Cryo-EM single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many protein complexes are flexible and can change conformation and composition as a result of functionally-associated dynamics. Such dynamics are poorly captured by current analysis methods. Here, we present cryoDRGN, an algorithm that for the first time leverages the representation power of deep neural networks to efficiently reconstruct highly heterogeneous complexes and continuous trajectories of protein motion. We apply this tool to two

The ability for viruses to mutate and evade the human immune system and cause infection, called viral escape, remains an obstacle to antiviral and vaccine development. Understanding the complex rules that govern escape could inform therapeutic design. We modeled viral escape with machine learning algorithms originally developed for human natural language. We identified escape mutations as those that preserve viral infectivity but cause a virus to look different to the immune system, akin to word changes that preserve a sentence’s grammaticality but change its meaning. With this approach, language models of influenza hemagglutinin, HIV-1 envelope glycoprotein (HIV Env), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike viral proteins can accurately predict structural escape patterns using sequence data alone. Our study represents a promising conceptual bridge between natural language and viral evolution.

We describe our efforts to prepare common starting structures and models for the SAMPL5 blind prediction challenge. We generated the starting input files and single configuration potential energies for the host-guest in the SAMPL5 blind prediction challenge for the GROMACS, AMBER, LAMMPS, DESMOND and CHARMM molecular simulation programs. All conversions were fully automated from the originally prepared AMBER input files using a combination of the ParmEd and InterMol conversion programs. We find that the energy calculations for all molecular dynamics engines for this molecular set agree to a better than 0.1% relative absolute energy for all energy components, and in most cases an order of magnitude better, when reasonable choices are made for different cutoff parameters. However, there are some surprising sources of statistically significant differences. Most importantly, different choices of Coulomb’s constant between programs are one of the largest sources of discrepancies in energies. We discuss the measures required to get good agreement in the energies for equivalent starting configurations between the simulation programs, and the energy differences that occur when simulations are run with program-specific default simulation parameter values. Finally, we discuss what was required to automate this conversion and comparison.

In motile cilia, a mechanoregulatory network is responsible for converting the action of thousands of dynein motors bound to doublet microtubules into a single propulsive waveform. Here, we use two complementary cryo-EM strategies to determine structures of the major mechanoregulators that bind ciliary doublet microtubules in Chlamydomonas reinhardtii . We determine structures of isolated radial spoke RS1, and the microtubule-bound RS1, RS2, and the nexin-dynein regulatory complex. From these structures, we identify and build atomic models for 30 proteins including 23 radial-spoke subunits. We reveal how mechanoregulatory complexes dock to doublet microtubules with regular 96-nm periodicity and communicate with one another. Additionally, we observe a direct and dynamically coupled association between RS2 and the dynein motor IDA c , providing a molecular basis for the control of motor activity by mechanical signals. These structures advance our understanding of the role of mechanoregulation in defining the ciliary waveform.

Radar‐bright features near Mercury's poles have been postulated to be deposits of water ice trapped in cold, permanently shadowed interiors of impact craters. From its orbit about Mercury, MESSENGER repeatedly imaged the planet's south polar region over one Mercury solar day, providing a complete view of the terrain near the south pole and enabling the identification of areas of permanent shadow larger in horizontal extent than approximately 4 km. In Mercury's south polar region, all radar‐bright features correspond to areas of permanent shadow. Application of previous thermal models suggests that the radar‐bright deposits in Mercury's south polar cold traps are in locations consistent with a composition dominated by water ice provided that some manner of insulation, such as a thin layer of regolith, covers many of the deposits.