Modeling catalytic reaction on ligand-protected metal nanoclusters

Abstract

Monolayer protected metal nanoclusters (MPC) show great potential for catalysis, highlighting the need for unraveling their mechanistic intricacies to enhance catalyst performance. However, due to their inherent complexity, an in-depth understanding of how nanoclusters facilitate chemical transformation has remained elusive. In this work, we employed a combination of classical molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) MD simulations, augmented with the on-the-fly probability-based enhanced sampling (OPES) method, to elucidate substrate binding to the MPC and a chemical reaction on the MPC surface. We investigated the oxidation of amino alcohol to oxazolidine, catalyzed by a peptide ligand functionalized Au₂₅ gold nanocluster, as a prototypical example. Classical MD simulations unveiled the crucial role of solvent and peptide-based ligands in substrate binding, while QM/MM simulations elucidated the mechanistic pathway and provided insight into the free energy landscape of the chemical reaction. This work demonstrates a computational workflow that can be applied to study similar MPC-catalyzed chemical reactions.