Computational Insights into Avidity of Polymeric Multivalent Binders

Insight into the thermo-responsive phase behavior of the P1 domain of α-synuclein using atomistic simulations

Biomolecular condensate formation driven by intrinsically disordered proteins (IDPs) is regulated by interactions between various domains of the proteins. Such condensates are implicated in various neurodegenerative diseases. The presynaptic intrinsically disordered protein, α-Syn is involved in the pathogenesis of Parkinson's disease. The central non-amyloid β-component (NAC) domain in the protein is considered to be a major driver of pathogenic aggregation, although recent studies have suggested that the P1 domain from the flanking N-terminal region can act as a 'master controller' for α-Syn function and aggregation. To gain molecular insight into the phase behavior of the P1 domain itself, we investigate how assemblies of P1 (residues 36-42) chains phase separate with varying temperatures using all-atom molecular dynamics simulations. The simulations reveal that P1 is able to phase separate above a lower critical solution temperature. Formation of a condensed phase is driven by exclusion of water molecules by the hydrophobic chains. P1 chain density in the condensate is determined by weak multi-chain interactions between the residues. Moreover, tyrosine (Y39) is involved in the formation of strongest contacts between residue pairs in the dense phase. These results provide a detailed picture of condensate formation by a key segment of the α-Syn molecule.

Integrative mapping reveals molecular features underlying the mechanism of nucleocytoplasmic transport

Nuclear Pore Complexes (NPCs) enable rapid, selective, and robust nucleocytoplasmic transport. To explain how transport emerges from the system components and their interactions, we used experimental data and theoretical information to construct an integrative Brownian dynamics model of transport through an NPC, coupled to a kinetic model of transport in the cell. The model recapitulates key aspects of transport for a wide range of molecular cargos, including pre-ribosomes and viral capsids. It quantifies how flexible phenylalanine-glycine (FG) repeat proteins raise an entropy barrier to passive diffusion and how this barrier is selectively lowered in facilitated diffusion by the many transient interactions of nuclear transport receptors with the FG repeats. Selective transport is enhanced by "fuzzy" multivalent interactions, redundant FG repeats, coupling to the energy-dependent RanGTP concentration gradient, and exponential dependence of transport kinetics on the transport barrier. Our model will facilitate rational modulation of the NPC and its artificial mimics.

Quantitative Prediction of Protein-Polyelectrolyte Binding Thermodynamics: Adsorption of Heparin-Analog Polysulfates to the SARS-CoV-2 Spike Protein RBD

Interactions of polyelectrolytes (PEs) with proteins play a crucial role in numerous biological processes, such as the internalization of virus particles into host cells. Although docking, machine learning methods, and molecular dynamics (MD) simulations are utilized to estimate binding poses and binding free energies of small-molecule drugs to proteins, quantitative prediction of the binding thermodynamics of PE-based drugs presents a significant obstacle in computer-aided drug design. This is due to the sluggish dynamics of PEs caused by their size and strong charge-charge correlations. In this paper, we introduce advanced sampling methods based on a force-spectroscopy setup and theoretical modeling to overcome this barrier. We exemplify our method with explicit solvent all-atom MD simulations of the interactions between anionic PEs that show antiviral properties, namely heparin and linear polyglycerol sulfate (LPGS), and the SARS-CoV-2 spike protein receptor binding domain (RBD). Our prediction for the binding free-energy of LPGS to the wild-type RBD matches experimentally measured dissociation constants within thermal energy, k B T, and correctly reproduces the experimental PE-length dependence. We find that LPGS binds to the Delta-variant RBD with an additional free-energy gain of 2.4 k B T, compared to the wild-type RBD, due to the additional presence of two mutated cationic residues contributing to the electrostatic energy gain. We show that the LPGS-RBD binding is solvent dominated and enthalpy driven, though with a large entropy-enthalpy compensation. Our method is applicable to general polymer adsorption phenomena and predicts precise binding free energies and reconfigurational friction as needed for drug and drug-delivery design.

Bond clusters control rupture force limit in shear loaded histidine-Ni2+ metal-coordinated proteins

Dynamic noncovalent interactions are pivotal to the structure and function of biological proteins and have been used in bioinspired materials for similar roles. Metal-coordination bonds, in particular, are especially tunable and enable control over static and dynamic properties when incorporated into synthetic materials. Despite growing efforts to engineer metal-coordination bonds to produce strong, tough, and self-healing materials, the systematic characterization of the exact contribution of these bonds towards mechanical strength and the effect of geometric arrangements is missing, limiting the full design potential of these bonds. In this work, we engineer the cooperative rupture of metal-coordination bonds to increase the rupture strength of metal-coordinated peptide dimers. Utilizing all-atom steered molecular dynamics simulations on idealized bidentate histidine-Ni²⁺ coordinated peptides, we show that histidine-Ni²⁺ bonds can rupture cooperatively in groups of two to three bonds. We find that there is a strength limit, where adding additional coordination bonds does not contribute to the additional increase in the protein rupture strength, likely due to the highly heterogeneous rupture behavior exhibited by the coordination bonds. Further, we show that this coordination bond limit is also found natural metal-coordinated biological proteins. Using these insights, we quantitatively suggest how other proteins can be rationally designed with dynamic noncovalent interactions to exhibit cooperative bond breaking behavior. Altogether, this work provides a quantitative analysis of the cooperativity and intrinsic strength limit for metal-coordination bonds with the aim of advancing clear guiding molecular principles for the mechanical design of metal-coordinated materials.

Immunostimulatory Polymers as Adjuvants, Immunotherapies, and Delivery Systems

Activating innate immunity in a controlled manner is necessary for the development of next-generation therapeutics. Adjuvants, or molecules that modulate the immune response, are critical components of vaccines and immunotherapies. While small molecules and biologics dominate the adjuvant market, emerging evidence supports the use of immunostimulatory polymers in therapeutics. Such polymers can stabilize and deliver cargo while stimulating the immune system by functioning as pattern recognition receptor (PRR) agonists. At the same time, in designing polymers that engage the immune system, it is important to consider any unintended initiation of an immune response that results in adverse immune-related events. Here, we highlight biologically derived and synthetic polymer scaffolds, as well as polymer–adjuvant systems and stimuli-responsive polymers loaded with adjuvants, that can invoke an immune response. We present synthetic considerations for the design of such immunostimulatory polymers, outline methods to target their delivery, and discuss their application in therapeutics. Finally, we conclude with our opinions on the design of next-generation immunostimulatory polymers, new applications of immunostimulatory polymers, and the development of improved preclinical immunocompatibility tests for new polymers.

Designing Enhanced Entropy Binding in Single-Chain Nanoparticles

Single-chain nanoparticles (SCNPs) are a new class of bio- and soft-matter polymeric objects in which a fraction of the monomers are able to form equivalently intra- or interpolymer bonds. Here we numerically show that a fully entropic gas-liquid phase separation can take place in SCNP systems. Control over the discontinuous (first-order) change-from a phase of independent diluted (fully-bonded) polymers to a phase in which polymers entropically bind to each other to form a (fully-bonded) polymer network-can be achieved by a judicious design of the patterns of reactive monomers along the polymer chain. Such a sensitivity arises from a delicate balance between the distinct entropic contributions controlling the binding.

Molecular communications in complex systems of dynamic supramolecular polymers

Supramolecular polymers are composed of monomers that self-assemble non-covalently, generating distributions of monodimensional fibres in continuous communication with each other and with the surrounding solution. Fibres, exchanging molecular species, and external environment constitute a sole complex system, which intrinsic dynamics is hard to elucidate. Here we report coarse-grained molecular simulations that allow studying supramolecular polymers at the thermodynamic equilibrium, explicitly showing the complex nature of these systems, which are composed of exquisitely dynamic molecular entities. Detailed studies of molecular exchange provide insights into key factors controlling how assemblies communicate with each other, defining the equilibrium dynamics of the system. Using minimalistic and finer chemically relevant molecular models, we observe that a rich concerted complexity is intrinsic in such self-assembling systems. This offers a new dynamic and probabilistic (rather than structural) picture of supramolecular polymer systems, where the travelling molecular species continuously shape the assemblies that statistically emerge at the equilibrium.

The dynamic structure of supramolecular polymers is challenging to determine both in experiments and in simulations. Here the authors use coarse-grained molecular models to provide a comprehensive analysis of the molecular communication in these complex molecular systems.

Phage Display-Derived Peptide for the Specific Binding of SARS-CoV-2

Beginning from the end of 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic swept all over the world and is still afflicting the whole global population. Given that the vaccine-manufacturing ability is limited and the virus can evolve quickly, vaccination alone may not be able to end the pandemic, thus developing fast and accurate diagnoses and effective therapeutics will always be unmet needs. Phage display peptide library has been used in screening antigen-specific peptides for the invention of novel mimic receptors/ligands. Here, we report that a 12-mer phage display peptide library has been screened against the SARS-CoV-2 receptor-binding domain (RBD), and five of the screened peptides show binding ability with the RBD protein by the enzyme-linked immune sorbent assay. The surface plasmon resonance assay further demonstrates that peptide no. 1 can specifically bind to SARS-CoV-2 RBD with a binding affinity constant (K d) of 5.8 μM. Transmission electron microscopy coupled with a magnetic bead assay further confirms that the screened peptide can specifically bind the inactivated SARS-CoV-2 virus. This SARS-CoV-2-specific peptide holds great promise as a new bioreceptor/ligand for the rapid and accurate detection of SARS-CoV-2.

Multivalent polymers can control phase boundary, dynamics, and organization of liquid-liquid phase separation

Multivalent polymers are a key structural component of many biocondensates. When interacting with their cognate binding proteins, multivalent polymers such as RNA and modular proteins have been shown to influence the liquid-liquid phase separation (LLPS) boundary to both control condensate formation and to influence condensate dynamics after phase separation. Much is still unknown about the function and formation of these condensed droplets, but changes in their dynamics or phase separation are associated with neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Alzheimer's Disease. Therefore, investigation into how the structure of multivalent polymers relates to changes in biocondensate formation and maturation is essential to understanding and treating these diseases. Here, we use a coarse-grain, Brownian Dynamics simulation with reactive binding that mimics specific interactions in order to investigate the difference between non-specific and specific multivalent binding polymers. We show that non-specific binding interactions can lead to much larger changes in droplet formation at lower protein-polymer interaction energies than their specific, valence-limited counterparts. We also demonstrate the effects of solvent conditions and polymer length on phase separation, and we present how modulating binding energy to the polymer can change the organization of a droplet in a three component system of polymer, binding protein, and solvent. Finally, we compare the effects of surface tension and polymer binding on the condensed phase dynamics, and show that both lower protein solubilities and higher attraction/affinity of the protein to the polymer result in slower droplet dynamics. This research will help to better understand experimental systems and provides additional insight into how multivalent polymers can control LLPS.

Effect of sticker clustering on the dynamics of associative networks

Recent experimental and theoretical work has shown that sticker clustering can be used to enhance properties such as toughness and creep resistance of polymer networks. While it is clear that the changes in properties are related to a change in network topology, the mechanistic relationship is still not well understood. In this work, the effect of sticker clustering was investigated by comparing the dynamics of random copolymers with those where the stickers are clustered at the ends of the chain in the unentangled regime using both linear mechanics and diffusion measurements. Copolymers of N,N-dimethyl acrylamide (DMA) and pendant histidine groups were synthesized using reversible addition-fragmentation chain transfer (RAFT) polymerization. The clustered polymers were synthesized using a bifunctional RAFT agent, such that the midblock consisted of PDMA and the two end blocks were random copolymers of DMA and the histidine-functionalized monomer. Upon addition of Ni ions, transient metal-coordinate crosslinks are formed as histidine-Ni complexes. Combined studies of rheology, neutron scattering and self-diffusion measurements using forced Rayleigh scattering revealed changes to the network topology and stress relaxation modes. The network topology is proposed to consist of aggregates of the histidine-Ni complexes bridged by the non-associative midblock. Therefore, stress relaxation requires the cooperative dissociation of multiple bonds, resulting in increased relaxation times. The increased relaxation times, however, were accompanied by faster diffusion. This is attributed to the presence of defects such as elastically inactive chain loops. This study demonstrates that the effects of cooperative sticker dissociation can be observed even in the presence of a significant fraction of loop defects which are known to alter the nonlinear properties of conventional telechelic polymers.

Physical modeling of multivalent interactions in the nuclear pore complex

In the nuclear pore complex, intrinsically disordered proteins (FG Nups), along with their interactions with more globular proteins called nuclear transport receptors (NTRs), are vital to the selectivity of transport into and out of the cell nucleus. Although such interactions can be modeled at different levels of coarse graining, in vitro experimental data have been quantitatively described by minimal models that describe FG Nups as cohesive homogeneous polymers and NTRs as uniformly cohesive spheres, in which the heterogeneous effects have been smeared out. By definition, these minimal models do not account for the explicit heterogeneities in FG Nup sequences, essentially a string of cohesive and noncohesive polymer units, and at the NTR surface. Here, we develop computational and analytical models that do take into account such heterogeneity in a minimal fashion and compare them with experimental data on single-molecule interactions between FG Nups and NTRs. Overall, we find that the heterogeneous nature of FG Nups and NTRs does play a role in determining equilibrium binding properties but is of much greater significance when it comes to unbinding and binding kinetics. Using our models, we predict how binding equilibria and kinetics depend on the distribution of cohesive blocks in the FG Nup sequences and of the binding pockets at the NTR surface, with multivalency playing a key role. Finally, we observe that single-molecule binding kinetics has a rather minor influence on the diffusion of NTRs in polymer melts consisting of FG-Nup-like sequences.

Polymer Stiffness Regulates Multivalent Binding and Liquid-Liquid Phase Separation

Multivalent binding is essential to many biological processes because it builds high-affinity bonds by using several weak binding interactions simultaneously. Multivalent polymers have shown promise as inhibitors of toxins and other pathogens, and they are important components in the formation of biocondensates. Explaining how structural features of these polymers change their binding and subsequent control of phase separation is critical to designing better pathogen inhibitors and also to understanding diseases associated with membraneless organelles. In this work, we will examine the binding of a multivalent polymer to a small target. This scenario could represent a polymeric inhibitor binding to a toxic protein or RNA binding to an RNA-binding protein in the case of liquid-liquid phase separation. We use simulation and theory to show that flexible random-coil polymers bind more strongly than stiff rod-like polymers and that flexible polymers nucleate condensed phases at lower binding energies than their rigid analogs. We hope these results will provide insight into the rational design of polymeric inhibitors and improve our understanding of phase separation in cells and membraneless organelles.

Bayesian Data Integration Questions Classic Study on Protease Self-Digest Kinetics

We combine Bayesian data integration with kinetic modeling to rigorously identify reaction mechanisms. This approach forces models to be consistent not only with kinetic measurements but with all available information. We revisit a classic study on trypsin self-digest acceleration by colloidal silica. Bayesian data integration reveals that the mechanism suggested in that study is inconsistent with its presented data. We propose an improved hypothesis. However, the detailed mechanism of the surface reaction cannot be inferred from the available data.

Influence of Binding Site Affinity Patterns on Binding of Multivalent Polymers

Using inspiration from biology, we can leverage multivalent binding interactions to enhance weak, monovalent binding between molecules. While most previous studies have focused on multivalent binders with uniform binding sites, new synthetic polymers might find it desirable to have multiple binding moieties along the chain. Here, we probe how patterning of heterogeneous binding sites along a polymer chain controls the binding affinity of a polymer using a reactive Brownian dynamics scheme. Unlike monovalent binders that are pattern-agnostic, we find that divalent binding is dependent on both the polymer pattern and binding target concentration. For dilute targets, blocky polymers provide high local concentrations of high-affinity sites, but at high target concentrations, competition for binding sites makes alternating polymers the strongest binders. Subsequently, we show that random copolymers are robust to target concentration fluctuations. These results will assist in the rational design of multivalent polymer therapeutics and materials.