Elucidating molecular mechanisms of protoxin-II state-specific binding to the human NaV1.7 channel.

Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells, and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-II (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.

A multiscale predictive digital twin for neurocardiac modulation.

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the ß-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.

Elucidating Molecular Mechanisms of Protoxin-2 State-specific Binding to the Human NaV1.7 Channel.

Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-2 (PTx2) has high selectivity for hNaV1.7 and serves as a valuable scaffold to design novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD as well as the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.

Elucidation of a dynamic interplay between a beta-2 adrenergic receptor, its agonist, and stimulatory G protein.

G protein-coupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligand-induced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta-2 adrenergic receptor (ß2AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (Gs). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to ß2AR by Gs protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from ß2AR and the conformational interconversions of Gs between closed and open conformations in the NE(+)-ß2AR-Gs ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter Gs α subunit (Gsα) conformational transitions. Our simulations showed that the interdomain movement and the stacking of Gsα α1 and α5 helices are significant for increasing the distance between the Gsα and ß2AR, which may indicate a partial dissociation of Gsα The distance increase commences when Gsα is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of ß2AR interacting with Gsα, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCR-mediated modulation of G protein activation.

Dendrimer-Peptide Conjugates for Effective Blockade of the Interactions between SARS-CoV-2 Spike Protein and Human ACE2 Receptor.

The coronavirus disease 2019 (COVID-19) pandemic has threatened the stability of global healthcare, which is becoming an endemic issue. Despite the development of various treatment strategies to fight COVID-19, the currently available treatment options have shown varied efficacy. Herein, we have developed an avidity-based SARS-CoV-2 antagonist using dendrimer-peptide conjugates (DPCs) for effective COVID-19 treatment. Two different peptide fragments obtained from angiotensin-converting enzyme 2 (ACE2) were integrated into a single sequence, followed by the conjugation to poly(amidoamine) (PAMAM) dendrimers. We hypothesized that the strong multivalent binding avidity endowed by dendrimers would help peptides effectively block the interaction between SARS-CoV-2 and ACE2, and this antagonist effect would be dependent upon the generation (size) of the dendrimers. To assess this, binding kinetics of the DPCs prepared from generation 4 (G4) and G7 PAMAM dendrimers to spike protein of SARS-CoV-2 were quantitatively measured using surface plasmon resonance. The larger dendrimer-based DPCs exhibited significantly enhanced binding strength by 3 orders of magnitude compared to the free peptides, whereas the smaller one showed a 12.8-fold increase only. An in vitro assay using SARS-CoV-2-mimicking microbeads also showed the improved SARS-CoV-2 blockade efficiency of the G7-peptide conjugates compared to G4. In addition, the interaction between the DPCs and SARS-CoV-2 was analyzed using molecular dynamics (MD) simulation, providing an insight into how the dendrimer-mediated multivalent binding effect can enhance the SARS-CoV-2 blockade. Our findings demonstrate that the DPCs having strong binding to SARS-CoV-2 effectively block the interaction between ACE2 and SARS-CoV-2, providing a potential as a high-affinity drug delivery system to direct anti-COVID payloads to the virus.

Photochemical control of bacterial gene expression based on trans encoded genetic switches.

Controlling gene expression by light with fine spatiotemporal resolution not only allows understanding and manipulating fundamental biological processes but also fuels the development of novel therapeutic strategies. In complement to exploiting optogenetic tools, photochemical strategies mostly rely on the incorporation of photo-responsive small molecules into the corresponding biomacromolecular scaffolds. Therefore, generally large synthetic effort is required and the switching of gene expression in both directions within a single system remains a challenge. Here, we report a trans encoded ribo-switch, which consists of an engineered tRNA mimicking structure (TMS), under control of small photo-switchable signalling molecules. The signalling molecules consist of two amino glycoside molecules that are connected via an azobenzene unit. The light responsiveness of our system originates from the photo-switchable noncovalent interactions between the signalling molecule and the TMS switch, leading to the demonstration of photochemically controlled expression of two different genes. We believe that this modular design will provide a powerful platform for controlling the expression of other functional proteins with high spatiotemporal resolution employing light as a stimulus.

Sulfoglycodendrimer Therapeutics for HIV-1 and SARS-CoV-2.

Hexavalent sulfoglycodendrimers (SGDs) are synthesized as mimics of host cell heparan sulfate proteoglycans (HSPGs) to inhibit the early stages in viral binding/entry of HIV-1 and SARS-CoV-2. Using an HIV neutralization assay, the most promising of the seven candidates are found to have sub-micromolar anti-HIV activities. Molecular dynamics simulations are separately implemented to investigate how/where the SGDs interacted with both pathogens. The simulations revealed that the SGDs: 1) develop multivalent binding with polybasic regions within and outside of the V3 loop on glycoprotein 120 (gp120) for HIV-1, and consecutively bind with multiple gp120 subunits, and 2) interact with basic amino acids in both the angiotensin-converting enzyme 2 (ACE2) and HSPG binding regions of the Receptor Binding Domain (RBD) from SARS-CoV-2. These results illustrate the considerable potential of SGDs as inhibitors in viral binding/entry of both HIV-1 and SARS-CoV-2 pathogens, leading the way for further development of this class of molecules as broad-spectrum antiviral agents.

Retrained Generic Antibodies Can Recognize SARS-CoV-2.

The dramatic impact novel viruses can have on humans could be more quickly mitigated if generic antibodies already present in one's system are temporarily retrained to recognize these viruses. This type of intervention can be administered during the early stages of infection, while a specific immune response is being developed. With this idea in mind, double-faced peptide-based boosters were computationally designed to allow recognition of SARS-CoV-2 by Hepatitis B antibodies. One booster face is made of ACE2-mimic peptides that can bind to the receptor binding domain (RBD) of SARS-CoV-2. The other booster face is composed of a Hepatitis B core-antigen, targeting the Hepatitis B antibody fragment. Molecular dynamics simulations revealed that the designed boosters have a highly specific and stable binding to both the RBD and the antibody fragment (AF). This approach can provide a cheap and efficient neutralization of emerging pathogens.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the past decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of adaptive (smart) therapeutics. Here, a computational strategy is developed to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), the templates are gradually modified by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the last decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of
adaptive (smart) therapeutics. Here, we develop a computational strategy to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), we gradually modify the templates by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries
of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.
.

Tuning of the Aggregation Behavior of Fluorinated Polymeric Nanoparticles for Improved Therapeutic Efficacy.

Incorporation of fluorinated moieties in polymeric nanoparticles has been shown in many instances to increase their uptake by living cells and, hence, has proven to be a useful approach to enhancing delivery to cells. However, it remains unclear how incorporation of fluorine affects critical transport processes, such as interactions with membranes, intracellular transport, and tumor penetration. In this study, we investigate the influence of fluorine on transport properties using a series of rationally designed poly(oligo(ethylene glycol) methyl ether acrylate)-block-perfluoropolyether (poly(OEGA)m-PFPE) copolymers. Copolymers with different fluorine contents were prepared and exhibit aggregate in solution in a manner dependent on the fluorine content. Doxorubicin-conjugated poly(OEGA)20-PFPE nanoparticles with lower fluorine content exist in solution as unimers, leading to greater exposure of hydrophobic PFPE segments to the cell surface. This, in turn, results in greater cellular uptake, deeper tumor penetration, as well as enhanced therapeutic efficacy compared to that with the micelle-state nanoaggregates (poly(OEGA)10-PFPE and poly(OEGA)5-PFPE) with higher fluorine content but with less PFPE exposed to the cell membranes. Our results demonstrate that the aggregation behavior of these fluorinated polymers plays a critical role in internalization and transport in living cells and 3D spheroids, providing important design criteria for the preparation of highly effective delivery agents.

Computational Design of ACE2-Based Peptide Inhibitors of SARS-CoV-2.

Peptide inhibitors against the SARS-CoV-2 coronavirus, currently causing a worldwide pandemic, are designed and simulated. The inhibitors are mostly formed by two sequential self-supporting α-helices (bundle) extracted from the protease domain (PD) of angiotensin-converting enzyme 2 (ACE2), which bind to the SARS-CoV-2 receptor binding domains. Molecular dynamics simulations revealed that the α-helical peptides maintain their secondary structure and provide a highly specific and stable binding (blocking) to SARS-CoV-2. To provide a multivalent binding to the SARS-CoV-2 receptors, many such peptides could be attached to the surfaces of nanoparticle carriers. The proposed peptide inhibitors could provide simple and efficient therapeutics against the COVID-19 disease.

Modified cyclodextrins as broad-spectrum antivirals.

Viral infections kill millions of people and new antivirals are needed. Nontoxic drugs that irreversibly inhibit viruses (virucidal) are postulated to be ideal. Unfortunately, all virucidal molecules described to date are cytotoxic. We recently developed nontoxic, broad-spectrum virucidal gold nanoparticles. Here, we develop further the concept and describe cyclodextrins, modified with mercaptoundecane sulfonic acids, to mimic heparan sulfates and to provide the key nontoxic virucidal action. We show that the resulting macromolecules are broad-spectrum, biocompatible, and virucidal at micromolar concentrations in vitro against many viruses [including herpes simplex virus (HSV), respiratory syncytial virus (RSV), dengue virus, and Zika virus]. They are effective ex vivo against both laboratory and clinical strains of RSV and HSV-2 in respiratory and vaginal tissue culture models, respectively. Additionally, they are effective when administrated in mice before intravaginal HSV-2 inoculation. Lastly, they pass a mutation resistance test that the currently available anti-HSV drug (acyclovir) fails.

Nanoparticle Conjugation Stabilizes and Multimerizes ß-Hairpin Peptides To Effectively Target PD-1/PD-L1 ß-Sheet-Rich Interfaces.

ß-Hairpin peptides present great potential as antagonists against ß-sheet-rich protein surfaces, of which wide and flat geometries are typically "undruggable" with small molecules. Herein, we introduce a peptide-dendrimer conjugate (PDC) approach that stabilizes the ß-hairpin structure of the peptide via intermolecular forces and the excluded volume effect as well as exploits the multivalent binding effect. Because of the synergistic advantages, the PDCs based on a ß-hairpin peptide isolated from an engineered programmed death-1 (PD-1) protein showed significantly higher affinity (avidity) to their binding counterpart, programmed death-ligand 1 (PD-L1), as compared to free peptides (by up to 5 orders of magnitude). The enhanced binding kinetics with high selectivity was translated into an improved immune checkpoint inhibitory effect in vitro, at a level comparable to (if not better than) that of a full-size monoclonal antibody. The results demonstrate the potential of the PDC system as a novel class of inhibitors targeting ß-strand-rich protein surfaces, such as PD-1 and PD-L1, displaying its potential as a new cancer immunotherapy platform.

An Organometallic Strategy for Assembling Atomically Precise Hybrid Nanomaterials.

For decades, chemists have strived to mimic the intricate design and diverse functions of naturally occurring systems through the bioinspired synthesis of programmable inorganic nanomaterials. The development of thiol-capped gold nanoparticles (AuNPs) has driven advancement in this area; however, although versatile and readily accessible, hybrid AuNPs are rarely atomically precise, which limits control over their surface topology and therefore the study of complex structure-function relationships. Here, we present a bottom-up approach to the systematic assembly of atomically precise hybrid nanoclusters employing a strategy that mimics the synthetic ease with which thiol-capped AuNPs are normally constructed, while producing well-defined covalent nanoscale assemblies with diverse surface topologies. For the first time, using a structurally characterized cluster-based organometallic building block, we demonstrate the systematic synthesis of nanoclusters with multivalent binding capabilities to complex protein targets.

Multivalent Cluster Nanomolecules for Inhibiting Protein-Protein Interactions.

Multivalent protein-protein interactions serve central roles in many essential biological processes, ranging from cell signaling and adhesion to pathogen recognition. Uncovering the rules that govern these intricate interactions is important not only to basic biology and chemistry but also to the applied sciences where researchers are interested in developing molecules to promote or inhibit these interactions. Here we report the synthesis and application of atomically precise inorganic cluster nanomolecules consisting of an inorganic core and a covalently linked densely packed layer of saccharides. These hybrid agents are stable under biologically relevant conditions and exhibit multivalent binding capabilities, which enable us to study the complex interactions between glycosylated structures and a dendritic cell lectin receptor. Importantly, we find that subtle changes in the molecular structure lead to significant differences in the nanomolecule's protein-binding properties. Furthermore, we demonstrate an example of using these hybrid nanomolecules to effectively inhibit protein-protein interactions in a human cell line. Ultimately, this work reveals an intricate interplay between the structural design of multivalent agents and their biological activities toward protein surfaces.

Novel Oligo-Guanidyl-PEG Carrier Forming Rod-Shaped Polyplexes.

A novel unconventional supramolecular oligo-cationic structure (Agm6-M-PEG-OCH3) has been synthesized to yield high efficiency therapeutic oligonucleotide (ON) delivery. Agm6-M-PEG-OCH3 was obtained by a multistep protocol that included the conjugation of agmatine (Agm) moieties to maltotriose (M), which was further derivatized with one poly(ethylene glycol) (PEG) chain. Gel electrophoresis analysis showed that the 19 base pairs dsDNA model ON completely associates with Agm6-M-PEG-OCH3 at 3 N/P molar ratio, which is in agreement with the in silico molecular predictions. Isothermal titration calorimetry (ITC) analyses showed that the Agm6-M-PEG-OCH3/ON association occurs through a combination of mechanisms depending on the N/P ratios resulting in different nanostructures. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) revealed that the Agm6-M-PEG-OCH3/ON polyplexes have rod-shape structure with a mean diameter of 50-75 nm and aspect ratio depending on the N/P ratio. The polyplexes were stable over time in buffer, while a slight size increase was observed in the presence of serum proteins. Cell culture studies showed that neither Agm6-M-PEG-OCH3 nor polyplexes displayed cytotoxic effects. Cellular uptake depended on the cell line and polyplex composition: cellular internalization was higher in the case of MCF-7 and KB cells compared to MC3T3-E1 cells and polyplexes with smaller aspect ratio were taken-up by cells more efficiently than polyplexes with higher aspect ratio. Finally, preliminary studies showed that our novel carrier efficiently delivered ONs into cells providing gene silencing.

Supramolecular Control of Azobenzene Switching on Nanoparticles.

The reversible photoisomerization of azobenzene has been utilized to construct a plethora of systems in which optical, electronic, catalytic, and other properties can be controlled by light. However, owing to azobenzene's hydrophobic nature, most of these examples have been realized only in organic solvents, and systems operating in water are relatively scarce. Here, we show that by coadsorbing the inherently hydrophobic azobenzenes with water-solubilizing ligands on the same nanoparticulate platforms, it is possible to render them essentially water-soluble. To this end, we developed a modified nanoparticle functionalization procedure allowing us to precisely fine-tune the amount of azobenzene on the functionalized nanoparticles. Molecular dynamics simulations helped us to identify two distinct supramolecular architectures (depending on the length of the background ligand) on these nanoparticles, which can explain their excellent aqueous solubilities. Azobenzenes adsorbed on these water-soluble nanoparticles exhibit highly reversible photoisomerization upon exposure to UV and visible light. Importantly, the mixed-monolayer approach allowed us to systematically investigate how the background ligand affects the switching properties of azobenzene. We found that the nature of the background ligand has a profound effect on the kinetics of azobenzene switching. For example, a hydroxy-terminated background ligand is capable of accelerating the back-isomerization reaction by more than 6000-fold. These results pave the way toward the development of novel light-responsive nanomaterials operating in aqueous media and, in the long run, in biological environments.

Catalytic transport of molecular cargo using diffusive binding along a polymer track.

Transport at the molecular scale is a prerequisite for the development of future molecular factories. Here, we have designed oligoanionic molecular sliders on polycationic tracks that exploit Brownian motion and diffusive binding to transport cargo without using a chemical fuel. The presence of the polymer tracks increases the rate of bimolecular reactions between modified sliders by over two orders of magnitude. Molecular dynamics simulations showed that the sliders not only diffuse, but also jump and hop surprisingly efficiently along polymer tracks. Inspired by acetyl-coenzyme A transporting and delivering acetyl groups in many essential biochemical processes, we developed a new and unconventional type of catalytic transport involving sliders (including coenzyme A) picking up, transporting and selectively delivering molecular cargo. Furthermore, we show that the concept of diffusive binding can also be utilized for the spatially controlled transport of chemical groups across gels. This work represents a new concept for designing functional nanosystems based on random Brownian motion.