this method in eliminating ring penetrations from classical MD simulation systems. The tool is available via gitlab as a VMD plugin, and has been developed to be generically useful across a variety of biomolecular simulations.

The development of nucleic acids force fields: From an unchallenged past to a competitive future

Molecular dynamics simulations have strongly matured as a method to study biomolecular processes. Their validity, however, is determined by the accuracy of the underlying force fields that describe the forces between all atoms. In this article, we review the development of nucleic acids force fields. We describe the early attempts in the 1990s and emphasize their strong influence on recent force fields. State-of-the-art force fields still use the same Lennard-Jones parameters derived 25 years ago in spite of the fact that these parameters were in general not fitted for nucleic acids. In addition, electrostatic parameters also are deprecated, which may explain some of the current force field deficiencies. We compare different force fields for various systems and discuss new tests of the recently developed Tumuc1 force field. The OL-force fields and Tumuc1 are arguably the best force fields to describe the DNA double helix. However, no force field is flawless. In particular, the description of sugar-puckering remains a problem for nucleic acids force fields. Future refinements are required, so we review methods for force field refinement and give an outlook to the future of force fields.

Harris S, Ramanathan A. Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom-atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

Modulation of cardiac thin filament structure by phosphorylated troponin-I analyzed by protein-protein docking and molecular dynamics simulation

Tropomyosin, controlled by troponin-linked Ca2+-binding, regulates muscle contraction by a macromolecular scale steric-mechanism that governs myosin-crossbridge-actin interactions. At low-Ca2+, C-terminal domains of troponin-I (TnI) trap tropomyosin in a position on thin filaments that interferes with myosin-binding, thus causing muscle relaxation. Steric inhibition is reversed at high-Ca2+ when TnI releases from F-actin-tropomyosin as Ca2+ and the TnI switch-peptide bind to the N-lobe of troponin-C (TnC). The opposite end of cardiac TnI contains a phosphorylation-sensitive ∼30 residue-long N-terminal peptide that is absent in skeletal muscle, and likely modifies these interactions in hearts. Here, PKA-dependent phosphorylation of serine 23 and 24 modulates Ca2+ and possibly switch-peptide binding to TnC, causing faster relaxation during the cardiac-cycle (lusitropy). The cardiac-specific N-terminal TnI domain is not captured in crystal structures of troponin or in cryo-EM reconstructions of thin filaments; thus, its global impact on thin filament structure and function is uncertain. Here, we used protein-protein docking and molecular dynamics simulation-based protocols to build a troponin model that was guided by and hence consistent with the recent seminal Yamada structure of Ca2+-activated thin filaments. We find that when present on thin filaments, phosphorylated Ser23/24 along with adjacent polar TnI residues interact closely with both tropomyosin and the N-lobe of TnC during our simulations. These interactions would likely bias tropomyosin to an off-state positioning on actin. In situ, such enhanced relaxation kinetics would promote cardiac lusitropy.

Membranes under the Magnetic Lens: A Dive into the Diverse World of Membrane Protein Structures Using Cryo-EM

Membrane proteins are highly diverse in both structure and function and can, therefore, present different challenges for structure determination. They are biologically important for cells and organisms as gatekeepers for information and molecule transfer across membranes, but each class of membrane proteins can present unique obstacles to structure determination. Historically, many membrane protein structures have been investigated using highly engineered constructs or using larger fusion proteins to improve solubility and/or increase particle size. Other strategies included the deconstruction of the full-length protein to target smaller soluble domains. These manipulations were often required for crystal formation to support X-ray crystallography or to circumvent lower resolution due to high noise and dynamic motions of protein subdomains. However, recent revolutions in membrane protein biochemistry and cryo-electron microscopy now provide an opportunity to solve high resolution structures of both large, >1 megadalton (MDa), and small, <100 kDa (kDa), drug targets in near-native conditions, routinely reaching resolutions around or below 3 Å. This review provides insights into how the recent advances in membrane biology and biochemistry, as well as technical advances in cryo-electron microscopy, help us to solve structures of a large variety of membrane protein groups, from small receptors to large transporters and more complex machineries.

Structural dynamics of SARS-CoV-2 nucleocapsid protein induced by RNA binding

The nucleocapsid (N) protein of the SARS-CoV-2 virus, the causal agent of COVID-19, is a multifunction phosphoprotein that plays critical roles in the virus life cycle, including transcription and packaging of the viral RNA. To play such diverse roles, the N protein has two globular RNA-binding modules, the N- (NTD) and C-terminal (CTD) domains, which are connected by an intrinsically disordered region. Despite the wealth of structural data available for the isolated NTD and CTD, how these domains are arranged in the full-length protein and how the oligomerization of N influences its RNA-binding activity remains largely unclear. Herein, using experimental data from electron microscopy and biochemical/biophysical techniques combined with molecular modeling and molecular dynamics simulations, we show that, in the absence of RNA, the N protein formed structurally dynamic dimers, with the NTD and CTD arranged in extended conformations. However, in the presence of RNA, the N protein assumed a more compact conformation where the NTD and CTD are packed together. We also provided an octameric model for the full-length N bound to RNA that is consistent with electron microscopy images of the N protein in the presence of RNA. Together, our results shed new light on the dynamics and higher-order oligomeric structure of this versatile protein.

The nucleocapsid (N) protein of the SARS-CoV-2 virus plays an essential role in virus particle assembly as it specifically binds to and wraps the virus genomic RNA into a well-organized structure known as the ribonucleoprotein. Understanding how the N protein wraps around the virus RNA is critical for the development of strategies to inhibit virus assembly within host cells. One of the limitations regarding the molecular structure of the ribonucleoprotein, however, is that the N protein has several unstructured and mobile regions that preclude the resolution of its full atomic structure. Moreover, the N protein can form higher-order oligomers, both in the presence and absence of RNA. Here we employed computational methods, supported by experimental data, to simulate the N protein structural dynamics in the absence and presence of RNA. Our data suggest that the N protein forms structurally dynamic dimers in the absence of RNA, with its structured N- and C-terminal domains oriented in extended conformations. In the presence of RNA, however, the N protein assumes a more compact conformation. Our model for the oligomeric structure of the N protein bound to RNA helps to understand how N protein dimers interact to each other to form the ribonucleoprotein.

Probing Structural Perturbation of Biomolecules by Extracting Cryo-EM Data Heterogeneity

Single-particle cryogenic electron microscopy (cryo-EM) has become an indispensable tool to probe high-resolution structural detail of biomolecules. It enables direct visualization of the biomolecules and opens a possibility for averaging molecular images to reconstruct a three-dimensional Coulomb potential density map. Newly developed algorithms for data analysis allow for the extraction of structural heterogeneity from a massive and low signal-to-noise-ratio (SNR) cryo-EM dataset, expanding our understanding of multiple conformational states, or further implications in dynamics, of the target biomolecule. This review provides an overview that briefly describes the workflow of single-particle cryo-EM, including imaging and data processing, and new methods developed for analyzing the data heterogeneity to understand the structural variability of biomolecules.

Cryo-EM analysis of Ebola virus nucleocapsid-like assembly

This protocol describes the reconstitution of the filamentous Ebola virus nucleocapsid-like assembly in vitro. This is followed by solving the cryo-EM structure using helical reconstruction, and flexible fitting of the existing model into the 5.8 Å cryo-EM map. The protocol can be applied to other filamentous viral protein assemblies, particularly those with high flexibility and moderate resolution maps, which present technical challenges to model building.

For complete details on the use and execution of this profile, please refer to Su et al. (2018).

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Preparation of Ebola nucleocapsid-like assembly for cryo-EM

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Cryo-EM helical reconstruction of flexible filamentous protein assembly

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Flexible fitting of protein model into cryo-EM density at moderate resolution

Chimeric CRISPR-CasX enzymes and guide RNAs for improved genome editing activity

A compact protein with a size of <1,000 amino acids, the CRISPR-associated protein CasX is a fundamentally distinct RNA-guided nuclease when compared to Cas9 and Cas12a. Although it can induce RNA-guided genome editing in mammalian cells, the activity of CasX is less robust than that of the widely used S. pyogenes Cas9. Here, we show that structural features of two CasX homologs and their guide RNAs affect the R-loop complex assembly and DNA cleavage activity. Cryo-EM-based structural engineering of either the CasX protein or the guide RNA produced two new CasX genome editors (DpbCasX-R3-v2 and PlmCasX-R1-v2) with significantly improved DNA manipulation efficacy. These results advance both the mechanistic understanding of CasX and its application as a genome-editing tool.

How advances in cryo-electron tomography have contributed to our current view of bacterial cell biology

Advancements in the field of cryo-electron tomography have greatly contributed to our current understanding of prokaryotic cell organization and revealed intracellular structures with remarkable architecture. In this review, we present some of the prominent advancements in cryo-electron tomography, illustrated by a subset of structural examples to demonstrate the power of the technique. More specifically, we focus on technical advances in automation of data collection and processing, sample thinning approaches, correlative cryo-light and electron microscopy, and sub-tomogram averaging methods. In turn, each of these advances enabled new insights into bacterial cell architecture, cell cycle progression, and the structure and function of molecular machines. Taken together, these significant advances within the cryo-electron tomography workflow have led to a greater understanding of prokaryotic biology. The advances made the technique available to a wider audience and more biological questions and provide the basis for continued advances in the near future.

Energy landscape of the SARS-CoV-2 reveals extensive conformational heterogeneity

Cryo-electron microscopy (cryo-EM) has produced a number of structural models of the SARS-CoV-2 spike, already prompting biomedical outcomes. However, these reported models and their associated electrostatic potential maps represent an unknown admixture of conformations stemming from the underlying energy landscape of the spike protein. As with any protein, some of the spike's conformational motions are expected to be biophysically relevant, but cannot be interpreted only by static models. Using experimental cryo-EM images, we present the energy landscape of the glycosylated spike protein, and identify the diversity of low-energy conformations in the vicinity of its open (so called 1RBD-up) state. The resulting atomic refinement reveal global and local molecular rearrangements that cannot be inferred from an average 1RBD-up cryo-EM model. Here we report varied degrees of "openness" in global conformations of the 1RBD-up state, not revealed in the single-model interpretations of the density maps, together with conformations that overlap with the reported models. We discover how the glycan shield contributes to the stability of these low-energy conformations. Five out of six binding sites we analyzed, including those for engaging ACE2, therapeutic mini-proteins, linoleic acid, two different kinds of antibodies, switch conformations between their known apo- and holo-conformations, even when the global spike conformation is 1RBD-up. This apo-to-holo switching is reminiscent of a conformational preequilibrium. We found only one binding site, namely that of AB-C135 remains in apo state within all the sampled free energy-minimizing models, suggesting an induced fit mechanism for the docking of this antibody to the spike.

Bridging the N-terminal and middle domains in FliG of the flagellar rotor

Flagella are necessary for bacterial movement and contribute to various aspects of virulence. They are complex cylindrical structures built of multiple molecular rings with self-assembly properties. The flagellar rotor is composed of the MS-ring and the C-ring. The FliG protein of the C-ring is central to flagellar assembly and function due to its roles in linking the C-ring with the MS-ring and in torque transmission from stator to rotor. No high-resolution structure of an assembled C-ring has been resolved to date, and the conformation adopted by FliG within the ring is unclear due to variations in available crystallographic data. Here, we use molecular dynamics (MD) simulations to study the conformation and dynamics of FliG in different states of assembly, including both in physiologically relevant and crystallographic lattice environments. We conclude that the linker between the FliG N-terminal and middle domain likely adopts an extended helical conformation in vivo, in contrast with the contracted conformation observed in some previous X-ray studies. We further support our findings with integrative model building of full-length FliG and a FliG ring model that is compatible with cryo-electron tomography (cryo-ET) and electron microscopy (EM) densities of the C-ring. Collectively, our study contributes to a better mechanistic understanding of the flagellar rotor assembly and its function.

Structural dynamics of receptor recognition and pH-induced dissociation of full-length Clostridioides difficile Toxin B

Clostridioides difficile secretes Toxin B (TcdB) as one of its major virulence factors, which binds to intestinal epithelial and subepithelial receptors, including frizzled proteins and chondroitin sulfate proteoglycan 4 (CSPG4). Here, we present cryo-EM structures of full-length TcdB in complex with the CSPG4 domain 1 fragment (D1401-560) at cytosolic pH and the cysteine-rich domain of frizzled-2 (CRD2) at both cytosolic and acidic pHs. CSPG4 specifically binds to the autoprocessing and delivery domains of TcdB via networks of salt bridges, hydrophobic and aromatic/proline interactions, which are disrupted upon acidification eventually leading to CSPG4 drastically dissociating from TcdB. In contrast, FZD2 moderately dissociates from TcdB under acidic pH, most likely due to its partial unfolding. These results reveal structural dynamics of TcdB during its preentry step upon endosomal acidification, which provide a basis for developing therapeutics against C. difficile infections.

Membrane Mixer: A Toolkit for Efficient Shuffling of Lipids in Heterogeneous Biological Membranes

Molecular dynamics (MD) simulations of biological membranes have achieved such levels of sophistication that are commonly used to predict unresolved structures and various properties of lipids and to substantiate experimental data. While achieving sufficient sampling of lipid dynamics remains a major challenge, a commonly used method to improve lipid sampling, e.g., in terms of specific interactions with membrane-associated proteins, is to randomize the initial arrangement of lipid constituents in multiple replicas of simulations, without changing the overall lipid composition of the membrane of interest. Here, we introduce a method that can rapidly generate multiple replicas of lipid bilayers with different spatial and conformational configurations for any given lipid composition. The underlying algorithm, which allows one to shuffle lipids at any desired level, relies on the application of an external potential, here referred to as the "carving potential", that removes clashes/entanglements before lipid positions are exchanged (shuffled), thereby minimizing the energy penalty due to abrupt lipid repositioning. The method is implemented as "Membrane Mixer Plugin (MMP) 1.0" in VMD, with a convenient graphical user interface that guides the user in setting various options and parameters. The plugin is fully automated and generates new membrane replicas more rapidly and conveniently than other analogous tools. The plugin and its capabilities introduced here can be extended to include additional features in future versions.

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Application of Homology Modeling by Enhanced Profile-Profile Alignment and Flexible-Fitting Simulation to Cryo-EM Based Structure Determination

Application of cryo-electron microscopy (cryo-EM) is crucially important for ascertaining the atomic structure of large biomolecules such as ribosomes and protein complexes in membranes. Advances in cryo-EM technology and software have made it possible to obtain data with near-atomic resolution, but the method is still often capable of producing only a density map with up to medium resolution, either partially or entirely. Therefore, bridging the gap separating the density map and the atomic model is necessary. Herein, we propose a methodology for constructing atomic structure models based on cryo-EM maps with low-to-medium resolution. The method is a combination of sensitive and accurate homology modeling using our profile–profile alignment method with a flexible-fitting method using molecular dynamics simulation. As described herein, this study used benchmark applications to evaluate the model constructions of human two-pore channel 2 (one target protein in CASP13 with its structure determined using cryo-EM data) and the overall structure of Enterococcus hirae V-ATPase complex.

A prototype protein nanocage minimized from carboxysomes with gated oxygen permeability

Protein nanocages (PNCs) in cells and viruses have inspired the development of self-assembling protein nanomaterials for various purposes. Despite the successful creation of artificial PNCs, the de novo design of PNCs with defined permeability remains challenging. Here, we report a prototype oxygen-impermeable PNC (OIPNC) assembled from the vertex protein of the β-carboxysome shell, CcmL, with quantum dots as the template via interfacial engineering. The structure of the cage was solved at the atomic scale by combined solid-state NMR spectroscopy and cryoelectron microscopy, showing icosahedral assembly of CcmL pentamers with highly conserved interpentamer interfaces. Moreover, a gating mechanism was established by reversibly blocking the pores of the cage with molecular patches. Thus, the oxygen permeability, which was probed by an oxygen sensor inside the cage, can be completely controlled. The CcmL OIPNC represents a PNC platform for oxygen-sensitive or oxygen-responsive storage, catalysis, delivery, sensing, etc.

EMDA: A Python package for Electron Microscopy Data Analysis

An open-source Python library EMDA for cryo-EM map and model manipulation is presented with a specific focus on validation. The use of several functionalities in the library is presented through several examples. The utility of local correlation as a metric for identifying map-model differences and unmodeled regions in maps, and how it is used as a metric of map-model validation is demonstrated. The mapping of local correlation to individual atoms, and its use to draw insights on local signal variations are discussed. EMDA’s likelihood-based map overlay is demonstrated by carrying out a superposition of two domains in two related structures. The overlay is carried out first to bring both maps into the same coordinate frame and then to estimate the relative movement of domains. Finally, the map magnification refinement in EMDA is presented with an example to highlight the importance of adjusting the map magnification in structural comparison studies.

Computational Modeling of the Virucidal Inhibition Mechanism for Broad-Spectrum Antiviral Nanoparticles and HPV16 Capsid Segments

Solid core nanoparticles (NPs) coated with sulfonated ligands that mimic heparan sulfate proteoglycans (HSPGs) can exhibit virucidal activity against many viruses that utilize HSPG interactions with host cells for the initial stages of infection. How the interactions of these NPs with large capsid segments of HSPG-interacting viruses lead to their virucidal activity has been unclear. Here, we describe the interactions between sulfonated NPs and segments of the human papilloma virus type 16 (HPV16) capsids using atomistic molecular dynamics simulations. The simulations demonstrate that the NPs primarily bind at the interfaces of two HPV16 capsid proteins. After equilibration, the distances and angles between capsid proteins in the capsid segments are larger for the systems in which the NPs bind at the interfaces of capsid proteins. Over time, NP binding can lead to breaking of contacts between two neighboring proteins. The revealed mechanism of NPs targeting the interfaces between pairs of capsid proteins can be utilized for designing new generations of virucidal materials and contribute to the development of new broad-spectrum non-toxic virucidal materials.

Stabilization of Ribosomal RNA of the Small Subunit by Spermidine in Staphylococcus aureus

Cryo-electron microscopy is now used as a method of choice in structural biology for studying protein synthesis, a process mediated by the ribosome machinery. In order to achieve high-resolution structures using this approach, one needs to obtain homogeneous and stable samples, which requires optimization of ribosome purification in a species-dependent manner. This is especially critical for the bacterial small ribosomal subunit that tends to be unstable in the absence of ligands. Here, we report a protocol for purification of stable 30 S from the Gram-positive bacterium Staphylococcus aureus and its cryo-EM structures: in presence of spermidine at a resolution ranging between 3.4 and 3.6 Å and in its absence at 5.3 Å. Using biochemical characterization and cryo-EM, we demonstrate the importance of spermidine for stabilization of the 30 S via preserving favorable conformation of the helix 44.

Mechanism of Rad26-assisted rescue of stalled RNA polymerase II in transcription-coupled repair

Transcription-coupled repair is essential for the removal of DNA lesions from the transcribed genome. The pathway is initiated by CSB protein binding to stalled RNA polymerase II. Mutations impairing CSB function cause severe genetic disease. Yet, the ATP-dependent mechanism by which CSB powers RNA polymerase to bypass certain lesions while triggering excision of others is incompletely understood. Here we build structural models of RNA polymerase II bound to the yeast CSB ortholog Rad26 in nucleotide-free and bound states. This enables simulations and graph-theoretical analyses to define partitioning of this complex into dynamic communities and delineate how its structural elements function together to remodel DNA. We identify an allosteric pathway coupling motions of the Rad26 ATPase modules to changes in RNA polymerase and DNA to unveil a structural mechanism for CSB-assisted progression past less bulky lesions. Our models allow functional interpretation of the effects of Cockayne syndrome disease mutations.