Heterochromatin protein 1 (HP1) plays a central role in establishing and maintaining constitutive heterochromatin. However, the mechanisms underlying HP1-nucleosome interactions and their contributions to heterochromatin functions remain elusive. In this study, we employed a multidisciplinary approach to unravel the interactions between human HP1α and nucleosomes. We have elucidated the cryo-EM structure of an HP1α dimer bound to an H2A.Z nucleosome, revealing that the HP1α dimer interfaces with nucleosomes at two distinct sites. The primary binding site is located at the N-terminus of histone H3, specifically at the trimethylated K9 (K9me3) region, while a novel secondary binding site is situated near histone H2B, close to nucleosome superhelical location 4 (SHL4). Our biochemical data further demonstrates that HP1α binding influences the dynamics of DNA on the nucleosome. It promotes DNA unwrapping near the nucleosome entry and exit sites while concurrently restricting DNA accessibility in the vicinity of SHL4. This study offers a model that explains how HP1α functions in heterochromatin maintenance and gene silencing, particularly in the context of H3K9me-dependent mechanisms. Additionally, it sheds light on the H3K9me-independent role of HP1 in responding to DNA damage.

Glucose, the primary cellular energy source, is metabolized through glycolysis initiated by the rate-limiting enzyme Hexokinase (HK). In energy-demanding tissues like the brain, HK1 is the dominant isoform, primarily localized on mitochondria, crucial for efficient glycolysis-oxidative phosphorylation coupling and optimal energy generation. This study unveils a unique mechanism regulating HK1 activity, glycolysis, and the dynamics of mitochondrial coupling, mediated by the metabolic sensor enzyme O-GlcNAc transferase (OGT). OGT catalyzes reversible O-GlcNAcylation, a post-translational modification, influenced by glucose flux. Elevated OGT activity induces dynamic O-GlcNAcylation of HK1's regulatory domain, subsequently promoting the assembly of the glycolytic metabolon on the outer mitochondrial membrane. This modification enhances HK1's mitochondrial association, orchestrating glycolytic and mitochondrial ATP production. Mutations in HK1's O-GlcNAcylation site reduce ATP generation, affecting synaptic functions in neurons. The study uncovers a novel pathway that bridges neuronal metabolism and mitochondrial function via OGT and the formation of the glycolytic metabolon, offering new prospects for tackling metabolic and neurological disorders.

The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making. All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow. The source code is publicly available on GitHub: https://github.com/radical-collaboration/MDFF-EnTK The preprint of this research is submitted on bioRxiv, doi: https://doi.org/10.1101/2021.12.07.471672 To obtain maximum compression of the data, the tar command used to generate this tarball was: GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/

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.

The cell distributes energy between two main branches: locomotion, and reproduction. This partitioning scheme is dynamic, and dependent on the cell's environment. In view of deconvoluting this energy balance, we present an investigation of the costs associated with cellular locomotion in Bacteroidetes. This exemplary organism displays a unique gliding motility. Such translocation is independent of well-known propulsive structures like flagella, pili, or fimbriae; rather, the cell uniquely glides on a surface. I will present a ‘rotary rack and pinion’ model engaging the Type IX Secretion System rotary motor to describe the gliding mechanism. (1) Using a Bayesian model of maximum entropy, we investigate the torque-guided, conformational landscape of the Secretion System in the periplasmic space. After 2 microseconds of simulation, an allosteric network is discovered that couples the power-strokes in the peripheral domains with the rotatory proton-pumping in the transmembrane part of the motor. (2) In analogy with our past computations of rotary ATPases, a combination of pH-simulations and Anisotropic Network Model are separately employed to decipher the chemo-mechanical forces that drive proton gradient across the motor. These coupling forces are monitored using light microscopy and tuned biochemically using mutations to control the gliding movements of the bacteria. (3) Finally, guided by recent cryo-EM experiments, both the periplasmic and membrane domains of the secretion system are integrated to drive a kinetic description of the energy cost associated with gliding motility, comparing with the growth necessities.

Glucose is the primary fuel of cells, and its metabolism starts with the activity of the first rate-limiting enzyme Hexokinase (HK). HK1 is the dominant isoform in the brain and is mainly localized near the mitochondrial outer membrane. The positioning of HK1 on mitochondria is critical because it couples two energy generation pathways: Glycolysis and mitochondrial oxidative phosphorylation. Here, we report a new molecular mechanism that regulates HK1 activity and mitochondrial localization via the metabolic sensor enzyme O-GlcNAc transferase (OGT).

The infrared spectrum of CD379Br and CD381Br between 900 cm-1 and 1400 cm-1 has been analyzed at high resolution. In this region, two fundamental vibrational states, v2 = 1 and v5 = 1, an overtone state, v3 = 2, and a combination state, v3 = v6 = 1, have been analyzed for both isotopologues. As found in other halomethane molecules, strong Coriolis resonances couple the v2 = 1 state to the v5 = 1 state, and similar resonances were also used to describe the coupling found between the v5 = 1 state to the v3 = 2 state. A new determination of the K- dependent constant A0 was performed for each isotopologue through the use of perturbation-allowed transitions. The values for A0 determined from the analysis are 2.6001898(26) and 2.6001905(27) for CD379Br and CD381Br, respectively. Density functional theory calculations were performed to examine the efficacy of high-level theo-retical calculations to accurately predict spectroscopic constants. The density functional theory calculations had variable success with the largest errors associated with the prediction of the Delta B rotational constants of the interacting states.

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 side chains. 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.

The infrared spectrum of CD379Br and CD381Br between 900 cm-1 and 1400 cm-1 has been analyzed at high resolution. In this region, two fundamental vibrational states, v2 = 1 and v5 = 1, an overtone state, v3 = 2, and a combination state, v3 = v6 = 1, have been analyzed for both isotopologues. As found in other halomethane molecules, strong Coriolis resonances couple the v2 = 1 state to the v5 = 1 state, and similar resonances were also used to describe the coupling found between the v5 = 1 state to the v3 = 2 state. A new determination of the K-dependent constant A0 was performed for each isotopologue through the use of perturbation-allowed transitions. The values for A0 determined from the analysis are 2.6001898(26) and 2.6001905(27) for CD379Br and CD381Br, respectively. Ab initio calculations were performed to examine the efficacy of high-level theoretical calculations to accurately predict spectroscopic constants. The ab initio calculations had variable success with the largest errors associated with the prediction of the DB rotational constants of the interacting states.

In this paper, we develop a formulation to utilize reinforcement learning and sampling-based robotics planning to derive low free energy transition pathways between two known states. Our formulation uses Jarzynski’s equality and the stiffspring approximation to obtain point estimates of energy, and construct an informed path search with atomistic resolution. At the core of this framework, is our first ever attempt we use a policy driven adaptive steered molecular dynamics (SMD) to control our molecular dynamics simulations. We show that both the reinforcement learning and robotics planning realization of the RL-guided framework can solve for pathways on toy analytical surfaces and alanine dipeptide.

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.

Adenovirus derived vectors, based on chimpanzee adenovirus Y25 (ChAdOx1) and human adenovirus type 26 are proving critical in combatting the 2019 SARS-CoV-2 pandemic. Following emergency use authorisation, scale up in vaccine administration has inevitably revealed vaccine related adverse effects; too rare to observe even in large Phase-III clinical trials. These include vaccine-induced thrombotic thrombocytopenia (VITT), an ultra-rare adverse event in which patients develop life-threatening blood clots 5-24 days following vaccination. To investigate vector-host interactions of ChAdOx1 underpinning VITT we solved the structure of the ChAdOx1 capsid by CryoEM, and the structure of the primary receptor tropism determining fiber-knob protein by crystallography. These structural insights have enabled us to unravel key protein interactions involved in ChAdOx1 cell entry and a possible means by which it may generate misplaced immunity to platelet factor 4 (PF4), a protein involved in coagulation. We use in vitro cell binding assays to show that the fiber-knob protein uses coxsackie and adenovirus receptor (CAR) as a high affinity binding partner, while it does not form a stable interface with CD46. Computational simulations identified a putative mechanism by which the ChAdOx1 capsid interacts with PF4 by binding in the spaces between hexon proteins, with downstream implications for the causes of VITT. Summary We present the structure of the ChAdOx1 viral vector, derived from chimpanzee adenovirus Y25 at 4.2Å resolution1. ChAdOx1 is in global use in the AstraZeneca vaccine, ChAdOx1 nCoV-19/AZD-1222, to combat the SARS-CoV-2 coronavirus pandemic. Recently observed, rare, adverse events make detailed mechanistic understanding of this vector key to informing proper treatment of affected patients and the development of safer viral vectors. Here, we determine a primary mechanism ChAdOx1 uses to attach to cells is coxsackie and adenovirus receptor (CAR), a protein which is identical in humans and chimpanzees. We demonstrate the vector does not form a stable CD46 interaction, a common species B adenovirus receptor, via its primary attachment protein. Further, we reveal the surface of the ChAdOx1 viral capsid has a strong electronegative potential. Molecular simulations suggest this charge, together with shape complementarity, are a mechanism by which an oppositely charged protein, platelet factor 4 (PF4) may bind the vector surface. PF4 is a key protein involved in the formation of blood clots2, and the target of auto-antibodies in heparin-induced immune thrombotic thrombocytopenia (HITT)3, an adverse reaction to heparin therapy which presents similarly to vaccine-induced immune thrombotic thrombocytopenia (VITT), a rare complication of ChAdOx1 nCoV-19 vaccination4–6. We propose a mechanism in which the ChAdOx1-PF4 complex may stimulate the production of antibodies against PF4, leading to delayed blood clot formation, as observed in VITT.

Recent advances in cryo-electron microscopy (cryo-EM) has enabled modeling macromolecular complexes that are essential components of life. The density maps obtained from cryo-EM experiments is often integrated with ab initio, knowledge-driven or first principles-based computational methods to build, fit and refine protein structures inside the electron density maps. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with a set of multiple physical models all of which contributes to the average observation

Cryo-EM is a powerful method for determining protein structures. But it requires computational assistance. Physics-based computations have the power to give low-free-energy structures and ensembles of populations, but have been computationally limited to only small soluble proteins. Here, we introduce CryoFold. By integrating data of varying sparsity from electron density maps of 3–5 Å resolution with coarse-grained physical knowledge of secondary and tertiary interactions, CryoFold determines ensembles of protein structures directly from sequence. We give six examples showing its broad capabilities, over proteins ranging from 72 to 2000 residues, including membrane and multi-domain proteins, and including results from two EMDB competitions. The ensembles CryoFold predicts starting from the density data of a single known protein conformation encompass multiple low-energy conformations, all of which are experimentally validated and biologically relevant.

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

In this paper, we utilized generative models, and reformulate it for problems in molecular dynamics (MD) simulation, by introducing an MD potential energy component to our generative model. By incorporating potential energy as calculated from TorchMD into a conditional generative framework, we attempt to construct a low-potential energy route of transformation between the helix~$\rightarrow$~coil structures of a protein. We show how to add an additional loss function to conditional generative models, motivated by potential energy of molecular configurations, and also present an optimization technique for such an augmented loss function. Our results show the benefit of this additional loss term on synthesizing realistic molecular trajectories.

We observe previously unknown interactions between clinically important adenovirus vector capsids, platelet factor 4, and CAR.

The v(3) parallel, and v(6) perpendicular infrared-active vibrational bands have been analyzed for both (CD3Br)-Br-79 and (CD3Br)-Br-81 at 0.0015 cm(-1) resolution. The band origins for the v(3) = 1 state are 577.28925(2) cm(-1) and 575.97685(2) cm(-1) for the (CD3Br)-Br-79 and (CD3Br)-Br-81 isotopologues, respectively; for the v(6) = 1 state the band origins are 713.46997(1) cm(-1) and 713.38156(1) cm(-1), respectively. The v(3) =1 and v(6)= 1 vibra-tional states are possibly the only unperturbed vibrational states in CD3Br, and thus yield the most reli-able infrared spectroscopy-based determination of the ground state rotational constants. The spectroscopic constants for both vibrational states, as well as the ground vibrational state were improved compared to previous studies through a direct fit of the vibrational bands, as well as a separate fit of the ground state combination differences. Ab initio calculations were performed to examine the efficacy of high-level theoretical calculations to accurately predict spectroscopic constants. Though not used in fitting the experimental data, nuclear quadrupole hyperfine splitting by the bromine atoms was observed in both vibrational states, an uncommon observation in the infrared spectra of polyatomic molecules. (C) 2020 Elsevier Inc. All rights reserved.