Enhanced TROSY Effect in [2-19 F, 2-13 C] Adenosine and ATP Analogs Facilitates NMR Spectroscopy of Very Large Biological RNAs in Solution.

Large RNAs are central to cellular functions, but characterizing such RNAs remains challenging by solution NMR. We present two labeling technologies based on [2-19 F, 2-13 C]-adenosine, which allow the incorporation of aromatic 19 F-13 C spin pairs. The labels when coupled with the transverse relaxation optimized spectroscopy (TROSY) enable us to probe RNAs comprising up to 124 nucleotides. With our new [2-19 F, 2-13 C]-adenosine-phosphoramidite, all resonances of the human hepatitis B virus epsilon RNA could be readily assigned. With [2-19 F, 2-13 C]-adenosine triphosphate, the 124 nt pre-miR-17-NPSL1-RNA was produced via in vitro transcription and the TROSY spectrum of this 40 kDa [2-19 F, 2-13 C]-A-labeled RNA featured sharper resonances than the [2-1 H, 2-13 C]-A sample. The mutual cancelation of the chemical-shift-anisotropy and the dipole-dipole-components of TROSY-resonances leads to narrow linewidths over a wide range of molecular weights. With the synthesis of a non-hydrolysable [2-19 F, 2-13 C]-adenosine-triphosphate, we facilitate the probing of co-factor binding in kinase complexes and NMR-based inhibitor binding studies in such systems. Our labels allow a straightforward assignment for larger RNAs via a divide-and-conquer/mutational approach. The new [2-19 F, 2-13 C]-adenosine precursors are a valuable addition to the RNA NMR toolbox and will allow the study of large RNAs/RNA protein complexes in vitro and in cells.

X-ray Crystallography Module in MD Simulation Program Amber 2023. Refining the Models of Protein Crystals.

The MD simulation package Amber offers an attractive platform to refine crystallographic structures of proteins: (i) state-of-the-art force fields help to regularize protein coordinates and reconstruct the poorly diffracting elements of the structure, such as flexible loops; (ii) MD simulations restrained by the experimental diffraction data provide an effective strategy to optimize structural models of protein crystals, including explicitly modeled interstitial solvent as well as crystal contacts. Here, we present the new crystallography module xray, released as a part of the Amber 2023 package. This module contains functions to calculate and scale structure factors (including the contributions from bulk solvent), evaluate the maximum-likelihood-type crystallographic potential, and compute its derivative forces. The X-ray functionality of Amber no longer relies on external dependencies so that the full advantage of GPU acceleration can be taken. This makes it possible to refine in a short time hundreds of crystal models, including supercell models comprised of multiple unit cells. The new automated Amber-based refinement procedure leads to an appreciable improvement in Rfree (in some cases, by as much as 0.067) as well as MolProbity scores.

An RNA excited conformational state at atomic resolution.

Sparse and short-lived excited RNA conformational states are essential players in cell physiology, disease, and therapeutic development, yet determining their 3D structures remains challenging. Combining mutagenesis, NMR spectroscopy, and computational modeling, we determined the 3D structural ensemble formed by a short-lived (lifetime ~2.1 ms) lowly-populated (~0.4%) conformational state in HIV-1 TAR RNA. Through a strand register shift, the excited conformational state completely remodels the 3D structure of the ground state (RMSD from the ground state = 7.2 ± 0.9 Å), forming a surprisingly more ordered conformational ensemble rich in non-canonical mismatches. The structure impedes the formation of the motifs recognized by Tat and the super elongation complex, explaining why this alternative TAR conformation cannot activate HIV-1 transcription. The ability to determine the 3D structures of fleeting RNA states using the presented methodology holds great promise for our understanding of RNA biology, disease mechanisms, and the development of RNA-targeting therapeutics.

AmberTools.

AmberTools is a free and open-source collection of programs used to set up, run, and analyze molecular simulations. The newer features contained within AmberTools23 are briefly described in this Application note.

MD simulations of macromolecular crystals: Implications for the analysis of Bragg and diffuse scattering.

Some of our most detailed information about structure and dynamics of macromolecules comes from X-ray-diffraction studies in crystalline environments. More than 170,000 atomic models have been deposited in the Protein Data Bank, and the number of observations (typically of intensities of Bragg diffraction peaks) is generally quite large, when compared to other experimental methods. Nevertheless, the general agreement between calculated and observed intensities is far outside the experimental precision, and the majority of scattered photons fall between the sharp Bragg peaks, and are rarely taken into account. This chapter considers how molecular dynamics simulations can be used to explore the connections between microscopic behavior in a crystalline lattice and observed scattering intensities, and point the way to new atomic models that could more faithfully recapitulate Bragg intensities and extract useful information from the diffuse scattering that lies between those peaks.

Robust total X-ray scattering workflow to study correlated motion of proteins in crystals.

The breathing motions of proteins are thought to play a critical role in function. However, current techniques to study key collective motions are limited to spectroscopy and computation. We present a high-resolution experimental approach based on the total scattering from protein crystals at room temperature (TS/RT-MX) that captures both structure and collective motions. To reveal the scattering signal from protein motions, we present a general workflow that enables robust subtraction of lattice disorder. The workflow introduces two methods: GOODVIBES, a detailed and refinable lattice disorder model based on the rigid-body vibrations of a crystalline elastic network; and DISCOBALL, an independent method of validation that estimates the displacement covariance between proteins in the lattice in real space. Here, we demonstrate the robustness of this workflow and further demonstrate how it can be interfaced with MD simulations towards obtaining high-resolution insight into functionally important protein motions.

New experimental evidence for pervasive dynamics in proteins.

There is ample computational, but only sparse experimental data suggesting that pico-ns motions with 1 Å amplitude are pervasive in proteins in solution. Such motions, if present in reality, must deeply affect protein function and protein entropy. Several NMR relaxation experiments have provided insights into motions of proteins in solution, but they primarily report on azimuthal angle variations of vectors of covalently-linked atoms. As such, these measurements are not sensitive to distance fluctuations, and cannot but under-represent the dynamical properties of proteins. Here we analyze a novel NMR relaxation experiment to measure amide proton transverse relaxation rates in uniformly 15 N labeled proteins, and present results for protein domain GB1 at 283 and 303 K. These relaxation rates depend on fluctuations of dipolar interactions between 1 HN and many nearby protons on both the backbone and sidechains. Importantly, they also report on fluctuations in the distances between these protons. We obtained a large mismatch between rates computed from the crystal structure of GB1 and the experimental rates. But when the relaxation rates were calculated from a 200 ns molecular dynamics trajectory using a novel program suite, we obtained a substantial improvement in the correspondence of experimental and theoretical rates. As such, this work provides novel experimental evidence of widespread motions in proteins. Since the improvements are substantial, but not sufficient, this approach may also present a new benchmark to help improve the theoretical forcefields underlying the molecular dynamics calculations.

RNA Electrostatics: How Ribozymes Engineer Active Sites to Enable Catalysis.

Electrostatic interactions are fundamental to RNA structure and function, and intimately influenced by solvation and the ion atmosphere. RNA enzymes, or ribozymes, are catalytic RNAs that are able to enhance reaction rates over a million-fold, despite having only a limited repertoire of building blocks and available set of chemical functional groups. Ribozyme active sites usually occur at junctions where negatively charged helices come together, and in many cases leverage this strained electrostatic environment to recruit metal ions in solution that can assist in catalysis. Similar strategies have been implicated in related artificially engineered DNA enzymes. Herein, we apply Poisson-Boltzmann, 3D-RISM, and molecular simulations to study a set of metal-dependent small self-cleaving ribozymes (hammerhead, pistol, and Varkud satellite) as well as an artificially engineered DNAzyme (8-17) to examine electrostatic features and their relation to the recruitment of monovalent and divalent metal ions important for activity. We examine several fundamental roles for these ions that include: (1) structural integrity of the catalytically active state, (2) pKa tuning of residues involved in acid-base catalysis, and (3) direct electrostatic stabilization of the transition state via Lewis acid catalysis. Taken together, these examples demonstrate how RNA electrostatics orchestrates the site-specific and territorial binding of metal ions to play important roles in catalysis.

Colicin E1 opens its hinge to plug TolC.

The double membrane architecture of Gram-negative bacteria forms a barrier that is impermeable to most extracellular threats. Bacteriocin proteins evolved to exploit the accessible, surface-exposed proteins embedded in the outer membrane to deliver cytotoxic cargo. Colicin E1 is a bacteriocin produced by, and lethal to, Escherichia coli that hijacks the outer membrane proteins (OMPs) TolC and BtuB to enter the cell. Here, we capture the colicin E1 translocation domain inside its membrane receptor, TolC, by high-resolution cryo-electron microscopy to obtain the first reported structure of a bacteriocin bound to TolC. Colicin E1 binds stably to TolC as an open hinge through the TolC pore-an architectural rearrangement from colicin E1's unbound conformation. This binding is stable in live E. coli cells as indicated by single-molecule fluorescence microscopy. Finally, colicin E1 fragments binding to TolC plug the channel, inhibiting its native efflux function as an antibiotic efflux pump, and heightening susceptibility to three antibiotic classes. In addition to demonstrating that these protein fragments are useful starting points for developing novel antibiotic potentiators, this method could be expanded to other colicins to inhibit other OMP functions.

Bacteria are constantly warring with each other for space and resources. As a result, they have developed a range of molecular weapons to poison, damage or disable other cells. For instance, bacteriocins are proteins that can latch onto structures at the surface of enemy bacteria and push toxins through their outer membrane. Bacteria are increasingly resistant to antibiotics, representing a growing concern for modern healthcare. One way that they are able to survive is by using 'efflux pumps' studded through their external membranes to expel harmful drugs before these can cause damage. Budiardjo et al. wanted to test whether bacteriocins could interfere with this defence mechanism by blocking efflux pumps. Bacteriocins are usually formed of binding elements (which recognise specific target proteins) and of a 'killer tail' that can stab the cell. Experiments showed that the binding parts of a bacteriocin could effectively 'plug' efflux pumps in Escherichia coli bacteria: high-resolution molecular microscopy revealed how the bacteriocin fragment binds to the pump, while fluorescent markers showed that it attached to the surface of E. coli and stopped the efflux pumps from working. As a result, lower amounts of antibiotics were necessary to kill the bacteria when bacteriocins were present. The work by Budiardjo et al. could lead to new ways to combat bacteria that will reduce the need for current antibiotics. In the future, bacteriocins could also be harnessed to target other proteins than efflux pumps, allowing scientists to manipulate a range of bacterial processes.

Integral equation models for solvent in macromolecular crystals.

The solvent can occupy up to ∼70% of macromolecular crystals, and hence, having models that predict solvent distributions in periodic systems could improve the interpretation of crystallographic data. Yet, there are few implicit solvent models applicable to periodic solutes, and crystallographic structures are commonly solved assuming a flat solvent model. Here, we present a newly developed periodic version of the 3D-reference interaction site model (RISM) integral equation method that is able to solve efficiently and describe accurately water and ion distributions in periodic systems; the code can compute accurate gradients that can be used in minimizations or molecular dynamics simulations. The new method includes an extension of the Ornstein-Zernike equation needed to yield charge neutrality for charged solutes, which requires an additional contribution to the excess chemical potential that has not been previously identified; this is an important consideration for nucleic acids or any other charged system where most or all the counter- and co-ions are part of the "disordered" solvent. We present several calculations of proteins, RNAs, and small molecule crystals to show that x-ray scattering intensities and the solvent structure predicted by the periodic 3D-RISM solvent model are in closer agreement with the experiment than are intensities computed using the default flat solvent model in the refmac5 or phenix refinement programs, with the greatest improvement in the 2 to 4 Šrange. Prospects for incorporating integral equation models into crystallographic refinement are discussed.

Molecular dynamics analysis of a flexible loop at the binding interface of the SARS-CoV-2 spike protein receptor-binding domain.

Since the identification of the SARS-CoV-2 virus as the causative agent of the current COVID-19 pandemic, considerable effort has been spent characterizing the interaction between the Spike protein receptor-binding domain (RBD) and the human angiotensin converting enzyme 2 (ACE2) receptor. This has provided a detailed picture of the end point structure of the RBD-ACE2 binding event, but what remains to be elucidated is the conformation and dynamics of the RBD prior to its interaction with ACE2. In this work, we utilize molecular dynamics simulations to probe the flexibility and conformational ensemble of the unbound state of the receptor-binding domain from SARS-CoV-2 and SARS-CoV. We have found that the unbound RBD has a localized region of dynamic flexibility in Loop 3 and that mutations identified during the COVID-19 pandemic in Loop 3 do not affect this flexibility. We use a loop-modeling protocol to generate and simulate novel conformations of the CoV2-RBD Loop 3 region that sample conformational space beyond the ACE2 bound crystal structure. This has allowed for the identification of interesting substates of the unbound RBD that are lower energy than the ACE2-bound conformation, and that block key residues along the ACE2 binding interface. These novel unbound substates may represent new targets for therapeutic design.

Simulations of Kindlin-2 PIP binding domains reveal protonation-dependent membrane binding modes.

Kindlin-2, a member of the Kindlin family of peripheral membrane proteins, is important for integrin activation and stabilization of epidermal growth factor receptor. It associates with the cytoplasmic face of the plasma membrane via dedicated phosphatidylinositol phosphate binding domains located in the N-terminal F0 and Pleckstrin Homology domains. These domains have binding affinity for phosphatidylinositol 4,5-bisphosphate and, to a greater degree, phosphatidylinositol 3,4,5-trisphosphate. The biological significance of the differential binding of these phosphatidylinositol phosphates to Kindlin-2 and the mechanism by which they activate Kindlin-2 are not well understood. Recently, ssNMR identified the predominant protonation states of phosphatidylinositol 4,5-bisphosphate and phosphatidylinositol 3,4,5-trisphosphate near physiological pH in the presence of anionic lipids. Here, we perform atomistic simulation of the bound state of the Pleckstrin Homology and F0 domains of Kindlin-2 at membranes containing phosphatidylinositol 4,5-bisphosphate/phosphatidylinositol 3,4,5-trisphosphate with differing protonation states. This computational approach demonstrates that these two phosphatidylinositol phosphates differently modulate Kindlin-2 subdomain binding in a protonation-state-dependent manner. We speculate these variations in binding mode provide a mechanism for intracellular pH and Ca2+ influx to control the membrane binding behavior and activity of Kindlin-2.

Refinement of RNA Structures Using Amber Force Fields.

Atomic models for nucleic acids derived from X-ray diffraction data at low resolution provide much useful information, but the observed scattering intensities can be fit with models that can differ in structural detail. Tradtional geometric restraints favor models that have bond length and angle terms derived from small molecule crystal structures. Here we explore replacing these restraints with energy gradients derived from force fields, including recently developed integral equation models to account for the effects of water molecules and ions that are not part of the explicit model. We compare conventional and force-field based refinements for 22 RNA crystals, ranging in resolution from 1.1 to 3.6 Å. As expected, it can be important to account for solvent screening of charge-charge interactions, especially in the crowded environment of a nucleic acid crystal. The newly refined models can show improvements in torsion angles and hydrogen-bonding interactions, and can significantly reduce unfavorable atomic clashes, while maintaining or improving agreement with observed scattering intensities.

A quantitative model predicts how m6A reshapes the kinetic landscape of nucleic acid hybridization and conformational transitions.

N6-methyladenosine (m6A) is a post-transcriptional modification that controls gene expression by recruiting proteins to RNA sites. The modification also slows biochemical processes through mechanisms that are not understood. Using temperature-dependent (20°C-65°C) NMR relaxation dispersion, we show that m6A pairs with uridine with the methylamino group in the anti conformation to form a Watson-Crick base pair that transiently exchanges on the millisecond timescale with a singly hydrogen-bonded low-populated (1%) mismatch-like conformation in which the methylamino group is syn. This ability to rapidly interchange between Watson-Crick or mismatch-like forms, combined with different syn:anti isomer preferences when paired (~1:100) versus unpaired (~10:1), explains how m6A robustly slows duplex annealing without affecting melting at elevated temperatures via two pathways in which isomerization occurs before or after duplex annealing. Our model quantitatively predicts how m6A reshapes the kinetic landscape of nucleic acid hybridization and conformational transitions, and provides an explanation for why the modification robustly slows diverse cellular processes.

Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction.

Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently supported by comparisons to quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine.

Using quantum chemistry to estimate chemical shifts in biomolecules.

An automated fragmentation quantum mechanics/molecular mechanics approach (AFNMR) has shown promising results in chemical shift calculations for biomolecules. Sample results for ubiquitin, and an RNA hairpin and helix are presented, and used to recent directions in quantum calculations. Trends in chemical shift are stable with regards to change in density functional or basis sets, and the use of the small "pcSseg-0" basis, which was optimized for chemical shift prediction [1], opens the way to more extensive conformational averaging, which can often be necessary, even for fairly well-defined structures.

Solution NMR readily reveals distinct structural folds and interactions in doubly 13C- and 19F-labeled RNAs.

RNAs form critical components of biological processes implicated in human diseases, making them attractive for small-molecule therapeutics. Expanding the sites accessible to nuclear magnetic resonance (NMR) spectroscopy will provide atomic-level insights into RNA interactions. Here, we present an efficient strategy to introduce 19F-13C spin pairs into RNA by using a 5-fluorouridine-5'-triphosphate and T7 RNA polymerase-based in vitro transcription. Incorporating the 19F-13C label in two model RNAs produces linewidths that are twice as sharp as the commonly used 1H-13C spin pair. Furthermore, the high sensitivity of the 19F nucleus allows for clear delineation of helical and nonhelical regions as well as GU wobble and Watson-Crick base pairs. Last, the 19F-13C label enables rapid identification of a small-molecule binding pocket within human hepatitis B virus encapsidation signal epsilon (hHBV ε) RNA. We anticipate that the methods described herein will expand the size limitations of RNA NMR and aid with RNA-drug discovery efforts.

Coupled intra- and interdomain dynamics support domain cross-talk in Pin1.

The functional mechanisms of multidomain proteins often exploit interdomain interactions, or "cross-talk." An example is human Pin1, an essential mitotic regulator consisting of a Trp-Trp (WW) domain flexibly tethered to a peptidyl-prolyl isomerase (PPIase) domain, resulting in interdomain interactions important for Pin1 function. Substrate binding to the WW domain alters its transient contacts with the PPIase domain via means that are only partially understood. Accordingly, we have investigated Pin1 interdomain interactions using NMR paramagnetic relaxation enhancement (PRE) and molecular dynamics (MD) simulations. The PREs show that apo-Pin1 samples interdomain contacts beyond the range suggested by previous structural studies. They further show that substrate binding to the WW domain simultaneously alters interdomain separation and the internal conformation of the WW domain. A 4.5-µs all-atom MD simulation of apo-Pin1 suggests that the fluctuations of interdomain distances are correlated with fluctuations of WW domain interresidue contacts involved in substrate binding. Thus, the interdomain/WW domain conformations sampled by apo-Pin1 may already include a range of conformations appropriate for binding Pin1's numerous substrates. The proposed coupling between intra-/interdomain conformational fluctuations is a consequence of the dynamic modular architecture of Pin1. Such modular architecture is common among cell-cycle proteins; thus, the WW-PPIase domain cross-talk mechanisms of Pin1 may be relevant for their mechanisms as well.

Atomistic Simulations of Heme Dissociation Pathways in Human Methemoglobins Reveal Hidden Intermediates.

Heme dissociations disrupt function and structural integrity of human hemoglobin and trigger various cardiovascular complications. These events become significant in methemoglobins that have undergone autoxidation of ferrous into ferric heme. We have structurally characterized the heme disassociation pathways for adult tetrameric methemoglobins using all-atom molecular dynamics simulations. These reveal that bis-histidine hemichromes, characterized here by the coordination of heme iron to both the F8 (proximal) and E7 (distal) histidines, are seen as intermediates following dissociation of the water molecule distally bound to each heme iron. Later, the breaking of coordination between heme iron and proximal histidine disrupts the F helix and pushes it away from the heme cavity, enabling both bulk solvent penetration and disruption of tetramer interface interactions. The interactions inhibiting heme dissociation were then seen to be (i) either a direct or a water-molecule-mediated interaction between distal histidine and heme iron and (ii) stacking between heme and the αCE1/ßCD1 phenylalanine residue. These interactions are less important in the ß than in α subunits due to a more flexible ß subunit CE loop region. The absence of a distal histidine interaction in the H(E7)L mutant and increased heme cavity volume in the V(E11)A mutant both promoted heme escape from the protein interior. Adult and fetal hemoglobins were seen to share a general heme disassociation pathway and intermediates due to the conservation of key heme pocket residues. The intermediates seen here are analyzed in light of experimental studies of heme dissociation and pathways of certain hemoglobinopathies.