Structural basis of inhibition of human Na1.8 by the tarantula venom peptide Protoxin-I.

Voltage-gated sodium channels (Nas) selectively permit diffusion of sodium ions across the cell membrane and, in excitable cells, are responsible for propagating action potentials. One of the nine human Na isoforms, Na1.8, is a promising target for analgesics, and selective inhibitors are of interest as therapeutics.

δ-Conotoxin Structure Prediction and Analysis through Large-Scale Comparative and Deep Learning Modeling Approaches.

The δ-conotoxins, a class of peptides produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage-gated sodium channels causing paralysis and other neurological responses, but difficulties in their isolation and synthesis have made structural characterization challenging. Taking advantage of recent breakthroughs in computational algorithms for structure prediction that have made modeling especially useful when experimental data is sparse, this work uses both the deep-learning-based algorithm AlphaFold and comparative modeling method RosettaCM to model and analyze 18 previously uncharacterized δ-conotoxins derived from piscivorous, vermivorous, and molluscivorous cone snails. The models provide useful insights into the structural aspects of these peptides and suggest features likely to be significant in influencing their binding and different pharmacological activities against their targets, with implications for drug development.

Phollow: Visualizing Gut Bacteriophage Transmission within Microbial Communities and Living Animals.

Bacterial viruses (known as "phages") shape the ecology and evolution of microbial communities, making them promising targets for microbiome engineering. However, knowledge of phage biology is constrained because it remains difficult to study phage transmission dynamics within multi-member communities and living animal hosts. We therefore created "Phollow": a live imaging-based approach for tracking phage replication and spread in situ with single-virion resolution.

Mitigating the Blurring Effect of CryoEM Averaging on a Flexible and Highly Symmetric Protein Complex through Sub-Particle Reconstruction.

Many macromolecules are inherently flexible as a feature of their structure and function. During single-particle CryoEM processing, flexible protein regions can be detrimental to high-resolution reconstruction as signals from thousands of particles are averaged together. This "blurring" effect can be difficult to overcome and is possibly more pronounced when averaging highly symmetric complexes.

Delta-Conotoxin Structure Prediction and Analysis through Large-scale Comparative and Deep Learning Modeling Approaches.

The delta-conotoxins, a class of peptide produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage-gated sodium channels causing paralysis and other neurological responses, but difficulties in their isolation and synthesis have made structural characterization challenging. Taking advantage of recent breakthroughs in computational algorithms for structure prediction that have made modeling especially useful when experimental data is sparse, this work uses both the deep-learning based algorithm AlphaFold and comparative modeling method RosettaCM to model and analyze 18 previously uncharacterized delta-conotoxins derived from piscivorous, vermivorous, and molluscivorous cone snails. The models provide useful insights into structural aspects of these peptides and suggest features likely to be significant in influencing their binding and different pharmacological activities against their targets, with implications for drug development.

Improved interface packing and design opportunities revealed by CryoEM analysis of a designed protein nanocage.

Symmetric protein assemblies play important roles in nature which makes them an attractive target for engineering. symmetric protein complexes can be created through computational protein design to tailor their properties from first principles, and recently several protein nanocages have been created by bringing together protein components through hydrophobic interactions. Accurate experimental structures of newly-developed proteins are essential to validate their design, improve assembly stability, and tailor downstream applications.

Progress Towards CryoEM: Negative-Stain Procedures for Biological Samples.

In recent years, electron cryo-microscopy (CryoEM) has become a powerful method for the high-resolution studies of biological macromolecules. While CryoEM experiments can begin without additional microscopy steps, negative-stain EM can tremendously minimize CryoEM screening. Negative-stain is a quick method that can be used to screen for robust biochemical conditions, the integrity, binding, and composition of samples and to get an estimation of sample grid concentration.

Structure of hepcidin-bound ferroportin reveals iron homeostatic mechanisms.

The serum level of iron in humans is tightly controlled by the action of the hormone hepcidin on the iron efflux transporter ferroportin. Hepcidin regulates iron absorption and recycling by inducing the internalization and degradation of ferroportin. Aberrant ferroportin activity can lead to diseases of iron overload, such as haemochromatosis, or iron limitation anaemias.

Near-atomic cryo-EM imaging of a small protein displayed on a designed scaffolding system.

Current single-particle cryo-electron microscopy (cryo-EM) techniques can produce images of large protein assemblies and macromolecular complexes at atomic level detail without the need for crystal growth. However, proteins of smaller size, typical of those found throughout the cell, are not presently amenable to detailed structural elucidation by cryo-EM. Here we use protein design to create a modular, symmetrical scaffolding system to make protein molecules of typical size suitable for cryo-EM.

Accurate design of megadalton-scale two-component icosahedral protein complexes.

Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.

Design of a hyperstable 60-subunit protein dodecahedron. [corrected].

The dodecahedron [corrected] is the largest of the Platonic solids, and icosahedral protein structures are widely used in biological systems for packaging and transport. There has been considerable interest in repurposing such structures for applications ranging from targeted delivery to multivalent immunogen presentation. The ability to design proteins that self-assemble into precisely specified, highly ordered icosahedral structures would open the door to a new generation of protein containers with properties custom-tailored to specific applications.

Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression.

We recently reported the development of a computational method for the design of coassembling multicomponent protein nanomaterials. While four such materials were validated at high-resolution by X-ray crystallography, low yield of soluble protein prevented X-ray structure determination of a fifth designed material, T33-09. Here we report the design and crystal structure of T33-31, a variant of T33-09 with improved soluble yield resulting from redesign efforts focused on mutating solvent-exposed side chains to charged amino acids.

Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces.

We describe a general approach to designing two-dimensional (2D) protein arrays mediated by noncovalent protein-protein interfaces. Protein homo-oligomers are placed into one of the seventeen 2D layer groups, the degrees of freedom of the lattice are sampled to identify configurations with shape-complementary interacting surfaces, and the interaction energy is minimized using sequence design calculations. We used the method to design proteins that self-assemble into layer groups P 3 2 1, P 4 2(1) 2, and P 6.

Accurate design of co-assembling multi-component protein nanomaterials.

The self-assembly of proteins into highly ordered nanoscale architectures is a hallmark of biological systems. The sophisticated functions of these molecular machines have inspired the development of methods to engineer self-assembling protein nanostructures; however, the design of multi-component protein nanomaterials with high accuracy remains an outstanding challenge. Here we report a computational method for designing protein nanomaterials in which multiple copies of two distinct subunits co-assemble into a specific architecture.

The structure of purified kinetochores reveals multiple microtubule-attachment sites.

Chromosomes must be accurately partitioned to daughter cells to prevent aneuploidy, a hallmark of many tumors and birth defects. Kinetochores are the macromolecular machines that segregate chromosomes by maintaining load-bearing attachments to the dynamic tips of microtubules. Here, we present the structure of isolated budding-yeast kinetochore particles, as visualized by EM and electron tomography of negatively stained preparations.