Computational Modeling and Experimental Approaches for Understanding the Mechanisms of [FeFe]-Hydrogenase
Submitted by Jun Zhu on Sun, 05/11/2025 - 08:52
Learning from nature has emerged as a promising strategy for catalyst development, wherein the remarkable performance of catalysts selected by nature over billions of years of evolution serves as a basis for the creative design of high-performance catalysts. Hydrogenases, with their exceptional catalytic activity in hydrogen oxidation and production, have been employed as prototypes for human learning to achieve better catalyst design. A comprehensive understanding of hydrogenases' structures and catalytic mechanisms is crucial to replicate and exceed their performance.