Research Highlights

2023

Coarse-Graining with Equivariant Neural Networks: A Path Towards Accurate and Data-Efficient Structural Models

Machine learning has recently entered into the mainstream of coarse-grained (CG) molecular modeling and simulation. While a variety of methods for incorporating deep learning into these models exist, many of them involve training neural networks to act directly as the CG force field. This has several benefits of which the most significant is accuracy. Neural networks can inherently incorporate multibody effects during the calculation of CG forces, and a well-trained neural network force field outperforms pairwise basis sets generated from essentially any methodology. However, this comes at a significant cost. First, these models are typically slower than pairwise force fields, even when accounting for specialized hardware, which accelerates the training and integration of such networks. The second and the focus of this paper is the need for a considerable amount of data to train such force fields. It is common to use 10s of microseconds of molecular dynamics data to train a single CG model, which approaches the point of eliminating the CG model’s usefulness in the first place. As we investigate in this work, this “data-hunger” trap from neural networks for predicting molecular energies and forces can be remediated in part by incorporating equivariant convolutional operations. We demonstrate that, for CG water, networks that incorporate equivariant convolutional operations can produce functional models using data sets as small as a single frame of reference data, while networks without these operations cannot.

K-Means Clustering Coarse-graining (KMC-CG): A Next Generation Methodology for Determining Optimal Coarse-grained Mappings of Large Biomolecules

Coarse-grained (CG) molecular dynamics (MD) has become a method of choice for simulating various large scale biomolecular processes; therefore, the systematic definition of the CG mappings for biomolecules remains an important topic. Appropriate CG mappings can significantly enhance the representability of a CG model and improve its ability to capture critical features of large biomolecules. In this work, we present a systematic and more generalized method called K-means clustering coarse-graining (KMC-CG), which builds on the earlier approach of essential dynamics coarse-graining (ED-CG). KMC-CG removes the sequence-dependent constraints of ED-CG, allowing it to explore a more extensive space and thus enabling the discovery of more physically optimal CG mappings. Furthermore, the implementation of the K-means clustering algorithm can variationally optimize the CG mapping with efficiency and stability. This new method is tested in three cases: ATP-bound G-actin, the HIV-1 CA pentamer, and the Arp2/3 complex. In these examples, the CG models generated by KMC-CG are seen to better capture the structural, dynamic, and functional domains. KMC-CG therefore provides a robust and consistent approach to generating CG models of large biomolecules that can then be more accurately parametrized by either bottom-up or top-down CG force fields..

Can a Coarse-grained Water Model Capture the Key Physical Features of the Hydrophobic Effect?

Coarse-grained (CG) molecular dynamics can be a powerful method for probing complex processes. However, most CG force fields use pairwise nonbonded interaction potentials sets, which can limit their ability to capture complex multi-body phenomena such as the hydrophobic effect. As the hydrophobic effect primarily manifests itself due to the nonpolar solute affecting the nearby hydrogen bonding network in water, capturing such effects using a simple one CG site or “bead” water model is a challenge. In this work, we systematically test the ability of CG one site water models for capturing critical features of the solvent environment around a hydrophobe as well as the potential of mean force (PMF) of neopentane association. We study two bottom-up models: a simple pairwise (SP) force-matched water model constructed using the multiscale coarse-graining method and the Bottom-Up Many-Body Projected Water (BUMPer) model, which has implicit three-body correlations. We also test the top-down monatomic (mW) and the Machine Learned mW (ML-mW) water models. The mW models perform well in capturing structural correlations but not the energetics of the PMF. BUMPer outperforms SP in capturing structural correlations and also gives an accurate PMF in contrast to the two mW models. Our study highlights the importance of including three-body interactions in CG water models, either explicitly or implicitly, while in general highlighting the applicability of bottom-up CG water models for studying hydrophobic effects in a quantitative fashion. This assertion comes with a caveat, however, regarding the accuracy of the enthalpy–entropy decomposition of the PMF of hydrophobe association.

Gaussian Representation of Coarse-Grained Interactions of Liquids: Theory, Parametrization, and Transferability

Coarse-grained (CG) interactions determined via bottom-up methodologies can faithfully reproduce the structural correlations observed in fine-grained (atomistic resolution) systems, yet they can suffer from limited extensibility due to complex many-body correlations. As part of an ongoing effort to understand and improve the applicability of bottom-up CG models, we propose an alternative approach to address both accuracy and transferability. Our main idea draws from classical perturbation theory to partition the hard sphere repulsive term from effective CG interactions. We then introduce Gaussian basis functions corresponding to the system’s characteristic length by linking these Gaussian sub-interactions to the local particle densities at each coordination shell. The remaining perturbative long-range interaction can be treated as a collective solvation interaction, which we show exhibits a Gaussian form derived from integral equation theories. By applying this numerical parametrization protocol to CG liquid systems, our microscopic theory elucidates the emergence of Gaussian interactions in common phenomenological CG models. To facilitate transferability for these reduced descriptions, we further infer equations of state to determine the sub-interaction parameter as a function of the system variables. The reduced models exhibit excellent transferability across the thermodynamic state points. Furthermore, we propose a new strategy to design the cross-interactions between distinct CG sites in liquid mixtures. This involves combining each Gaussian in the proper radial domain, yielding accurate CG potentials of mean force and structural correlations for multi-component systems. Overall, our findings establish a solid foundation for constructing transferable bottom-up CG models of liquids with enhanced extensibility.

Understanding Dynamics in Coarse-Grained Models: III. Roles of Rotational Motion and Translation-Rotation Coupling in Coarse-Grained Dynamics

This paper series aims to establish a complete correspondence between fine-grained (FG) and coarse-grained (CG) dynamics by way of excess entropy scaling (introduced in Paper I). While Paper II successfully captured translational motions in CG systems using a hard sphere mapping, the absence of rotational motions in single-site CG models introduces differences between FG and CG dynamics. In this third paper, our objective is to faithfully recover atomistic diffusion coefficients from CG dynamics by incorporating rotational dynamics. By extracting FG rotational diffusion, we unravel, for the first time reported to our knowledge, a universality in excess entropy scaling between the rotational and translational diffusion. Once the missing rotational dynamics are integrated into the CG translational dynamics, an effective translation-rotation coupling becomes essential. We propose two different approaches for estimating this coupling parameter: the rough hard sphere theory with acentric factor (temperature-independent) or the rough Lennard-Jones model with CG attractions (temperature-dependent). Altogether, we demonstrate that FG diffusion coefficients can be recovered from CG diffusion coefficients by (1) incorporating “entropy-free” rotational diffusion with translation-rotation coupling and (2) recapturing the missing entropy. Our findings shed light on the fundamental relationship between FG and CG dynamics in molecular fluids.

OpenMSCG: A Software Tool for Bottom-up Coarse-graining

We have recently released OpenMSCG, a software package which incorporates various state-of-the-art methods in the field of bottom-up coarse-graining. These methods include the Multiscale Coarse-Graining (MS-CG) method, Ultra Coarse-Graining (UCG), Relative Entropy Minimization (REM), Boltzmann Inversion (BI), Essential Dynamics Coarse-Graining (ED-CG), and Heterogenous Elastic Network Modeling (hENM). Our software package includes tutorials for each of these methods as well as extensive documentation to enable usability. OpenMSCG can read various file formats used in popular MD simulation packages including GROMACS, LAMMPS, and NAMD. The OpenMSCG software package can be readily applied throughout the CG model development workflow from defining the coarse-grained mapping to force-field optimization.

Proton Dissociation and Delocalization Under Stepwise Hydration of Zeolite HZSM-5

The protonation behavior of zeolite Brønsted acid sites (BAS) in the presence of water is important for the performance of these widely used catalysts. Despite extensive study, the number of water molecules necessary for deprotonation is not well understood, in large part because experiments have been unable to access this information. In this work, we report experimental evidence for full deprotonation of the BAS in the presence of two or more water molecules, with a deprotonation energy of 1.6 kcal/mol. Linear IR absorption and 2D IR spectra were measured over a wide range of controlled hydration levels from 0.5 to 8.0 equivalents of H2O/Al at a constant temperature. Distinct spectral signatures of the protonated BAS and excess proton are identified, and their hydration dependence is analyzed quantitatively. Using the experiment as a benchmark, ab initio molecular dynamics simulations are reported that reproduce the experimental trends in the protonation state and IR spectra. The proton charge position and delocalization are quantified in clusters of 1–8 H2O molecules using the recently developed rCEC method. This analysis provides insight into the proton structure in confined water clusters, showing that the excess charge remains relatively localized between two oxygen atoms across the hydration range.

Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models Through Virtual Particles

One of the primary challenges of coarse-grained modeling is developing a CG model which is sufficiently accurate while retaining a significant speedup in simulation time. To help resolve this issue, we have developed a new coarse-graining methodology to incorporate “virtual” particles, i.e., CG sites with no correspondence in the atomistic representation, into CG models. Optimization of the virtual particles proceeds via a relative entropy principle in which machine-learning models are used to approximate the relative entropy gradient. Models which include virtual particles remain fast to simulate since all interactions are pairwise, however optimizing virtual particle interactions matches higher-order correlations of the “real” CG sites in the model. We have demonstrated the utility of virtual particles through development of a “VCG” model of a DOPC bilayer, in which virtual particles aid in recapitulating self-assembly and membrane flexibility.

Elucidating the Molecular Mechanism of CO2 Capture by Amino Acid Ionic Liquids

Amino acid ionic liquids show promise for the CO2 chemisorption process, despite that their precise molecular mechanisms, particularly proton transfer, are not well-understood. In our study, we explore the atomistic-level reaction mechanisms leading to carbamate formation for CO2 capture by amino acid ionic liquids, based on ab initio molecular dynamics augmented by well-tempered metadynamics. Our ab initio free-energy sampling examines a two-step reaction pathway: the serine anion reacts with CO2 to form a zwitterion, which then undergoes a kinetically facile intermolecular proton transfer to the O atom of the COO- group of a neighboring serine. The reduced free-energy barriers are due to strengthened interactions between the zwitterion and serine, enhancing the kinetic favorability of proton transfer, central to the CO2 capture mechanism. This research sheds light on the critical mechanistic and kinetic aspects of these reactions from explicit condensed phase ab initio MD free-energy sampling of the CO2 capture process.

Organization of Upstream ESCRT Machinery at the HIV-1 Budding Site

In the late stages of the HIV-1 life cycle, membrane localization and self-assembly of Gag polyproteins induce membrane deformation and budding. Release of the virion requires direct interaction between immature Gag lattice and upstream ESCRT machinery at the viral budding site, followed by assembly of downstream ESCRT-III factors, culminating in membrane scission. However, molecular details of upstream ESCRT assembly dynamics at the viral budding site remain unclear. In this work, using coarse-grained (CG) molecular dynamics (MD) simulations, we investigated the interactions between Gag, ESCRT-I, ESCRT-II, and membrane to delineate the dynamical mechanisms by which upstream ESCRTs assemble templated by late-stage immature Gag lattice. We first systematically derived “bottom-up” CG molecular models and interactions of upstream ESCRT proteins from experimental structural data and extensive all-atom MD simulations. Using these molecular models, we performed CG MD simulations of ESCRT-I oligomerization and ESCRT-I/II supercomplex formation at the neck of the budding virion. Our simulations demonstrate that ESCRT-I can effectively oligomerize to higher-order complexes templated by the immature Gag lattice both in the absence of ESCRT-II and when multiple copies of ESCRT-II are localized at the bud neck. The ESCRT-I/II supercomplexes formed in our simulations exhibit predominantly columnar structures, which has important implications for the nucleation pathway of downstream ESCRT-III polymers. Importantly, ESCRT-I/II supercomplexes bound to Gag initiate membrane neck constriction by pulling the inner edge of the bud neck closer to the ESCRT-I headpiece ring. Our findings serve to elucidate a network of interactions between upstream ESCRT machinery, immature Gag lattice, and membrane neck that regulate protein assembly dynamics at the HIV-1 budding site.

Deciphering the Dynamic Codes: Advances in Biomolecular Modeling and Simulation

This collection for the “theory and simulation/computational methods” section presents a selection of articles describing current advances in biomolecular modeling, molecular simulations and theories, and integration of experimental data in the determination of structure, dynamics, and function. From single units to multi-structural complexes (proteins, membranes, RNA/DNA, and nucleosome/chromatin), the inherent underlying dynamics bridge structure to function. Assembling into essential forms, biological macromolecules fluctuate on many different time scales to interact and communicate (via allostery) with others in their functional activity.

Acidic Conditions Impact Hydrophobe Transfer Across the Oil-Water Interface in Unusual Ways

The solvation of hydrophobic species in the aqueous solution and its transfer between the hydrophilic-hydrophobic interfaces play a crucial role in diverse disciplines. The Hofmeister series qualitatively arranges the ions by their ability to “salting-out” proteins. Although a hydrated proton shares a similar size with the salting-out cation K+, the salting-out effect of hydrocarbons in HCl solutions is much weaker than that in salt solutions. To understand the mechanism behind, molecular dynamics simulation and umbrella sampling are used to study hydrophobic solute transfer across the water-oil interface with different electrolytes (HCl and NaCl). With the Multistate Empirical Valence Bond (MS-EVB) methodology and the analysis of solvation structure of neopentane, we find that hydronium can to a certain degree stabilize the hydrophobic solute in the aqueous phase and including at the oil-water interface. At the same time, sodium cation tends to “salt out” the hydrophobic solute in the expected fashion.

The Structure of Phosphatidylinositol Remodeling MBOAT7 Reveals Its Catalytic Mechanism and Enables Inhibitor Identification

Cells remodel glycerophospholipid acyl chains via the Lands cycle to adjust membrane properties. Membrane-bound O-acyltransferase (MBOAT) 7 acylates lyso-phosphatidylinositol (lyso-PI) with arachidonyl-CoA. MBOAT7 mutations cause brain developmental disorders, and reduced expression is linked to fatty liver disease. In contrast, increased MBOAT7 expression is linked to hepatocellular and renal cancers. The mechanistic basis of MBOAT7 catalysis and substrate selectivity are unknown. Here, we report the structure and a model for the catalytic mechanism of human MBOAT7. Arachidonyl-CoA and lyso-PI access the catalytic center through a twisted tunnel from the cytosol and lumenal sides, respectively. N-terminal residues on the ER lumenal side determine phospholipid headgroup selectivity: swapping them between MBOATs 1, 5, and 7 converts enzyme specificity for different lyso-phospholipids. Finally, the MBOAT7 structure and virtual screening enabled identification of small-molecule inhibitors that may serve as lead compounds for pharmacologic development.

Structure and Function of Lipid Droplet Assembly Complexes

Cells store lipids as a reservoir of metabolic energy and membrane component precursors in organelles called lipid droplets (LDs). LD formation occurs in the endoplasmic reticulum (ER) at LD assembly complexes (LDAC), consisting of an oligomeric core of seipin and accessory proteins. LDACs determine the sites of LD formation and are required for this process to occur normally. Seipin oligomers form a cage-like structure in the membrane that may serve to facilitate the phase transition of neutral lipids in the membrane to form an oil droplet within the LDAC. Modeling suggests that, as the LD grows, seipin anchors it to the ER bilayer and conformational shifts of seipin transmembrane segments open the LDAC dome toward the cytoplasm, enabling the emerging LD to egress from the ER.

Statistical Mechanical Design Principles for Coarse-grained Interactions Across Different Conformational Free Energy Surfaces

Systematic bottom-up coarse-graining (CG) of molecular systems provides a means to explore different coupled length and time scales while treating the molecular-scale physics at a reduced level. However, the configuration dependence of CG interactions often results in CG models with limited applicability for exploring the parametrized configurations. We propose a statistical mechanical theory to design CG interactions across different configurations and conditions. In order to span wide ranges of conformational space, distinct classical CG free energy surfaces for characteristic configurations are identified using molecular collective variables. The coupling interaction between different CG free energy surfaces can then be systematically determined by analogy to quantum mechanical approaches describing coupled states. The present theory can accurately capture the underlying many-body potentials of mean force in the CG variables for various order parameters applied to liquids, interfaces, and in principle proteins, uncovering the complex nature underlying the coupling interaction and imparting a new protocol for the design of predictive multiscale models.

The Role of Conformational Change and Key Glutamic Acid Residues in the ClC-ec1 Antiporter

The triple glutamine (Q) mutant (QQQ) structure of a Cl−/H+ antiporter from Escherichia coli (ClC-ec1) displaying a novel backbone arrangement has been used to challenge the long-held notion that Cl−/H+ antiporters do not operate through large conformational motions. The QQQ mutant substitutes the glutamine residue for an external glutamate E148, an internal glutamate E203, and a third glutamate E113 that hydrogen-bonds with E203. However, it is unknown if QQQ represents a physiologically relevant state, as well as how the protonation of the wild-type glutamates relates to the global dynamics. We herein apply continuous constant-pH molecular dynamics to investigate the H+-coupled dynamics of ClC-ec1. Although any large-scale conformational rearrangement upon acidification would be due to the accumulation of excess charge within the protein, protonation of the glutamates significantly impacts mainly the local structure and dynamics. Despite the fact that the extracellular pore enlarges at acidic pHs, an occluded ClC-ec1 within the active pH range of 3.5–7.5 requires a protonated E148 to facilitate extracellular Cl− release. E203 is also involved in the intracellular H+ transfer as an H+ acceptor. The water wire connection of E148 with the intracellular solution is regulated by the charge states of the E113/E203 dyad with coupled proton titration. However, the dynamics extracted from our simulations are not QQQ-like, indicating that the QQQ mutant does not represent the behavior of the wild-type ClC-ec1. These findings reinforce the necessity of having a protonatable residue at the E203 position in ClC-ec1 and suggest that a higher level of complexity exists for the intracellular H+ transfer in Cl−/H+ antiporters.

How Does Electronic Polarizability or Scaled-Charge Affect the Interfacial Properties of Room Temperature Ionic Liquids?

The air-room temperature ionic liquid (RTIL) interface plays an important role in many applications. We present molecular dynamics simulation results for the air-liquid interface of a common RTIL, [C4mim][NTf2]. To elucidate the effect of electronic polarizability and scaled-charge ions on the properties of the RTIL air-liquid interface, we employ three different kinds of force fields: a nonpolarizable force field (FF) with united ion charges (FixQ), a nonpolarizable FF with scaled-charge by 0.8 (ScaleQ), and a polarizable FF (Drude). We evaluated the structural and dynamical properties in the interfacial, sub-interfacial, and central layers. While the FixQ model largely overestimates the Columbic interaction compared to the Drude model, the ScaleQ model cannot reproduce the results of the Drude model either, due to an inappropriate scaled-down charged near the interface. It is therefore necessary to utilize a polarizable force field to accurately predict the interfacial properties by explicitly considering the polarization effect.

Critical Mechanistic Features of HIV-1 Viral Capsid Assembly

The maturation of HIV-1 capsid protein (CA) into a cone-shaped lattice capsid is critical for viral infectivity. CA can self-assemble into a range of capsid morphologies made of ~175 to 250 hexamers and 12 pentamers. The cellular polyanion inositol hexakisphosphate (IP6) has recently been demonstrated to facilitate conical capsid formation by coordinating a ring of arginine residues within the central cavity of capsid hexamers and pentamers. However, the kinetic interplay of events during IP6 and CA co-assembly remains unclear. In this work, we use coarse-grained molecular dynamics simulations to elucidate the molecular mechanism of capsid formation, including the role played by IP6. We show that IP6, in small quantities at first, promotes curvature generation by trapping pentameric defects in the growing lattice and shifts assembly behavior toward kinetically favored outcomes. Our analysis also suggests that IP6 can stabilize metastable capsid intermediates and can induce structural pleomorphism in mature capsids.

Transient Water Wires Mediate Selective Proton Conduction in Designed Channel Proteins

Selective proton transport through proteins is essential for forming and using proton gradients in cells. Protons are conducted along hydrogen-bonded ‘wires’ of water molecules and polar side chains, which, somewhat surprisingly, are often interrupted by dry apolar stretches in the conduction pathways, inferred from static protein structures. Here we hypothesize that protons are conducted through such dry spots by forming transient water wires, often highly correlated with the presence of the excess protons in the water wire. To test this hypothesis, we performed molecular dynamics simulations to design transmembrane channels with stable water pockets interspersed by apolar segments capable of forming flickering water wires. The minimalist designed channels conduct protons at rates similar to viral proton channels, and they are at least 106-fold more selective for H+ over Na+. These studies inform the mechanisms of biological proton conduction and the principles for engineering proton-conductive materials.

Using Classifiers to Understand Coarse-grained Models and Their Fidelity With the Underlying All-Atom Systems

Bottom-up coarse-grained (CG) molecular dynamics models are parameterized using complex effective Hamiltonians. These models are typically optimized to approximate high dimensional data from atomistic simulations. However, human validation of these models is often limited to low dimensional statistics that do not necessarily differentiate between the CG model and said atomistic simulations. We propose that classification can be used to variationally estimate high dimensional error and that explainable machine learning can help convey this information to scientists. This approach is demonstrated using Shapley additive explanations and two CG protein models. This framework may also be valuable for ascertaining whether allosteric effects at the atomistic level are accurately propagated to a CG model.

Unveiling the Catalytic Mechanism of GTP Hydrolysis in Microtubules

Microtubules (MTs) are large cytoskeletal polymers, composed of αβ-tubulin heterodimers, capable of stochastically converting from polymerizing to depolymerizing states and vice versa. Depolymerization is coupled with hydrolysis of guanosine triphosphate (GTP) within β-tubulin. Hydrolysis is favored in the MT lattice compared to a free heterodimer with an experimentally observed rate increase of 500- to 700-fold, corresponding to an energetic barrier lowering of 3.8 to 4.0 kcal/mol. Mutagenesis studies have implicated α-tubulin residues, α:E254 and α:D251, as catalytic residues completing the β-tubulin active site of the lower heterodimer in the MT lattice. The mechanism for GTP hydrolysis in the free heterodimer, however, is not understood. Additionally, there has been debate concerning whether the GTP-state lattice is expanded or compacted relative to the GDP state and whether a “compacted” GDP-state lattice is required for hydrolysis. In this work, extensive quantum mechanics/molecular mechanics simulations with transition-tempered metadynamics free-energy sampling of compacted and expanded interdimer complexes, as well as a free heterodimer, have been carried out to provide clear insight into the GTP hydrolysis mechanism. α:E254 was found to be the catalytic residue in a compacted lattice, while in the expanded lattice, disruption of a key salt bridge interaction renders α:E254 less effective. The simulations reveal a barrier decrease of 3.8 ± 0.5 kcal/mol for the compacted lattice compared to a free heterodimer, in good agreement with experimental kinetic measurements. Additionally, the expanded lattice barrier was found to be 6.3 ± 0.5 kcal/mol higher than compacted, demonstrating that GTP hydrolysis is variable with lattice state and slower at the MT tip.

Understanding Dynamics in Coarse-Grained Models: I. Universal Excess Entropy Scaling Relationship

Coarse-grained (CG) models facilitate an efficient exploration of complex systems by reducing the unnecessary degrees of freedom of the fine-grained (FG) system while recapitulating major structural correlations. Unlike structural properties, assessing dynamic properties in CG modeling is often unfeasible due to the accelerated dynamics of the CG models, which allows for more efficient structural sampling. Therefore, the ultimate goal of the present series of articles is to establish a better correspondence between the FG and CG dynamics. To assess and compare dynamical properties in the FG and the corresponding CG models, we utilize the excess entropy scaling relationship. For Paper I of this series, we provide evidence that the FG and the corresponding CG counterpart follow the same universal scaling relationship. By carefully reviewing and examining the literature, we develop a new theory to calculate excess entropies for the FG and CG systems while accounting for entropy representability. We demonstrate that the excess entropy scaling idea can be readily applied to liquid water and methanol systems at both the FG and CG resolutions. For both liquids, we reveal that the scaling exponents remain unchanged from the coarse-graining process, indicating that the scaling behavior is universal for the same underlying molecular systems. Combining this finding with the concept of mapping entropy in CG models, we show that the missing entropy plays an important role in accelerating the CG dynamics.

Understanding Dynamics in Coarse-Grained Models: II. Coarse-Grained Diffusion Modeled Using Hard Sphere Theory

The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) systems. Despite its universality, a more exact determination of the scaling relationship was not possible due to the semi-empirical nature. In this second paper, an analytical excess entropy scaling relation is derived for bottom-up CG systems. At the single-site CG resolution, effective hard sphere systems are constructed that yield near-identical dynamical properties as the target CG systems by taking advantage of how hard sphere dynamics and excess entropy can be analytically expressed in terms of the liquid packing fraction. Inspired by classical equilibrium perturbation theories and recent advances in constructing hard sphere models for predicting activated dynamics of supercooled liquids, we propose a new approach for understanding the diffusion of molecular liquids in the normal regime using hard sphere reference fluids. The proposed “fluctuation matching” is designed to have the same amplitude of long wavelength density fluctuations (dimensionless compressibility) as the CG system. Utilizing the Enskog theory to derive an expression for hard sphere diffusion coefficients, a bridge between the CG dynamics and excess entropy is then established. The CG diffusion coefficient can be roughly estimated using various equations of the state, and an accurate prediction of accelerated CG dynamics at different temperatures is also possible in advance of running any CG simulation. By introducing another layer of coarsening, these findings provide a more rigorous method to assess excess entropy scaling and understand the accelerated CG dynamics of molecular fluids.

2022

A Generalized Transition State Theory Treatment of Water-Assisted Proton Transport Processes in Proteins

Transition state theory (TST) is widely employed for estimating the transition rate of a reaction when combined with free energy sampling techniques. A derivation of the transition theory rate expression for a general n-dimensional case is presented in this work which specifically focuses on water-assisted proton transfer/transport reactions, especially for protein systems. Our work evaluates the TST prefactor calculated at the transition state dividing surface compared to one sampled, as an approximation, in the reactant state in four case studies of water-assisted proton transport inside membrane proteins and highlights the significant impact of the prefactor position dependence in proton transport processes.

Prion-Like Low Complexity Regions Enable Avid Virus-Host Interactions During HIV-1 Infection

Cellular proteins CPSF6, NUP153 and SEC24C play crucial roles in HIV-1 infection. While weak interactions of short phenylalanine-glycine (FG) containing peptides with isolated capsid hexamers have been characterized, how these cellular factors functionally engage with biologically relevant mature HIV-1 capsid lattices is unknown. Here we show that prion-like low complexity regions (LCRs) enable avid CPSF6, NUP153 and SEC24C binding to capsid lattices. Structural studies revealed that multivalent CPSF6 assembly is mediated by LCR-LCR interactions, which are templated by binding of CPSF6 FG peptides to a subset of hydrophobic capsid pockets positioned along adjoining hexamers. In infected cells, avid CPSF6 LCR-mediated binding to HIV-1 cores is essential for functional virus-host interactions. The investigational drug lenacapavir accesses unoccupied hydrophobic pockets in the complex to potently impair HIV-1 inside the nucleus without displacing the tightly bound cellular cofactor from virus cores. These results establish previously undescribed mechanisms of virus-host interactions and antiviral action.

Structure of SARS-CoV-2 M Protein in Lipid Nanodiscs

SARS-CoV-2 encodes four structural proteins incorporated into virions, spike (S), envelope (E), nucleocapsid (N), and membrane (M). M plays an essential role in viral assembly by organizing other structural proteins through physical interactions and directing them to sites of viral budding. As the most abundant protein in the viral envelope and a target of patient antibodies, M is a compelling target for vaccines and therapeutics. Still, the structure of M and molecular basis for its role in virion formation are unknown. Here, we present the cryo-EM structure of SARS-CoV-2 M in lipid nanodiscs to 3.5 Å resolution. M forms a 50 kDa homodimer that is structurally related to the SARS-CoV-2 ORF3a viroporin, suggesting a shared ancestral origin. Structural comparisons reveal how intersubunit gaps create a small, enclosed pocket in M and large open cavity in ORF3a, consistent with a structural role and ion channel activity, respectively. M displays a strikingly electropositive cytosolic surface that may be important for interactions with N, S, and viral RNA. Molecular dynamics simulations show a high degree of structural rigidity in a simple lipid bilayer and support a role for M homodimers in scaffolding viral assembly. Together, these results provide insight into roles for M in coronavirus assembly and structure.

Activated IRSp53 Clustering Controls the Formation of VASP-Actin-Based Membrane Protrusions

Filopodia are actin-rich membrane protrusions essential for cell morphogenesis, motility, and cancer invasion. How cells control filopodium initiation on the plasma membrane remains elusive. We performed experiments in cellulo, in vitro, and in silico to unravel the mechanism of filopodium initiation driven by the membrane curvature sensor IRSp53 (insulin receptor substrate protein of 53 kDa). We showed that full-length IRSp53 self-assembles into clusters on membranes depending on PIP2. Using well-controlled in vitro reconstitution systems, we demonstrated that IRSp53 clusters recruit the actin polymerase VASP (vasodilator-stimulated phosphoprotein) to assemble actin filaments locally on membranes, leading to the generation of actin-filled membrane protrusions reminiscent of filopodia. By pulling membrane nanotubes from live cells, we observed that IRSp53 can only be enriched and trigger actin assembly in nanotubes at highly dynamic membrane regions. Our work supports a regulation mechanism of IRSp53 in its attributes of curvature sensation and partner recruitment to ensure a precise spatial-temporal control of filopodium initiation.

Centroid Molecular Dynamics Can Be Greatly Accelerated Through Neural Network Learned Centroid Forces Derived from Path Integral Molecular Dynamics

For nearly the past 30 years, centroid molecular dynamics (CMD) has proven to be a viable classical-like phase space formulation for the calculation of quantum dynamical properties. However, calculation of the centroid effective force remains a significant computational cost and limits the ability of CMD to be an efficient approach to study condensed phase quantum dynamics. In this paper, we introduce a neural network-based methodology for first learning the centroid effective force from path integral molecular dynamics data, which is subsequently used as an effective force field to evolve the centroids directly with the CMD algorithm. This method, called machine-learned centroid molecular dynamics (ML-CMD), is faster and far less costly than both standard “on the fly” CMD and ring polymer molecular dynamics (RPMD). The training aspect of ML-CMD is also straightforwardly implemented utilizing the DeepMD software kit. ML-CMD is then applied to two model systems to illustrate the approach: liquid para-hydrogen and water. The results show comparable accuracy to both CMD and RPMD in the estimation of quantum dynamical properties, including the self-diffusion constant and velocity time correlation function, but with significantly reduced overall computational cost.

Bottom-Up Coarse-Graining: Principles and Perspectives

Large-scale computational molecular models provide scientists a means to investigate the effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship between variations on the molecular scale and macroscopic observable properties facilitates an understanding of the molecular interactions driving the properties of real world materials and complex systems (e.g., those found in biology, chemistry, and materials science). As a result, discovering an explicit, systematic connection between microscopic nature and emergent mesoscopic behavior is a fundamental goal for this type of investigation. The molecular forces critical to driving the behavior of complex heterogeneous systems are often unclear. More problematically, simulations of representative model systems are often prohibitively expensive from both spatial and temporal perspectives, impeding straightforward investigations over possible hypotheses characterizing molecular behavior. While the reduction in resolution of a study, such as moving from an atomistic simulation to that of the resolution of large coarse-grained (CG) groups of atoms, can partially ameliorate the cost of individual simulations, the relationship between the proposed microscopic details and this intermediate resolution is nontrivial and presents new obstacles to study. Small portions of these complex systems can be realistically simulated. Alone, these smaller simulations likely do not provide insight into collectively emergent behavior. However, by proposing that the driving forces in both smaller and larger systems (containing many related copies of the smaller system) have an explicit connection, systematic bottom-up CG techniques can be used to transfer CG hypotheses discovered using a smaller scale system to a larger system of primary interest. The proposed connection between different CG systems is prescribed by (i) the CG representation (mapping) and (ii) the functional form and parameters used to represent the CG energetics, which approximate potentials.

Accurate  pKa Calculations in Proteins with Reactive Molecular Dynamics Provide Physical Insight Into the Electrostatic Origins of Their Values

Classical molecular dynamics simulations are a versatile tool in the study of biomolecular systems, but they usually rely on a fixed bonding topology, precluding the explicit simulation of chemical reactivity. Certain modifications can permit the modeling of reactions. One such method, multiscale reactive molecular dynamics, makes use of a linear combination approach to describe condensed-phase free energy surfaces of reactive processes of biological interest. Before these simulations can be performed, models of the reactive moieties must first be parametrized using electronic structure data. A recent study demonstrated that gas-phase electronic structure data can be used to derive parameters for glutamate and lysine which reproduce experimental pKa values in both bulk water and the staphylococcal nuclease protein with remarkable accuracy and transferability between the water and protein environments. In this work, we first present a new model for aspartate derived in similar fashion and demonstrate that it too produces accurate pKa values in both bulk and protein contexts. We also describe a modification to the prior methodology, involving refitting some of the classical force field parameters to density functional theory calculations, which improves the transferability of the existing glutamate model. Finally and most importantly, this reactive molecular dynamics approach, based on rigorous statistical mechanics, allows one to specifically analyze the fundamental physical causes for the marked pKa shift of both aspartate and glutamate between bulk water and protein and also to demonstrate that local steric and electrostatic effects largely explain the observed differences.

Coarse-graining of Imaginary Time Feynman Path Integrals: Inclusion of Intramolecular Interactions and Bottom-up Force-matching

Feynman’s imaginary time path integral formalism of quantum statistical mechanics and the corresponding quantum-classical isomorphism provide a tangible way of incorporating nuclear quantum effect (NQE) in the simulation of condensed matter systems using well-developed classical simulation techniques. Our previous work has presented the many-body coarse-graining of path integral (CG-PI) theory that builds an isomorphism between the quantum partition function of N distinguishable particles and the classical partition function of 2N pseudoparticles. In this present work, we develop a generalized version of the many-body CG-PI theory that incorporates many-body interactions in the force field. Based on the new derivation, we provide a numerical CG-PI (n-CG-PI) modeling strategy parametrized from the underlying path integral molecular dynamics (PIMD) trajectories using force matching and Boltzmann inversion. The n-CG-PI models for two liquid systems are shown to capture well both the intramolecular and intermolecular structural correlations of the reference PIMD simulations. The generalized derivation of the many-body CG-PI theory and the n-CG-PI model presented in this work extend the scope of the CG-PI formalism by generalizing the previously limited theory to incorporate force fields of realistic molecular systems.

Proton Coupling and the Multiscale Kinetic Mechanism of a Peptide Transporter

Proton-coupled peptide transporters (POTs) are crucial for the uptake of di- and tripeptides as well as drug and prodrug molecules in prokaryotes and eukaryotic cells. We illustrate from multiscale modeling how transmembrane proton flux couples within a POT protein to drive essential steps of the full functional cycle: 1) protonation of a glutamate on transmembrane helix 7 (TM7) opens the extracellular gate, allowing ligand entry; 2) inward proton flow induces the cytosolic release of ligand by varying the protonation state of a second conserved glutamate on TM10; 3) proton movement between TM7 and TM10 is thermodynamically driven and kinetically permissible via water proton shuttling without the participation of ligand. Our results, for the first time, give direct computational confirmation for the alternating access model of POTs, and point to a quantitative multiscale kinetic picture of the functioning protein mechanism..

Accurate and Transferable Reactive Molecular Dynamics Models from Constrained Density Functional Theory

Chemical reactions constitute the central feature of many liquid, material, and biomolecular processes. Conventional molecular dynamics (MD) is inadequate for simulating chemical reactions given the fixed bonding topology of most force fields, while modeling chemical reactions using ab initio molecular dynamics is limited to shorter time and length scales given its high computational cost. As such, the multiscale reactive molecular dynamics method provides one promising alternative for simulating complex chemical systems at atomistic detail on a reactive potential energy surface. However, the parametrization of such models is a key barrier to their applicability and success. In this work, we present reactive MD models derived from constrained density functional theory that are both accurate and transferable. We illustrate the features of these models for proton dissociation reactions of amino acids in both aqueous and protein environments. Specifically, we present models for ionizable glutamate and lysine that predict accurate absolute pKa values in water as well as their significantly shifted pKa in staphylococcal nuclease (SNase) without any modification of the models. As one outcome of the new methodology, the simulations show that the deprotonation of ionizable residues in SNase can be closely coupled with side chain rotations, which is a concept likely generalizable to many other proteins. Furthermore, the present approach is not limited to only pKa prediction but can enable the fully atomistic simulation of many other reactive systems along with a determination of the key aspects of the reaction mechanisms.

Inositol Hexakisphosphate (IP6) Accelerates Immature HIV-1 Gag Protein Assembly Towards Kinetically-Trapped Morphologies

During the late stages of the HIV-1 lifecycle, immature virions are produced by the concerted activity of Gag polyproteins, primarily mediated by the capsid (CA) and spacer peptide 1 (SP1), which assemble into a spherical lattice, package viral genomic RNA, and deform the plasma membrane. Recently, inositol hexakisphosphate (IP6) has been identified as an essential assembly cofactor that efficiently produces both immature virus-like particles. In this work, we investigate the molecular influence of IP6 on the structural outcomes and dynamics of CA/SP1 assembly using coarse-grained (CG) molecular dynamics (MD) simulations and free energy calculations. We derive a bottom-up CG model of CA/SP1 and IP6 and simulate their assembly under conditions that emulate both in vitro and in vivo system. Our findings suggest that IP6 induces kinetically trapped immature morphologies, which may be physiologically important for later stages of viral morphogenesis and potentially useful for virus-like particle technologies.

Seipin Transmembrane Segments Critically Function in Triglyceride Nucleation and Lipid Droplet Budding from the Membrane

Lipid droplets (LDs) are organelles formed in the endoplasmic reticulum (ER) to store triacylglycerol (TG) and sterol esters. The ER protein seipin is key for LD biogenesis. Seipin forms a cage-like structure, with each seipin monomer containing a conserved hydrophobic helix and two transmembrane (TM) segments. How the different parts of seipin function in TG nucleation and LD budding is poorly understood. Here, we utilized molecular dynamics simulations of human seipin, along with cell-based experiments, to study seipin’s functions in protein–lipid interactions, lipid diffusion, and LD maturation. An all-atom simulation indicates that seipin TM segment residues and hydrophobic helices residues located in the phospholipid tail region of the bilayer attract TG. Simulating larger, growing LDs with coarse-grained models, we find that the seipin TM segments form a constricted neck structure to facilitate conversion of a flat oil lens into a budding LD. Using cell experiments and simulations, we also show that conserved, positively charged residues at the end of seipin’s TM segments affect LD maturation. We propose a model in which seipin TM segments critically function in TG nucleation and LD growth.

Static and Dynamic Correlations in Water: Comparison of Classical Ab Initio Molecular Dynamics at Elevated Temperature With Path Integral Simulations at Ambient Temperature

It is a common practice in ab initio molecular dynamics (AIMD) simulations of water to use an elevated temperature to overcome the overstructuring and slow diffusion predicted by most current density functional theory (DFT) models. The simulation results obtained in this distinct thermodynamic state are then compared with experimental data at ambient temperature based on the rationale that a higher temperature effectively recovers nuclear quantum effects (NQEs) that are missing in the classical AIMD simulations. In this work, we systematically examine the foundation of this assumption for several DFT models as well as for the many-body MB-pol model. We find for the cases studied that a higher temperature does not correctly mimic NQEs at room temperature, which is especially manifest in significantly different three-molecule correlations as well as hydrogen bond dynamics. In many of these cases, the effects of NQEs are the opposite of the effects of carrying out the simulations at an elevated temperature.

Ion permeation, selectivity, and electronic polarization in fluoride channels

Fluoride channels (Flucs) export toxic F− from the cytoplasm. Crystallography and mutagenesis have identified several conserved residues crucial for fluoride transport, but the permeation mechanism at the molecular level has remained elusive. Herein, we have applied constant-pH molecular dynamics and free-energy-sampling methods to investigate fluoride permeation through a Fluc protein from Escherichia coli. We find that fluoride is facile to permeate in its charged form, i.e., F−, by traversing through a non-bonded network. The extraordinary F− selectivity is gained by the hydrogen-bonding capability of the central binding site and the Coulombic filter at the channel entrance. The F− permeation rate calculated using an electronically polarizable force field is significantly more accurate compared with the experimental value than that calculated using a more standard additive force field, suggesting an essential role for electronic polarization in the F−–Fluc interactions.

Computational Studies of Lipid Droplets

Lipid droplets (LDs) are intracellular organelles whose primary function is energy storage. Known to emerge from the endoplasmic reticulum (ER) bilayer, LDs have a unique structure with a core consisting of neutral lipids, triacylglycerol (TG) or sterol esters (SE), surrounded by a phospholipid (PL) monolayer and decorated by proteins that come and go throughout their complex lifecycle. In this Feature Article, we review recent developments in computational studies of LDs, a rapidly growing area of research. We highlight how molecular dynamics (MD) simulations have provided valuable molecular-level insight into LD targeting and LD biogenesis. Additionally, we review the physical properties of TG from different force fields compared with experimental data. Possible future directions and challenges are discussed.

Strain and Rupture of HIV-1 Capsids During Uncoating

The mature capsids of HIV-1 are transiently stable complexes that self-assemble around the viral genome during maturation, and uncoat to release preintegration complexes that archive a double-stranded DNA copy of the virus in the host cell genome. However, a detailed view of how HIV cores rupture remains lacking. Here, we elucidate the physical properties involved in capsid rupture using a combination of large-scale all-atom molecular dynamics simulations and cryo-electron tomography. We find that intrinsic strain on the capsid forms highly correlated patterns along the capsid surface, along which cracks propagate. Capsid rigidity also increases with high strain. Our findings provide fundamental insight into viral capsid uncoating.

Cooperative Multivalent Receptor Binding Promotes Exposure of the SARS-CoV-2 Fusion Machinery Core

The molecular events that permit the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to bind and enter cells are important to understand for both fundamental and therapeutic reasons. Spike proteins consist of S1 and S2 domains, which recognize angiotensin-converting enzyme 2 (ACE2) receptors and contain the viral fusion machinery, respectively. Ostensibly, the binding of spike trimers to ACE2 receptors promotes dissociation of the S1 domains and exposure of the fusion machinery, although the molecular details of this process have yet to be observed. We report the development of bottom-up coarse-grained (CG) models consistent with cryo-electron tomography data, and the use of CG molecular dynamics simulations to investigate viral binding and S2 core exposure. We show that spike trimers cooperatively bind to multiple ACE2 dimers at virion-cell interfaces in a manner distinct from binding between soluble proteins, which processively induces S1 dissociation. We also simulate possible variant behavior using perturbed CG models, and find that ACE2-induced S1 dissociation is primarily sensitive to conformational state populations and the extent of S1/S2 cleavage, rather than ACE2 binding affinity. These simulations reveal an important concerted interaction between spike trimers and ACE2 dimers that primes the virus for membrane fusion and entry.

Key Factors Governing Initial Stages of Lipid Droplet Formation

Lipid droplets (LDs) are neutral lipid storage organelles surrounded by a phospholipid (PL) monolayer. LD biogenesis from the endoplasmic reticulum is driven by phase separation of neutral lipids, overcoming surface tension and membrane deformation. However, the core biophysics of the initial steps of LD formation remains relatively poorly understood. Here, we use a tunable, phenomenological coarse–grained model to study triacylglycerol (TG) nucleation in a bilayer membrane. We show that PL rigidity has a strong influence on TG lensing and membrane remodeling: when membrane rigidity increases, TG clusters remain more planar with high anisotropy but a minor degree of phase nucleation. This finding is confirmed by advanced sampling simulations that calculate nucleation free energy as a function of the degree of nucleation and anisotropy. We also show that asymmetric tension, controlled by the number of PL molecules on each membrane leaflet, determines the budding direction. A TG lens buds in the direction of the monolayer containing excess PL molecules to allow for better PL coverage of TG, consistent with the reported experiments. Finally, two governing mechanisms of the LD growth, Ostwald ripening and merging, are observed. Taken together, this study characterizes the interplay between two thermodynamic quantities during the initial LD phases, the TG bulk free energy and membrane remodeling energy.

Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics

Ab initio molecular dynamics (AIMD) has become one of the most popular and robust approaches for modeling complicated chemical, liquid, and material systems. However, the formidable computational cost often limits its widespread application in simulations of the largest-scale systems. The situation becomes even more severe in cases where the hydrogen nuclei may be better described as quantized particles using a path integral representation. Here, we present a computational approach that combines machine learning with recent advances in path integral contraction schemes, and we achieve a 2 orders of magnitude acceleration over direct path integral AIMD simulation while at the same time maintaining its accuracy.

Multiscale Simulation of an Influenza A M2 Channel Mutant Reveals Key Features of Its Markedly Different Proton Transport Behavior

The influenza A M2 channel, a prototype for viroporins, is an acid-activated viroporin that conducts protons across the viral membrane, a critical step in the viral life cycle. Four central His37 residues control channel activation by binding subsequent protons from the viral exterior, which opens the Trp41 gate and allows proton flux to the interior. Asp44 is essential for maintaining the Trp41 gate in a closed state at high pH, resulting in asymmetric conduction. The prevalent D44N mutant disrupts this gate and opens the C-terminal end of the channel, resulting in increased conduction and a loss of this asymmetric conduction. Here, we use extensive Multiscale Reactive Molecular Dynamics (MS-RMD) and quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations with an explicit, reactive excess proton to calculate the free energy of proton transport in this M2 mutant and to study the dynamic molecular-level behavior of D44N M2. We find that this mutation significantly lowers the barrier of His37 deprotonation in the activated state and shifts the barrier for entry to the Val27 tetrad. These free energy changes are reflected in structural shifts. Additionally, we show that the increased hydration around the His37 tetrad diminishes the effect of the His37 charge on the channel’s water structure, facilitating proton transport and enabling activation from the viral interior. Altogether, this work provides key insight into the fundamental characteristics of PT in WT M2 and how the D44N mutation alters this PT mechanism, and it expands understanding of the role of emergent mutations in viroporins.

2021

Molecular interactions of the M and E integral membrane proteins of SARS-CoV-2

Specific lipid–protein interactions are key for cellular processes, and even more so for the replication of pathogens. The COVID-19 pandemic has drastically changed our lives and caused the death of nearly four million people worldwide, as of this writing. SARS-CoV-2 is the virus that causes the disease and has been at the center of scientific research over the past year. Most of the research on the virus is focused on key players during its initial attack and entry into the cellular host; namely the S protein, its glycan shield, and its interactions with the ACE2 receptors of human cells. As cases continue to rise around the globe, and new mutants are identified, there is an urgent need to understand the mechanisms of this virus during different stages of its life cycle. Here, we consider two integral membrane proteins of SARS-CoV-2 known to be important for viral assembly and infectivity. We have used microsecond-long all-atom molecular dynamics to examine the lipid–protein and protein–protein interactions of the membrane (M) and envelope (E) structural proteins of SARS-CoV-2 in a complex membrane model. We contrast the two proposed protein complexes for each of these proteins, and quantify their effect on their local lipid environment. This ongoing work also aims to provide molecular-level understanding of the mechanisms of action of this virus to possibly aid in the design of novel treatments.

A Quantitative Paradigm for Water Assisted Proton Transport Through Proteins and Other Confined Spaces

Water-assisted proton transport through confined spaces influences many phenomena in biomolecular and nanomaterial systems. In such cases, the water molecules that fluctuate in the confined pathways provide the environment and the medium for the hydrated excess proton migration via Grotthuss shuttling. However, a definitive collective variable (CV) that accurately couples the hydration and the connectivity of the proton wire with the proton translocation has remained elusive. To address this important challenge—and thus to define a quantitative paradigm for facile proton transport in confined spaces—a CV is derived in this work from graph theory, which is verified to accurately describe water wire formation and breakage coupled to the proton translocation in carbon nanotubes and the Cl⁻/H⁺ antiporter protein, ClC-ec1. Significant alterations in the conformations and thermodynamics of water wires are uncovered after introducing an excess proton into them. Large barriers in the proton translocation free-energy profiles are found when water wires are defined to be disconnected according to the new CV, even though the pertinent confined space is still reasonably well hydrated and—by the simple measure of the mere existence of a water structure—the proton transport would have been predicted to be facile via that oversimplified measure. In this paradigm, however, the simple presence of water is not sufficient for inferring proton translocation, since an excess proton itself is able to drive hydration, and additionally, the water molecules themselves.

Preservation of HIV-1 Gag Helical Bundle Symmetry by Bevirimat Is Central to Maturation Inhibition

The assembly and maturation of human immunodeficiency virus type 1 (HIV-1) require proteolytic cleavage of the Gag polyprotein. The rate-limiting step resides at the junction between the capsid protein CA and spacer peptide 1, which assembles as a six-helix bundle (6HB). Bevirimat (BVM), the first-in-class maturation inhibitor drug, targets the 6HB and impedes proteolytic cleavage, yet the molecular mechanisms of its activity, and relatedly, the escape mechanisms of mutant viruses, remain unclear. Here, we employed extensive molecular dynamics (MD) simulations and free energy calculations to quantitatively investigate molecular structure–activity relationships, comparing wild-type and mutant viruses in the presence and absence of BVM and inositol hexakisphosphate (IP6), an assembly cofactor. Our analysis shows that the efficacy of BVM is directly correlated with preservation of 6-fold symmetry in the 6HB, which exists as an ensemble of structural states. We identified two primary escape mechanisms, and both lead to loss of symmetry, thereby facilitating helix uncoiling to aid access of protease. Our findings also highlight specific interactions that can be targeted for improved inhibitor activity and support the use of MD simulations for future inhibitor design.

Resolving the Structural Debate for the Hydrated Excess Proton in Water

It has long been proposed that the hydrated excess proton in water (aka the solvated “hydronium” cation) likely has two limiting forms, that of the Eigen cation (H₉O₄⁺) and that of the Zundel cation (H₅O₂⁺). There has been debate over which of these two is the more dominant species and/or whether intermediate (or “distorted”) structures between these two limits are the more realistic representation. Spectroscopy experiments have recently provided further results regarding the excess proton. These experiments show that the hydrated proton has an anisotropy reorientation time scale on the order of 1–2 ps. This time scale has been suggested to possibly contradict the picture of the more rapid “special pair dance” phenomenon for the hydrated excess proton, which is a signature of a distorted Eigen cation. The special pair dance was predicted from prior computational studies in which the hydrated central core hydronium structure continually switches (O–H···O)* special pair hydrogen-bond partners with the closest three water molecules, yielding on average a distorted Eigen cation with three equivalent and dynamically exchanging distortions. Through state-of-art simulations it is shown here that anisotropy reorientation time scales of the same magnitude are obtained that also include structural reorientations associated with the special pair dance, leading to a reinterpretation of the experimental results. These results and additional analyses point to a distorted and dynamic Eigen cation as the most prevalent hydrated proton species in aqueous acid solutions of dilute to moderate concentration, as opposed to a stabilized or a distorted (but not “dancing”) Zundel cation.

Integrin-Based Mechanosensing through Conformational Activation

Cells can detect and react to the biophysical properties of the extracellular environment through integrin-based adhesion sites and adapt to the extracellular milieu in a process called mechanotransduction. At these adhesion sites, integrins connect the extracellular matrix (ECM) with the F-actin cytoskeleton and transduce mechanical forces generated by the actin retrograde flow and myosin II to the ECM through mechanosensitive focal adhesion proteins that are collectively termed the “molecular clutch.” The transmission of forces across integrin-based adhesions establishes a mechanical reciprocity between the viscoelasticity of the ECM and the cellular tension. During mechanotransduction, force allosterically alters the functions of mechanosensitive proteins within adhesions to elicit biochemical signals that regulate both rapid responses in cellular mechanics and long-term changes in gene expression. Integrin-mediated mechanotransduction plays important roles in development and tissue homeostasis, and its dysregulation is often associated with diseases.

2020