Water droplets containing the SARS-CoV-2 virus, responsible for coronavirus 2019 transmission, were introduced into a controlled-temperature and -humidity chamber. The SARS-CoV-2 virus with green fluorescent protein tag in droplets was used to infect Caco-2 cells, with viability assessed through flow cytometry and microscopic counting. Whereas temperature fluctuations within typical indoor ranges (20°C–30°C) had minimal impact, we observed a notable decrease in infection rate as the surrounding air’s relative humidity increased. By investigating humidity levels between 20% and 70%, we identified a threshold of ≥40% relative humidity as most effective in diminishing SARS-CoV-2 infectivity. We also found that damage of the viral proteins under high relative humidity may be responsible for the decrease in their activity. This outcome supports previous research demonstrating a rise in the concentration of reactive oxygen species within water droplets with elevated relative humidity.

The resistance–nodulation–division efflux machinery confers antimicrobial resistance to Gram-negative bacteria by actively pumping antibiotics out of the cell. The protein complex is powered by proton motive force; however, the proton transfer mechanism itself and indeed even its stoichiometry is still unclear. Here we review computational studies from the last decade that focus on elucidating the number of protons transferred per conformational cycle of the pump. Given the difficulties in studying proton movement using even state-of-the-art structural biology methods, the contributions from computational studies have been invaluable from a mechanistic perspective.

The formulation and testing of hypotheses using ‘big biology data’ often lie at the interface of computational biology and structural biology. The Protein Data Bank (PDB), which was established about 50 years ago, catalogs three-dimensional (3D) shapes of organic macromolecules and showcases a structural view of biology. The comparative analysis of the structures of homologs, particularly of proteins, from different species has significantly improved the in-depth analyses of molecular and cell biological questions. In addition, computational tools that were developed to analyze the ‘protein universe’ are providing the means for efficient resolution of longstanding debates in cell and molecular evolution. In celebrating the golden jubilee of the PDB, much has been written about the transformative impact of PDB on a broad range of fields of scientific inquiry and how structural biology transformed the study of the fundamental processes of life. Yet, the transforming influence of PDB on one field of inquiry of fundamental interest—the reconstruction of the distant biological past—has gone almost unnoticed. Here, I discuss the recent advances to highlight how insights and tools of structural biology are bearing on the data required for the empirical resolution of vigorously debated and apparently contradicting hypotheses in evolutionary biology. Specifically, I show that evolutionary characters defined by protein structure are superior compared to conventional sequence characters for reliable, data-driven resolution of competing hypotheses about the origins of the major clades of life and evolutionary relationship among those clades. Since the better quality data unequivocally support two primary domains of life, it is imperative that the primary classification of life be revised accordingly.