Classical solution of the FeMo-cofactor model to chemical accuracy and its implications

TL;DR

This paper demonstrates a classical computational approach to accurately determine the electronic structure of the FeMo-cofactor, a complex biological catalyst, challenging the notion that quantum computing is necessary for such tasks.

Contribution

It introduces classical protocols that achieve chemical accuracy for FeMo-cofactor models, providing a new pathway for studying complex bioinorganic systems.

Findings

Classical methods can reach chemical accuracy for FeMo-co models.

A simplified computational procedure reveals electronic landscape of FeMo-co.

Classical approaches challenge the assumption that quantum computing is required for such complex systems.

Abstract

The main source of reduced nitrogen for living things comes from nitrogenase, which converts N2 to NH3 at the FeMo-cofactor (FeMo-co). Because of its role in supporting life, the uncertainty surrounding the catalytic cycle, and its compositional richness with eight transition metal ions, FeMo-co has fascinated scientists for decades. After much effort, the complete atomic structure was resolved. However, its electronic structure, central to reactivity, remains under intense debate. FeMo-co's complexity, arising from many unpaired electrons, has led to suggestions that it lies beyond the reach of classical computing. Consequently, there has been much interest in the potential of quantum algorithms to compute its electronic structure. Estimating the cost to compute the ground-state to chemical accuracy (~1 kcal/mol) within one or more FeMo-co models is a common benchmark of quantum algorithms in quantum chemistry, with numerous resource estimates in the literature. Here we address how to perform the same task using classical computation. We use a 76 orbital/152 qubit resting state model, the subject of most quantum resource estimates. Based on insight into the multiple configuration nature of the states, we devise classical protocols that yield rigorous or empirical upper bounds to the ground-state energy. Extrapolating these we predict the ground-state energy with an estimated uncertainty on the order of chemical accuracy. Having performed this long-discussed computational task, we next consider implications beyond the model. We distill a simpler computational procedure which we apply to reveal the electronic landscape in realistic representations of the cofactor. We thus illustrate a path to a precise computational understanding of FeMo-co electronic structure.