Critical mechanistic features of HIV-1 viral capsid assembly

HIV-1 adapts to lost IP6 coordination through second-site mutations that restore conical capsid assembly

The HIV-1 capsid is composed of capsid (CA) protein hexamers and pentamers (capsomers) that contain a central pore hypothesised to regulate capsid assembly and facilitate nucleotide import early during post-infection. These pore functions are mediated by two positively charged rings created by CA Arg-18 (R18) and Lys-25 (K25). Here we describe the forced evolution of viruses containing mutations in R18 and K25. Whilst R18 mutants fail to replicate, K25A viruses acquire compensating mutations that restore nearly wild-type replication fitness. These compensating mutations, which rescue reverse transcription and infection without reintroducing lost pore charges, map to three adaptation hot-spots located within and between capsomers. The second-site suppressor mutations act by restoring the formation of pentamers lost upon K25 mutation, enabling closed conical capsid assembly both in vitro and inside virions. These results indicate that there is no intrinsic requirement for K25 in either nucleotide import or capsid assembly. We propose that whilst HIV-1 must maintain a precise hexamer:pentamer equilibrium for proper capsid assembly, compensatory mutations can tune this equilibrium to restore fitness lost by mutation of the central pore.

QM/CG-MM: Systematic Embedding of Quantum Mechanical Systems in a Coarse-Grained Environment with Accurate Electrostatics

Quantum Mechanics/Molecular Mechanics (QM/MM) can describe chemical reactions in molecular dynamics (MD) simulations at a much lower cost than ab initio MD. Still, it is prohibitively expensive for many systems of interest because such systems usually require long simulations for sufficient statistical sampling. Additional MM degrees of freedom are often slow and numerous but secondary in interest. Coarse-graining (CG) is well-known to be able to speed up sampling through both reduction in simulation cost and the ability to accelerate the dynamics. Therefore, embedding a QM system in a CG environment can be a promising way of expediting sampling without compromising the information about the QM subsystem. Sinitskiy and Voth first proposed the theory of Quantum Mechanics/Coarse-grained Molecular Mechanics (QM/CG-MM) with a bottom-up CG mapping. Mironenko and Voth subsequently introduced the DFT-QM/CG-MM formalism to couple a Density Functional Theory (DFT) treated QM system and to an apolar environment. Here, we present a more complete theory that addresses MM environments with significant polarity by explicitly accounting for the electrostatic coupling. We demonstrate our QM/CG-MM method with a chloride-methyl chloride SN2 reaction system in acetone, which is sensitive to solvent polarity. The method accurately recapitulates the potential of mean force for the substitution reaction, and the reaction barrier from the best model agrees with the atomistic simulations within sampling error. These models also have generalizability. In two other reactive systems that they have not been trained on, the QM/CG-MM model still achieves the same level of agreement with the atomistic QM/MM models. Finally, we show that in these examples the speed-up in the sampling is proportional to the acceleration of the rotational dynamics of the solvent in the CG system.

Hierarchical Framework for Predicting Entropies in Bottom-Up Coarse-Grained Models

The thermodynamic entropy of coarse-grained (CG) models stands as one of the most important properties for quantifying the missing information during the CG process and for establishing transferable (or extendible) CG interactions. However, performing additional CG simulations on top of model construction often leads to significant additional computational overhead. In this work, we propose a simple hierarchical framework for predicting the thermodynamic entropies of various molecular CG systems. Our approach employs a decomposition of the CG interactions, enabling the estimation of the CG partition function and thermodynamic properties a priori. Starting from the ideal gas description, we leverage classical perturbation theory to systematically incorporate simple yet essential interactions, ranging from the hard sphere model to the generalized van der Waals model. Additionally, we propose an alternative approach based on multiparticle correlation functions, allowing for systematic improvements through higher-order correlations. Numerical applications to molecular liquids validate the high fidelity of our approach, and our computational protocols demonstrate that a reduced model with simple energetics can reasonably estimate the thermodynamic entropy of CG models without performing any CG simulations. Overall, our findings present a systematic framework for estimating not only the entropy but also other thermodynamic properties of CG models, relying solely on information from the reference system.

A Review of FDA-Approved Anti-HIV-1 Drugs, Anti-Gag Compounds, and Potential Strategies for HIV-1 Eradication

Acquired immunodeficiency syndrome (AIDS) is an enormous global health threat stemming from human immunodeficiency virus (HIV-1) infection. Up to now, the tremendous advances in combination antiretroviral therapy (cART) have shifted HIV-1 infection from a fatal illness into a manageable chronic disorder. However, the presence of latent reservoirs, the multifaceted nature of HIV-1, drug resistance, severe off-target effects, poor adherence, and high cost restrict the efficacy of current cART targeting the distinct stages of the virus life cycle. Therefore, there is an unmet need for the discovery of new therapeutics that not only bypass the limitations of the current therapy but also protect the body's health at the same time. The main goal for complete HIV-1 eradication is purging latently infected cells from patients' bodies. A potential strategy called "lock-in and apoptosis" targets the budding phase of the life cycle of the virus and leads to susceptibility to apoptosis of HIV-1 infected cells for the elimination of HIV-1 reservoirs and, ultimately, for complete eradication. The current work intends to present the main advantages and disadvantages of United States Food and Drug Administration (FDA)-approved anti-HIV-1 drugs as well as plausible strategies for the design and development of more anti-HIV-1 compounds with better potency, favorable pharmacokinetic profiles, and improved safety issues.

Formalizing Coarse-Grained Representations of Anisotropic Interactions at Multimeric Protein Interfaces Using Virtual Sites

Molecular simulations of biomacromolecules that assemble into multimeric complexes remain a challenge due to computationally inaccessible length and time scales. Low-resolution and implicit-solvent coarse-grained modeling approaches using traditional nonbonded interactions (both pairwise and spherically isotropic) have been able to partially address this gap. However, these models may fail to capture the complex anisotropic interactions present at macromolecular interfaces unless higher-order interaction potentials are incorporated at the expense of the computational cost. In this work, we introduce an alternate and systematic approach to represent directional interactions at protein-protein interfaces by using virtual sites restricted to pairwise interactions. We show that virtual site interaction parameters can be optimized within a relative entropy minimization framework by using only information from known statistics between coarse-grained sites. We compare our virtual site models to traditional coarse-grained models using two case studies of multimeric protein assemblies and find that the virtual site models predict pairwise correlations with higher fidelity and, more importantly, assembly behavior that is morphologically consistent with experiments. Our study underscores the importance of anisotropic interaction representations and paves the way for more accurate yet computationally efficient coarse-grained simulations of macromolecular assembly in future research.

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

HIV-1 Capsid Uncoating Is a Multistep Process That Proceeds through Defect Formation Followed by Disassembly of the Capsid Lattice

The HIV-1 core consists of a cone-shaped capsid shell made of capsid protein (CA) hexamers and pentamers encapsulating the viral genome. HIV-1 capsid disassembly, referred to as uncoating, is important for productive infection; however, the location, timing, and regulation of uncoating remain controversial. Here, we employ amber codon suppression to directly label CA. In addition, a fluid phase fluorescent probe is incorporated into the viral core to detect small defects in the capsid lattice. This double-labeling strategy enables the visualization of uncoating of single cores in vitro and in living cells, which we found to always proceed through at least two distinct steps─the formation of a defect in the capsid lattice that initiates gradual loss of CA below a detectable level. Importantly, intact cores containing the fluid phase and CA fluorescent markers enter and uncoat in the nucleus, as evidenced by a sequential loss of both markers, prior to establishing productive infection. This two-step uncoating process is observed in different cells, including a macrophage line. Notably, the lag between the release of fluid phase marker and terminal loss of CA appears to be independent of the cell type or reverse transcription and is much longer (>5-fold) for nuclear capsids compared to cell-free cores or cores in the cytosol, suggesting that the capsid lattice is stabilized by capsid-binding nuclear factors. Our results imply that intact HIV-1 cores enter the cell nucleus and that uncoating is initiated through a localized defect in the capsid lattice prior to a global loss of CA.

HIV-1 capsid shape, orientation, and entropic elasticity regulate translocation into the nuclear pore complex

Nuclear import and uncoating of the viral capsid are critical steps in the HIV-1 life cycle that serve to transport and release genomic material into the nucleus. Viral core import involves translocating the HIV-1 capsid at the nuclear pore complex (NPC). Notably, the central channel of the NPC appears to often accommodate and allow passage of intact HIV-1 capsid, though mechanistic details of the process remain to be fully understood. Here, we investigate the molecular interactions that operate in concert between the HIV-1 capsid and the NPC that regulate capsid translocation through the central channel. To this end, we develop a "bottom-up" coarse-grained (CG) model of the human NPC from recently released cryo-electron tomography structure and then construct composite membrane-embedded CG NPC models. We find that successful translocation from the cytoplasmic side to the NPC central channel is contingent on the compatibility of the capsid morphology and channel dimension and the proper orientation of the capsid approach to the channel from the cytoplasmic side. The translocation dynamics is driven by maximizing the contacts between phenylalanine-glycine nucleoporins at the central channel and the capsid. For the docked intact capsids, structural analysis reveals correlated striated patterns of lattice disorder likely related to the intrinsic capsid elasticity. Uncondensed genomic material inside the docked capsid augments the overall lattice disorder of the capsid. Our results suggest that the intrinsic "elasticity" can also aid the capsid to adapt to the stress and remain structurally intact during translocation.

Capsid-host interactions for HIV-1 ingress

The HIV-1 capsid, composed of approximately 1,200 copies of the capsid protein, encases genomic RNA alongside viral nucleocapsid, reverse transcriptase, and integrase proteins. After cell entry, the capsid interacts with a myriad of host factors to traverse the cell cytoplasm, pass through the nuclear pore complex (NPC), and then traffic to chromosomal sites for viral DNA integration. Integration may very well require the dissolution of the capsid, but where and when this uncoating event occurs remains hotly debated. Based on size constraints, a long-prevailing view was that uncoating preceded nuclear transport, but recent research has indicated that the capsid may remain largely intact during nuclear import, with perhaps some structural remodeling required for NPC traversal. Completion of reverse transcription in the nucleus may further aid capsid uncoating. One canonical type of host factor, typified by CPSF6, leverages a Phe-Gly (FG) motif to bind capsid. Recent research has shown these peptides reside amid prion-like domains (PrLDs), which are stretches of protein sequence devoid of charged residues. Intermolecular PrLD interactions along the exterior of the capsid shell impart avid host factor binding for productive HIV-1 infection. Herein we overview capsid-host interactions implicated in HIV-1 ingress and discuss important research questions moving forward. Highlighting clinical relevance, the long-acting ultrapotent inhibitor lenacapavir, which engages the same capsid binding pocket as FG host factors, was recently approved to treat people living with HIV.

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.

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.

OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining

The "bottom-up" approach to coarse-graining, for building accurate and efficient computational models to simulate large-scale and complex phenomena and processes, is an important approach in computational chemistry, biophysics, and materials science. As one example, the Multiscale Coarse-Graining (MS-CG) approach to developing CG models can be rigorously derived using statistical mechanics applied to fine-grained, i.e., all-atom simulation data for a given system. Under a number of circumstances, a systematic procedure, such as MS-CG modeling, is particularly valuable. Here, we present the development of the OpenMSCG software, a modularized open-source software that provides a collection of successful and widely applied bottom-up CG methods, including Boltzmann Inversion (BI), Force-Matching (FM), Ultra-Coarse-Graining (UCG), Relative Entropy Minimization (REM), Essential Dynamics Coarse-Graining (EDCG), and Heterogeneous Elastic Network Modeling (HeteroENM). OpenMSCG is a high-performance and comprehensive toolset that can be used to derive CG models from large-scale fine-grained simulation data in file formats from common molecular dynamics (MD) software packages, such as GROMACS, LAMMPS, and NAMD. OpenMSCG is modularized in the Python programming framework, which allows users to create and customize modeling "recipes" for reproducible results, thus greatly improving the reliability, reproducibility, and sharing of bottom-up CG models and their applications.

Sub-stoichiometric Modulation of Viral Targets-Potent Antiviral Agents That Exploit Target Vulnerability

The modulation of oligomeric viral targets at sub-stoichiometric ratios of drug to target has been advocated for its efficacy and potency, but there are only a limited number of documented examples. In this Viewpoint, we summarize the invention of the HIV-1 maturation inhibitor fipravirimat and discuss the emerging details around the mode of action of this class of drug that reflects inhibition of a protein composed of 1,300-1,600 monomers that interact in a cooperative fashion. Similarly, the HCV NS5A inhibitor daclatasvir has been shown to act in a highly sub-stoichiometric fashion, inhibiting viral replication at concentrations that are ∼23,500 lower than that of the protein target.

Analyzing the Geometry and Dynamics of Viral Structures: A Review of Computational Approaches Based on Alpha Shape Theory, Normal Mode Analysis, and Poisson-Boltzmann Theories

The current SARS-CoV-2 pandemic highlights our fragility when we are exposed to emergent viruses either directly or through zoonotic diseases. Fortunately, our knowledge of the biology of those viruses is improving. In particular, we have more and more structural information on virions, i.e., the infective form of a virus that includes its genomic material and surrounding protective capsid, and on their gene products. It is important to have methods that enable the analyses of structural information on such large macromolecular systems. We review some of those methods in this paper. We focus on understanding the geometry of virions and viral structural proteins, their dynamics, and their energetics, with the ambition that this understanding can help design antiviral agents. We discuss those methods in light of the specificities of those structures, mainly that they are huge. We focus on three of our own methods based on the alpha shape theory for computing geometry, normal mode analyses to study dynamics, and modified Poisson-Boltzmann theories to study the organization of ions and co-solvent and solvent molecules around biomacromolecules. The corresponding software has computing times that are compatible with the use of regular desktop computers. We show examples of their applications on some outer shells and structural proteins of the West Nile Virus.

Understanding Virus Structure and Dynamics through Molecular Simulations

Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.

Structural insights into HIV-1 polyanion-dependent capsid lattice formation revealed by single particle cryo-EM

The HIV-1 capsid houses the viral genome and interacts extensively with host cell proteins throughout the viral life cycle. It is composed of capsid protein (CA), which assembles into a conical fullerene lattice composed of roughly 200 CA hexamers and 12 CA pentamers. Previous structural analyses of individual CA hexamers and pentamers have provided valuable insight into capsid structure and function, but detailed structural information about these assemblies in the broader context of the capsid lattice is lacking. In this study, we combined cryoelectron tomography and single particle analysis (SPA) cryoelectron microscopy to determine structures of continuous regions of the capsid lattice containing both hexamers and pentamers. We also developed a method of liposome scaffold-based in vitro lattice assembly ("lattice templating") that enabled us to directly study the lattice under a wider range of conditions than has previously been possible. Using this approach, we identified a critical role for inositol hexakisphosphate in pentamer formation and determined the structure of the CA lattice bound to the capsid-targeting antiretroviral drug GS-6207 (lenacapavir). Our work reveals key structural details of the mature HIV-1 CA lattice and establishes the combination of lattice templating and SPA as a robust strategy for studying retroviral capsid structure and capsid interactions with host proteins and antiviral compounds.

Enrich and switch: IP6 and maturation of HIV-1 capsid

Recent studies offer new insight on the mechanisms of IP6-mediated HIV-1 capsid assembly. The immature Gag lattice enables enrichment of IP6 into virions, aiding capsid maturation. Structures of capsid protein (CA) assemblies reveal motifs serving as switches modulating the conformations of CA pentamers/hexamers and affect co-factor accessibility.