Understanding 2D-IR Spectra of Hydrogenases: A Descriptive and Predictive Computational Study

Abstract

[NiFe] hydrogenases are metalloenzymes that catalyze the reversible cleavage of dihydrogen (H2), a clean future fuel. Understanding the mechanism of these biocatalysts requires spectroscopic techniques that yield insights into the structure and dynamics of the [NiFe] active site. Due to the presence of CO and CN− ligands at this cofactor, infrared (IR) spectroscopy represents an ideal technique for studying these aspects, but molecular information from linear IR absorption experiments is limited. More detailed insights can be obtained from ultrafast nonlinear IR techniques like IRpump-IRprobe and two-dimensional (2D-)IR spectroscopy. However, fully exploiting these advanced techniques requires an in-depth understanding of experimental observables and the encoded molecular information. To address this challenge, we present a descriptive and predictive computational approach for the simulation and analysis of static 2D-IR spectra of [NiFe] hydrogenases and similar organometallic systems. Accurate reproduction of experimental spectra from a first-coordination-sphere model suggests a decisive role of the [NiFe] core in shaping the enzymatic potential energy surface. We also reveal spectrally encoded molecular information that is not accessible by experiments, thereby helping to understand the catalytic role of the diatomic ligands, structural differences between [NiFe] intermediates, and possible energy transfer mechanisms. Our studies demonstrate the feasibility and benefits of computational spectroscopy in the 2D-IR investigation of hydrogenases, thereby further strengthening the potential of this nonlinear IR technique as a powerful research tool for the investigation of complex bioinorganic molecules.