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Catalytic dwell oscillations complete the F1-ATPase mechanism

The F1-ATPase molecular motor rotates subunit-γ in 120° power strokes within its ring of three catalytic sites separated by catalytic dwells for ATP hydrolysis and Pi release. By monitoring rotary position of subunit-γ in E. coli F1 every 5 μs, we resolved Stage-1 catalytic dwell oscillations that extend from -13° to 13° centered at 0° consistent with F1 structures containing transition state inhibitors, which decay by a first order process consistent with ATP hydrolysis. During Stage-2, 80% of the oscillations extend from 3° and 25° centered at 14°, while 20% are centered at 33° and can extend to 27°–44° comparable to the ATP binding position. Remarkably, in Stage-3 subunit-γ returns to 0° to end the catalytic dwell, which keeps the start of power strokes in phase for consecutive rotational events. These newly observed states fit with F1 structures that were inconsistent with the canonical mechanism, and indicate that catalytic dwell oscillations must persist until the correct occupancy of substrates and products occurs at all three catalytic sites. When that condition is met, F1 can proceed to the next power stroke. Understanding the basis of these catalytic dwell oscillations completes the F1-ATPase rotary mechanism.

Crystal structures of monomeric BsmI restriction endonuclease reveal coordinated sequential cleavage of two DNA strands

BsmI, a thermophilic Type IIS restriction endonuclease from Bacillus stearothermophilus, presents a unique structural composition, housing two distinct active sites within a single monomer. Recognition of the non-symmetrical 5’-GAATGC-3’ sequence enables precise cleavage of the top and bottom DNA strands. Synthetic biology interventions have led to the transformation of BsmI into Nb.BsmI, a nicking endonuclease. Here we introduce Nt*.BsmI, tailored for top-strand cleavage, which is inactive on standard double-stranded DNA, but active on bottom-strand nicked DNA, suggesting a sequential cleavage mechanism. Crystallographic structures of pre- and post-reactive complexes with cognate DNA show one major conformational change, a retractable loop possibly governing sequential active site accessibility. The x-ray structures reveal the position of the divalent metal ions in the active sites and the DNA:protein interactions, while the models predicted by Alphafold3 are incorrect. This comprehensive structural and functional study lays a foundation for rational enzyme redesign and potential applications in biotechnology.

Photo-assisted technologies for environmental remediation

Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage light energy to mineralize these contaminants. In this Review, we discuss the mechanisms and efficiencies of photo-assisted advanced oxidation processes for wastewater treatment and photothermal technologies for air purification. The integration of solar energy enhances degradation efficiency and reduces energy consumption, enabling more efficient remediation methods. We evaluate the technological aspects of photo-assisted technologies, such as photo-Fenton, photo-persulfate activation, photo-ozonation and photoelectrochemical oxidation, emphasizing their potential for practical applications. Finally, we discuss the challenges in scaling up photo-assisted technologies for specific environmental remediation needs. Photo-assisted technologies have demonstrated effectiveness in environmental remediation, although large-scale applications remain constrained by high costs. Future potential applications of photo-assisted technologies will require that technology selection be tailored to specific pollution scenarios and engineering processes optimized to minimize costs.

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

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