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Enzymes in multistep metabolic pathways utilize an array of regulatory mechanisms to maintain a delicate homeostasis [K. Magnuson, S. Jackowski, C. O. Rock, J. E. Cronan, Jr,Microbiol. Rev.57, 522–542 (1993)]. Carrier proteins in particular play an essential role in shuttling substrates between appropriate enzymes in metabolic pathways. Although hypothesized [E. Płoskoń et al.,Chem. Biol.17, 776–785 (2010)], allosteric regulation of substrate delivery has never before been demonstrated for any acyl carrier protein (ACP)-dependent pathway. Studying these mechanisms has remained challenging due to the transient and dynamic nature of protein–protein interactions, the vast diversity of substrates, and substrate instability [K. Finzel, D. J. Lee, M. D. Burkart,ChemBioChem16, 528–547 (2015)]. Here we demonstrate a unique communication mechanism between the ACP and partner enzymes using solution NMR spectroscopy and molecular dynamics to elucidate allostery that is dependent on fatty acid chain length. We demonstrate that partner enzymes can allosterically distinguish between chain lengths via protein–protein interactions as structural features of substrate sequestration are translated from within the ACP four-helical bundle to the protein surface, without the need for stochastic chain flipping. These results illuminate details of cargo communication by the ACP that can serve as a foundation for engineering carrier protein-dependent pathways for specific, desired products. 

CRISPR-Cas9 is a cutting-edge genome-editing technology, which employs the endonuclease Cas9 to cleave DNA sequences of interest. However, the catalytic mechanism of DNA cleavage and the critical role of the Mg2+ ions have remained elusive. Here, quantum–classical QM(Car-Parrinello)/MM simulations are used to disclose the two-Mg2+ aided mechanism of phosphodiester bond cleavage in the RuvC domain. We reveal that the catalysis proceeds through an associative pathway activated by H983 and fundamentally assisted by the joint dynamics of the two Mg2+ ions, which cooperatively act to properly orient the reactants and lead the chemical step to completion. Cross-validation of this mechanism is achieved by evaluating alternative reaction pathways and in light of experimental data, delivering fundamental insights on how CRISPR-Cas9 cleaves nucleic acids. This knowledge is critical for improving the Cas9 catalytic efficiency and its metal-dependent function, helping also the development of novel Cas9-based genome-editing tools. 

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike’s full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.