Elasticity of the HIV-1 Core Facilitates Nuclear Entry and Infection

HIV-1 infection requires passage of the viral core through the nuclear pore of the cell, a process that depends on functions of the viral capsid 1,2 . Recent studies have shown that HIV- 1 cores enter the nucleus prior to capsid disassembly 3-5 . Interactions with the nuclear pore complex are necessary but not sufficient for nuclear entry, and the mechanism by which the viral core traverses the comparably sized nuclear pore is unknown. Here we show that the HIV-1 core is highly elastic and that this property is linked to nuclear entry and infectivity. Using atomic force microscopy-based approaches, we found that purified wild type cores rapidly returned to their normal conical morphology following a severe compression. Results from independently performed molecular dynamic simulations of the mature HIV-1 capsid also revealed its elastic property. Analysis of four HIV-1 capsid mutants that exhibit impaired nuclear entry revealed that the mutant viral cores are brittle. Suppressors of the mutants restored elasticity and rescued infectivity and nuclear entry. Elasticity was also reduced by treatment of cores with the capsid-targeting compound PF74 and the antiviral drug lenacapavir. Our results indicate that capsid elasticity is a fundamental property of the HIV-1 core that enables its passage through the nuclear pore complex, thereby facilitating infection. These results provide new insights into the mechanisms of HIV-1 nuclear entry and the antiviral mechanisms of HIV-1 capsid inhibitors.

Multidisciplinary studies with mutated HIV-1 capsid proteins reveal structural mechanisms of lattice stabilization

HIV-1 capsid (CA) stability is important for viral replication. E45A and P38A mutations enhance and reduce core stability, thus impairing infectivity. Second-site mutations R132T and T216I rescue infectivity. Capsid lattice stability was studied by solving seven crystal structures (in native background), including P38A, P38A/T216I, E45A, E45A/R132T CA, using molecular dynamics simulations of lattices, cryo-electron microscopy of assemblies, time-resolved imaging of uncoating, biophysical and biochemical characterization of assembly and stability. We report pronounced and subtle, short- and long-range rearrangements: (1) A38 destabilized hexamers by loosening interactions between flanking CA protomers in P38A but not P38A/T216I structures. (2) Two E45A structures showed unexpected stabilizing CANTD-CANTD inter-hexamer interactions, variable R18-ring pore sizes, and flipped N-terminal β-hairpin. (3) Altered conformations of E45Aa α9-helices compared to WT, E45A/R132T, WTPF74, WTNup153, and WTCPSF6 decreased PF74, CPSF6, and Nup153 binding, and was reversed in E45A/R132T. (4) An environmentally sensitive electrostatic repulsion between E45 and D51 affected lattice stability, flexibility, ion and water permeabilities, electrostatics, and recognition of host factors.

Performance efficient macromolecular mechanics via sub-nanometer shape based coarse graining

Dimensionality reduction via coarse grain modeling is a valuable tool in biomolecular research. For large assemblies, ultra coarse models are often knowledge-based, relying on a priori information to parameterize models thus hindering general predictive capability. Here, we present substantial advances to the shape based coarse graining (SBCG) method, which we refer to as SBCG2. SBCG2 utilizes a revitalized formulation of the topology representing network which makes high-granularity modeling possible, preserving atomistic details that maintain assembly characteristics. Further, we present a method of granularity selection based on charge density Fourier Shell Correlation and have additionally developed a refinement method to optimize, adjust and validate high-granularity models. We demonstrate our approach with the conical HIV-1 capsid and heteromultimeric cofilin-2 bound actin filaments. Our approach is available in the Visual Molecular Dynamics (VMD) software suite, and employs a CHARMM-compatible Hamiltonian that enables high-performance simulation in the GPU-resident NAMD3 molecular dynamics engine.

Recognition of the TDP-43 nuclear localization signal by importin α1/β

Cytoplasmic mislocalization of the TAR-DNA binding protein of 43 kDa (TDP-43) leads to large, insoluble aggregates that are a hallmark of amyotrophic lateral sclerosis and frontotemporal dementia. Here, we study how importin α1/β recognizes TDP-43 bipartite nuclear localization signal (NLS). We find that the NLS makes extensive contacts with importin α1, especially at the minor NLS-binding site. NLS binding results in steric clashes with the C terminus of importin α1 that disrupts the TDP-43 N-terminal domain (NTD) dimerization interface. A putative phosphorylation site in the proximity of TDP-43 R83 at the minor NLS site destabilizes binding to importins by reducing the NLS backbone dynamics. Based on these data, we explain the pathogenic role of several post-translational modifications and mutations in the proximity of TDP-43 minor NLS site that are linked to disease and shed light on the chaperone activity of importin α1/β.

Full scale structural, mechanical and dynamical properties of HIV-1 liposomes

Enveloped viruses are enclosed by a lipid membrane inside of which are all of the components necessary for the virus life cycle; viral proteins, the viral genome and metabolites. Viral envelopes are lipid bilayers that adopt morphologies ranging from spheres to tubes. The envelope is derived from the host cell during viral replication. Thus, the composition of the bilayer depends on the complex constitution of lipids from the host-cell's organelle(s) where assembly and/or budding of the viral particle occurs. Here, molecular dynamics (MD) simulations of authentic, asymmetric HIV-1 liposomes are used to derive a unique level of resolution of its full-scale structure, mechanics and dynamics. Analysis of the structural properties reveal the distribution of thicknesses of the bilayers over the entire liposome as well as its global fluctuations. Moreover, full-scale mechanical analyses are employed to derive the global bending rigidity of HIV-1 liposomes. Finally, dynamical properties of the lipid molecules reveal important relationships between their 3D diffusion, the location of lipid-rafts and the asymmetrical composition of the envelope. Overall, our simulations reveal complex relationships between the rich lipid composition of the HIV-1 liposome and its structural, mechanical and dynamical properties with critical consequences to different stages of HIV-1's life cycle.

Deep-learning in situ classification of HIV-1 virion morphology

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Efficient classifier capable of overcoming inherent problems of small-data training sets.

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Automated detection and classification of HIV-1 particle morphology from transmission electron micrographs.

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Three orders of magnitude speed increase in data processing with negligible loss in accuracy.

Transmission electron microscopy (TEM) has a multitude of uses in biomedical imaging due to its ability to discern ultrastructure morphology at the nanometer scale. Through its ability to directly visualize virus particles, TEM has for several decades been an invaluable tool in the virologist’s toolbox. As applied to HIV-1 research, TEM is critical to evaluate activities of inhibitors that block the maturation and morphogenesis steps of the virus lifecycle. However, both the preparation and analysis of TEM micrographs requires time consuming manual labor. Through the dedicated use of computer vision frameworks and machine learning techniques, we have developed a convolutional neural network backbone of a two-stage Region Based Convolutional Neural Network (RCNN) capable of identifying, segmenting and classifying HIV-1 virions at different stages of maturation and morphogenesis. Our results outperformed common RCNN backbones, achieving 80.0% mean Average Precision on a diverse set of micrographs comprising different experimental samples and magnifications. We expect that this tool will be of interest to a broad range of researchers.

Molecular dynamics of the viral life cycle: progress and prospects

Molecular dynamics (MD) simulations across spatiotemporal resolutions are widely applied to study viruses and represent the central technique uniting the field of computational virology. We discuss the progress of MD in elucidating the dynamics of the viral life cycle, including the status of modeling intact extracellular virions and leveraging advanced simulations to mimic active life cycle processes. We further remark on the prospects of MD for continued contributions to the basic science characterization of viruses, especially given the increasing availability of high-quality experimental data and supercomputing power. Overall, integrative computational methods that are closely guided by experiments are unmatched in the level of detail they provide, enabling-now and in the future-new discoveries relevant to thwarting viral infection.

Curvature of the Retroviral Capsid Assembly Is Modulated by a Molecular Switch

During the maturation step, the retroviral capsid proteins (CAs) assemble into polymorphic capsids. Their acute curvature is largely determined by 12 pentamers inserted into the hexameric lattice. However, how the CA switches its conformation to control assembly curvature remains unclear. We report the high-resolution structural model of the Rous sarcoma virus (RSV) CA T = 1 capsid, established by molecular dynamics simulations combining solid-state NMR and prior cryoelectron tomography restraints. Comparing this with our previous model of the RSV CA tubular assembly, we identify the key residues for dictating the incorporation of acute curvatures. These residues undergo large torsion angle changes, resulting in a 34° rotation of the C-terminal domain relative to its N-terminal domain around the flexible interdomain linker, without substantial changes of either the conformation of individual domains or the assembly contact interfaces. This knowledge provides new insights to help decipher the mechanism of the retroviral capsid assembly.

Atomic-resolution structure of HIV-1 capsid tubes by magic-angle spinning NMR

HIV-1 capsid plays multiple key roles in viral replication, and inhibition of capsid assembly is an attractive target for therapeutic intervention. Here, we report the atomic-resolution structure of the capsid protein (CA) tubes, determined by magic-angle-spinning NMR and data-guided molecular dynamics simulations. Functionally important regions, including the NTD β-hairpin, the cyclophilin A loop, residues in the hexamer center pore, and the NTD-CTD linker region, are well defined. The structure of individual CA chains, their arrangement in the pseudo-hexameric units of the tube and the inter-hexamer interfaces are consistent with those in intact capsid cores and substantially different from the organization in crystal structures, which featured flat hexamers. The inherent curvature in the CA tubes is controlled by conformational variability of residues in the linker region and of dimer and trimer interfaces. The present structure reveals atomic-level detail into capsid architecture and provides important guidance for the design of novel capsid inhibitors.

Accelerating prediction of chemical shift of protein structures on GPUs: Using OpenACC

Experimental chemical shifts (CS) from solution and solid state magic-angle-spinning nuclear magnetic resonance (NMR) spectra provide atomic level information for each amino acid within a protein or protein complex. However, structure determination of large complexes and assemblies based on NMR data alone remains challenging due to the complexity of the calculations. Here, we present a hardware accelerated strategy for the estimation of NMR chemical-shifts of large macromolecular complexes based on the previously published PPM_One software. The original code was not viable for computing large complexes, with our largest dataset taking approximately 14 hours to complete. Our results show that serial code refactoring and parallel acceleration brought down the time taken of the software running on an NVIDIA Volta 100 (V100) Graphic Processing Unit (GPU) to 46.71 seconds for our largest dataset of 11.3 million atoms. We use OpenACC, a directive-based programming model for porting the application to a heterogeneous system consisting of x86 processors and NVIDIA GPUs. Finally, we demonstrate the feasibility of our approach in systems of increasing complexity ranging from 100K to 11.3M atoms.

Nuclear magnetic resonance (NMR) spectroscopy yields chemical shifts (CSs) which reveal chemical details of the environment of an atom in a protein. Computer estimation of CSs require the calculation of several contributing terms including interatomic distances, ring current effects and the formation of hydrogen bonds. Here, taking advantage of graphic processing units (GPUs), the estimation of chemical shifts are accelerated thus enabling the determination of the CSs for large systems, encompassing millions of atoms. The rapid determination of CSs enables the use of CS-based validation for other molecular dynamics computations.

High-Performance Analysis of Biomolecular Containers to Measure Small-Molecule Transport, Transbilayer Lipid Diffusion, and Protein Cavities

Compartmentalization is a central theme in biology. Cells are composed of numerous membrane-enclosed structures, evolved to facilitate specific biochemical processes; viruses act as containers of genetic material, optimized to drive infection. Molecular dynamics simulations provide a mechanism to study biomolecular containers and the influence they exert on their environments; however, trajectory analysis software generally lacks knowledge of container interior versus exterior. Further, many relevant container analyses involve large-scale particle tracking endeavors, which may become computationally prohibitive with increasing system size. Here, a novel method based on 3-D ray casting is presented, which rapidly classifies the space surrounding biomolecular containers of arbitrary shape, enabling fast determination of the identities and counts of particles (e.g., solvent molecules) found inside and outside. The method is broadly applicable to the study of containers and enables high-performance characterization of properties such as solvent density, small-molecule transport, transbilayer lipid diffusion, and topology of protein cavities. The method is implemented in VMD, a widely used simulation analysis tool that supports personal computers, clouds, and parallel supercomputers, including ORNL’s Summit and Titan and NCSA’s Blue Waters, where the method can be employed to efficiently analyze trajectories encompassing millions of particles. The ability to rapidly characterize the spatial relationships of particles relative to a biomolecular container over many trajectory frames, irrespective of large particle counts, enables analysis of containers on a scale that was previously unfeasible, at a level of accuracy that was previously unattainable.

Structural basis for the homotypic fusion of chlamydial inclusions by the SNARE-like protein IncA

Many intracellular bacteria, including Chlamydia, establish a parasitic membrane-bound organelle inside the host cell that is essential for the bacteria’s survival. Chlamydia trachomatis forms inclusions that are decorated with poorly characterized membrane proteins known as Incs. The prototypical Inc, called IncA, enhances Chlamydia pathogenicity by promoting the homotypic fusion of inclusions and shares structural and functional similarity to eukaryotic SNAREs. Here, we present the atomic structure of the cytoplasmic domain of IncA, which reveals a non-canonical four-helix bundle. Structure-based mutagenesis, molecular dynamics simulation, and functional cellular assays identify an intramolecular clamp that is essential for IncA-mediated homotypic membrane fusion during infection.

Chlamydia trachomatis forms membrane-bound inclusions inside the host cell that are decorated with IncA, a SNARE-like protein that promotes the fusion of inclusions. Here, Cingolani et al. show that the protein folds into a non-canonical four-helix bundle and identify an intramolecular clamp required for membrane fusion.