Enhanced sampling molecular dynamics simulations correctly predict the diverse activities of a series of stiff-stilbene G-quadruplex DNA ligands

Ligands with the capability to bind G-quadruplexes (G4s) specifically, and to control G4 structure and behaviour, offer great potential in the development of novel therapies, technologies and functional materials. Most known ligands bind to a pre-formed topology, but G4s are highly dynamic and a small number of ligands have been discovered that influence these folding equilibria. Such ligands may be useful as probes to understand the dynamic nature of G4 in vivo, or to exploit the polymorphism of G4 in the development of molecular devices. To date, these fascinating molecules have been discovered serendipitously. There is a need for tools to predict such effects to drive ligand design and development, and for molecular-level understanding of ligand binding mechanisms and associated topological perturbation of G4 structures. Here we study the G4 binding mechanisms of a family of stiff-stilbene G4 ligands to human telomeric DNA using molecular dynamics (MD) and enhanced sampling (metadynamics) MD simulations. The simulations predict a variety of binding mechanisms and effects on G4 structure for the different ligands in the series. In parallel, we characterize the binding of the ligands to the G4 target experimentally using NMR and CD spectroscopy. The results show good agreement between the simulated and experimentally observed binding modes, binding affinities and ligand-induced perturbation of the G4 structure. The simulations correctly predict ligands that perturb G4 topology. Metadynamics simulations are shown to be a powerful tool to aid development of molecules to influence G4 structure, both in interpreting experiments and to help in the design of these chemotypes.

Enhanced sampling molecular dynamics simulations and solution-phase experiments come together to demonstrate the diverse effects of G4-interactive small molecules.     

Targeting structural features of viral genomes with a nano-sized supramolecular drug

RNA targeting is an exciting frontier for drug design. Intriguing targets include functional RNA structures in structurally-conserved untranslated regions (UTRs) of many lethal viruses. However, computational docking screens, valuable in protein structure targeting, fail for inherently flexible RNA. Herein we harness MD simulations with Markov state modeling to enable nanosize metallo-supramolecular cylinders to explore the dynamic RNA conformational landscape of HIV-1 TAR untranslated region RNA (representative for many viruses) replicating experimental observations. These cylinders are exciting as they have unprecedented nucleic acid binding and are the first supramolecular helicates shown to have anti-viral activity in cellulo: the approach developed in this study provides additional new insight about how such viral UTR structures might be targeted with the cylinder binding into the heart of an RNA-bulge cavity, how that reduces the conformational flexibility of the RNA and molecular details of the insertion mechanism. The approach and understanding developed represents a new roadmap for design of supramolecular drugs to target RNA structural motifs across biology and nucleic acid nanoscience.

MD simulations and Markov state modeling explore induced fit binding of metallo-helicates to bulges in dynamic TAR RNA, reproduce experimental data, show how RNA conformational flexibility is reduced, and give mechanistic insight into insertion.     

Large scale relative protein ligand binding affinities using non-equilibrium alchemy

Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily set up and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) foundations, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome performing on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein–ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ mol⁻¹, equivalent to Schrödinger''s FEP+ AUE of 3.66 ± 0.14 kJ mol⁻¹. For the first time, a setup is presented for overall high precision and high accuracy relative protein–ligand alchemical free energy calculations based on open-source software.

Relative ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design.     

Hierarchical dynamics in allostery following ATP hydrolysis monitored by single molecule FRET measurements and MD simulations

We report on a study that combines advanced fluorescence methods with molecular dynamics (MD) simulations to cover timescales from nanoseconds to milliseconds for a large protein. This allows us to delineate how ATP hydrolysis in a protein causes allosteric changes at a distant protein binding site, using the chaperone Hsp90 as test system. The allosteric process occurs via hierarchical dynamics involving timescales from nano- to milliseconds and length scales from Ångstroms to several nanometers. We find that hydrolysis of one ATP is coupled to a conformational change of Arg380, which in turn passes structural information via the large M-domain α-helix to the whole protein. The resulting structural asymmetry in Hsp90 leads to the collapse of a central folding substrate binding site, causing the formation of a novel collapsed state (closed state B) that we characterise structurally. We presume that similar hierarchical mechanisms are fundamental for information transfer induced by ATP hydrolysis through many other proteins.

We report on a study that combines advanced fluorescence methods with molecular dynamics simulations to cover timescales from nanoseconds to milliseconds for a large protein, the chaperone Hsp90.     

Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment

The amlyoid-β peptide (Aβ) is closely linked to the development of Alzheimer''s disease. Molecular dynamics (MD) simulations have become an indispensable tool for studying the behavior of this peptide at the atomistic level. General key aspects of MD simulations are the force field used for modeling the peptide and its environment, which is important for accurate modeling of the system of interest, and the length of the simulations, which determines whether or not equilibrium is reached. In this study we address these points by analyzing 30-μs MD simulations acquired for Aβ40 using seven different force fields. We assess the convergence of these simulations based on the convergence of various structural properties and of NMR and fluorescence spectroscopic observables. Moreover, we calculate Markov state models for the different MD simulations, which provide an unprecedented view of the thermodynamics and kinetics of the amyloid-β peptide. This further allows us to provide answers for pertinent questions, like: which force fields are suitable for modeling Aβ? (a99SB-UCB and a99SB-ILDN/TIP4P-D); what does Aβ peptide really look like? (mostly extended and disordered) and; how long does it take MD simulations of Aβ to attain equilibrium? (at least 20–30 μs). We believe the analyses presented in this study will provide a useful reference guide for important questions relating to the structure and dynamics of Aβ in particular, and by extension other similar disordered proteins.

The convergence of MD simulations is tested using varying measures for the intrinsically disordered amyloid-β peptide (Aβ). Markov state models show that 20–30 μs of MD is needed to reliably reproduce the thermodynamics and kinetics of Aβ.     

Distinct electronic structures and bonding interactions in inverse-sandwich samarium and ytterbium biphenyl complexes

Inverse-sandwich samarium and ytterbium biphenyl complexes were synthesized by the reduction of their trivalent halide precursors with potassium graphite in the presence of biphenyl. While the samarium complex had a similar structure as previously reported rare earth metal biphenyl complexes, with the two samarium ions bound to the same phenyl ring, the ytterbium counterpart adopted a different structure, with the two ytterbium ions bound to different phenyl rings. Upon the addition of crown ether to encapsulate the potassium ions, the inverse-sandwich samarium biphenyl structure remained intact; however, the ytterbium biphenyl structure fell apart with the concomitant formation of a divalent ytterbium crown ether complex and potassium biphenylide. Spectroscopic and computational studies were performed to gain insight into the electronic structures and bonding interactions of these samarium and ytterbium biphenyl complexes. While the ytterbium ions were found to be divalent with a 4f¹⁴ electron configuration and form a primarily ionic bonding interaction with biphenyl dianion, the samarium ions were in the trivalent state with a 4f⁵ electron configuration and mainly utilized the 5d orbitals to form a δ-type bonding interaction with the π* orbitals of the biphenyl tetraanion, showing covalent character.

Inverse-sandwich samarium and ytterbium biphenyl complexes were synthesized and characterized by X-ray crystallography. Combined experimental and computational studies indicated that they have distinct electronic structures and bonding interactions.     

Mechanochemical synthesis of glycine oligomers in a virtual rotational diamond anvil cell

Mechanochemistry of glycine under compression and shear at room temperature is predicted using quantum-based molecular dynamics (QMD) and a simulation design based on rotational diamond anvil cell (RDAC) experiments. Ensembles of high throughput semiempirical density functional tight binding (DFTB) simulations are used to identify chemical trends and bounds for glycine chemistry during rapid shear under compressive loads of up to 15.6 GPa. Significant chemistry is found to occur during compressive shear above 10 GPa. Recovered products consist of small molecules such as water, structural analogs to glycine, heterocyclic molecules, large oligomers, and polypeptides including the simplest polypeptide glycylglycine at up to 4% mass fraction. The population and size of oligomers generally increases with pressure. A number of oligomeric polypeptide precursors and intermediates are also identified that consist of two or three glycine monomers linked together through C–C, C–N, and/or C–O bridges. Even larger oligomers also form that contain peptide C–N bonds and exhibit branched structures. Many of the product molecules exhibit one or more chiral centers. Our simulations demonstrate that athermal mechanical compressive shearing of glycine is a plausible prebiotic route to forming polypeptides.

Compressive shearing forces can induce mechanochemical oligomerization reactions in glycine.     

Water-induced formation of an alkali-ion dimer in cryptomelane nanorods

Tunneled metal oxides such as α-Mn₈O₁₆ (hollandite) have proven to be compelling candidates for charge-storage materials in high-density batteries. In particular, the tunnels can support one-dimensional chains of K⁺ ions (which act as structure-stabilizing dopants) and H₂O molecules, as these chains are favored by strong H-bonds and electrostatic interactions. In this work, we examine the role of water molecules in enhancing the stability of K⁺-doped α-Mn₈O₁₆ (cryptomelane). The combined experimental and theoretical analyses show that for high enough concentrations of water and tunnel-ions, H₂O displaces K⁺ ions from their natural binding sites. This displacement becomes energetically favorable due to the formation of K²⁺ dimers, thereby modifying the stoichiometric charge of the system. These findings have potentially significant technological implications for the consideration of cryptomelane as a Li⁺/Na⁺ battery electrode. Our work establishes the functional role of water in altering the energetics and structural properties of cryptomelane, an observation that has frequently been overlooked in previous studies.

Water displaces potassium ions and initiates the formation of a homonuclear dimer ion (K²⁺) in the tunnels of hollandite.     

Interpretable molecular models for molybdenum disulfide and insight into selective peptide recognition

Molybdenum disulfide (MoS₂) is a layered material with outstanding electrical and optical properties. Numerous studies evaluate the performance in sensors, catalysts, batteries, and composites that can benefit from guidance by simulations in all-atom resolution. However, molecular simulations remain difficult due to lack of reliable models. We introduce an interpretable force field for MoS₂ with record performance that reproduces structural, interfacial, and mechanical properties in 0.1% to 5% agreement with experiments. The model overcomes structural instability, deviations in interfacial and mechanical properties by several 100%, and empirical fitting protocols in earlier models. It is compatible with several force fields for molecular dynamics simulation, including the interface force field (IFF), CVFF, DREIDING, PCFF, COMPASS, CHARMM, AMBER, and OPLS-AA. The parameters capture polar covalent bonding, X-ray structure, cleavage energy, infrared spectra, bending stability, bulk modulus, Young''s modulus, and contact angles with polar and nonpolar solvents. We utilized the models to uncover the binding mechanism of peptides to the MoS₂ basal plane. The binding strength of several 7mer and 8mer peptides scales linearly with surface contact and replacement of surface-bound water molecules, and is tunable in a wide range from −86 to −6 kcal mol⁻¹. The binding selectivity is multifactorial, including major contributions by van-der-Waals coordination and charge matching of certain side groups, orientation of hydrophilic side chains towards water, and conformation flexibility. We explain the relative attraction and role of the 20 amino acids using computational and experimental data. The force field can be used to screen and interpret the assembly of MoS₂-based nanomaterials and electrolyte interfaces up to a billion atoms with high accuracy, including multiscale simulations from the quantum scale to the microscale.

We introduce a cutting-edge force field for molybdenum disulfide and use it to uncover mechanisms of peptide recognition and design.     

High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs). The global exploration problem is decomposed into a set of separate MD trajectories that can be restarted within a selective process to achieve sufficient phase-space sampling. Accurate statistical properties can be obtained through reweighting. Within this highly parallel setup, the Tinker-HP package can be powered by an arbitrary large number of GPUs on supercomputers, reducing exploration time from years to days. This approach is used to tackle the urgent modeling problem of the SARS-CoV-2 Main Protease (M^pro) producing more than 38 μs of all-atom simulations of its apo (ligand-free) dimer using the high-resolution AMOEBA PFF. The first 15.14 μs simulation (physiological pH) is compared to available non-PFF long-timescale simulation data. A detailed clustering analysis exhibits striking differences between FFs, with AMOEBA showing a richer conformational space. Focusing on key structural markers related to the oxyanion hole stability, we observe an asymmetry between protomers. One of them appears less structured resembling the experimentally inactive monomer for which a 6 μs simulation was performed as a basis for comparison. Results highlight the plasticity of the M^pro active site. The C-terminal end of its less structured protomer is shown to oscillate between several states, being able to interact with the other protomer, potentially modulating its activity. Active and distal site volumes are found to be larger in the most active protomer within our AMOEBA simulations compared to non-PFFs as additional cryptic pockets are uncovered. A second 17 μs AMOEBA simulation is performed with protonated His172 residues mimicking lower pH. Data show the protonation impact on the destructuring of the oxyanion loop. We finally analyze the solvation patterns around key histidine residues. The confined AMOEBA polarizable water molecules are able to explore a wide range of dipole moments, going beyond bulk values, leading to a water molecule count consistent with experimental data. Results suggest that the use of PFFs could be critical in drug discovery to accurately model the complexity of the molecular interactions structuring M^pro.

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs).     

Forwards and backwards – synthesis of Laurencia natural products using a biomimetic and retrobiomimetic strategy incorporating structural reassignment of laurefurenynes C–F

Laurefurenynes C–F are four natural products isolated from Laurencia species whose structures were originally determined on the basis of extensive nuclear magnetic resonance experiments. On the basis of a proposed biogenesis, involving a tricyclic oxonium ion as a key intermediate, we have reassigned the structures of these four natural products and synthesized the four reassigned structures using a biomimetic approach demonstrating that they are the actual structures of the natural products. In addition, we have developed a synthesis of the enantiomers of the natural products laurencin and deacetyllaurencin from the enantiomer of (E)-laurefucin using an unusual retrobiomimetic strategy. All of these syntheses have been enabled by the use of tricyclic oxonium ions as pivotal synthetic intermediates.

The synthesis and structural reassignment of laurefurenynes C–F has been achieved, with the new structures fitting with a proposed biosynthesis. Also reported is the synthesis of ent-laurencin and ent-deacetyllaurencin via a retrobiomimetic approach.     

Unprecedented hour-long residence time of a cation in a left-handed G-quadruplex

Cations are critical for the folding and assembly of nucleic acids. In G-quadruplex structures, cations can bind between stacked G-tetrads and coordinate with negatively charged guanine carbonyl oxygens. They usually exchange between binding sites and with the bulk in solution with time constants ranging from sub-millisecond to seconds. Here we report the first observation of extremely long-lived K⁺ and NH₄⁺ ions, with an exchange time constant on the order of an hour, when coordinated at the center of a left-handed G-quadruplex DNA. A single-base mutation, that switched one half of the structure from left- to right-handed conformation resulting in a right–left hybrid G-quadruplex, was shown to remove this long-lived behaviour of the central cation.

An extremely long-lived cation has been detected in left-handed G-quadruplexes.     

Discovery of cryptic allosteric sites using reversed allosteric communication by a combined computational and experimental strategy

Allostery, which is one of the most direct and efficient methods to fine-tune protein functions, has gained increasing recognition in drug discovery. However, there are several challenges associated with the identification of allosteric sites, which is the fundamental cornerstone of drug design. Previous studies on allosteric site predictions have focused on communication signals propagating from the allosteric sites to the orthosteric sites. However, recent biochemical studies have revealed that allosteric coupling is bidirectional and that orthosteric perturbations can modulate allosteric sites through reversed allosteric communication. Here, we proposed a new framework for the prediction of allosteric sites based on reversed allosteric communication using a combination of computational and experimental strategies (molecular dynamics simulations, Markov state models, and site-directed mutagenesis). The desirable performance of our approach was demonstrated by predicting the known allosteric site of the small molecule MDL-801 in nicotinamide dinucleotide (NAD⁺)-dependent protein lysine deacetylase sirtuin 6 (Sirt6). A potential novel cryptic allosteric site located around the L116, R119, and S120 residues within the dynamic ensemble of Sirt6 was identified. The allosteric effect of the predicted site was further quantified and validated using both computational and experimental approaches. This study proposed a state-of-the-art computational pipeline for detecting allosteric sites based on reversed allosteric communication. This method enabled the identification of a previously uncharacterized potential cryptic allosteric site on Sirt6, which provides a starting point for allosteric drug design that can aid the identification of candidate pockets in other therapeutic targets.

Using reversed allosteric communication, we performed MD simulations, MSMs, and mutagenesis experiments, to discover allosteric sites. It reproduced the known allosteric site for MDL-801 on Sirt6 and uncovered a novel cryptic allosteric Pocket X.     

Mechanism of inhibition of SARS-CoV-2 Mpro by N3 peptidyl Michael acceptor explained by QM/MM simulations and design of new derivatives with tunable chemical reactivity

The SARS-CoV-2 main protease (M^pro) is essential for replication of the virus responsible for the COVID-19 pandemic, and one of the main targets for drug design. Here, we simulate the inhibition process of SARS-CoV-2 M^pro with a known Michael acceptor (peptidyl) inhibitor, N3. The free energy landscape for the mechanism of the formation of the covalent enzyme-inhibitor product is computed with QM/MM molecular dynamics methods. The simulations show a two-step mechanism, and give structures and calculated barriers in good agreement with experiment. Using these results and information from our previous investigation on the proteolysis reaction of SARS-CoV-2 M^pro, we design two new, synthetically accessible N3-analogues as potential inhibitors, in which the recognition and warhead motifs are modified. QM/MM modelling of the mechanism of inhibition of M^pro by these novel compounds indicates that both may be promising candidates as drug leads against COVID-19, one as an irreversible inhibitor and one as a potential reversible inhibitor.

QM/MM simulations identify the mechanism of reaction of N3, a covalent peptidyl inhibitor of SARS-CoV-2 main protease. Modelling of two novel proposed compounds, B1 and B2, suggests that reversibility of covalent inhibition could be tailored.     

Et3SiH + KOtBu provide multiple reactive intermediates that compete in the reactions and rearrangements of benzylnitriles and indolenines

The combination of potassium tert-butoxide and triethylsilane is unusual because it generates multiple different types of reactive intermediates simultaneously that provide access to (i) silyl radical reactions, (ii) hydrogen atom transfer reactions to closed shell molecules and to radicals, (iii) electron transfer reductions and (iv) hydride ion chemistry, giving scope for unprecedented outcomes. Until now, reactions with this reagent pair have generally been explained by reference to one of the intermediates, but we now highlight the interplay and competition between them.

The combination of potassium tert-butoxide and triethylsilane provides simultaneous access to multiple reactive intermediates, radicals, H-atom donors, hydride donors and electron donors, giving scope for unprecedented reaction outcomes.     

Observations of tetrel bonding between sp3-carbon and THF

We report the direct observation of tetrel bonding interactions between sp³-carbons of the supramolecular synthon 3,3-dimethyl-tetracyanocyclopropane (1) and tetrahydrofuran in the gas and crystalline phase. The intermolecular contact is established via σ-holes and is driven mainly by electrostatic forces. The complex manifests distinct binding geometries when captured in the crystalline phase and in the gas phase. We elucidate these binding trends using complementary gas phase quantum chemical calculations and find a total binding energy of −11.2 kcal mol⁻¹ for the adduct. Our observations pave the way for novel strategies to engineer sp³-C centred non-covalent bonding schemes for supramolecular chemistry.

sp³-C⋯THF tetrel bonding was observed in the crystalline state and in the gas phase. Density functional calculations revealed interaction energies up to −11.2 kcal mol⁻¹ and showed that these adducts are held together mainly by electrostatics.     

Molecularly-tunable nanoelectrode arrays created by harnessing intermolecular interactions

Intermolecular interactions play a critical role in the binding strength of molecular assemblies on surfaces. The ability to harness them enables molecularly-tunable interfacial structures and properties. Herein we report the tuning of the intermolecular interactions in monolayer assemblies derived from organothiols of different structures for the creation of nanoelectrode arrays or ensembles with effective mass transport by a molecular-level perforation strategy. The homo- and hetero-intermolecular interactions can be fully controlled, which is demonstrated not only by thermodynamic analysis of the fractional coverage but also by surface infrared reflection absorption and X-ray photoelectron spectroscopic characterizations. This understanding enables controllable electrochemical perforation for the creation of ensembles or arrays of channels across the monolayer thickness with molecular and nanoscale dimensions. Redox reactions on the nanoelectrode array display molecular tunability with a radial diffusion characteristic in good agreement with theoretical simulation results. These findings have implications for designing membrane-type ion-gating, electrochemical sensing, and electrochemical energy storage devices with molecular level tunability.

Intermolecular interactions in monolayer assembly are harnessed for creating molecularly-tunable nanoelectrode arrays or ensembles.