Computational chemistry

Theory Project: Density Functional Theory Modelization of Iron Clusters of Biological Relevance

The understanding of the role of transition metals in biological systems is key to unveil important aspects of the enzymatic capability of metaloenzymes which contains a metal cluster core. For instance, the iron-sulfur clusters are ubiquitous in biological systems and may be found in the active site of a wide variety of metalloproteins and metalloenzymes, which are involved in biological processes such as electron transfer (ferredoxin), small molecule activation (nitrogenase, hydrogenase, carbon monoxide dehydrogenase), radical-based catalytic transformations (hydrogen abstraction, sulfur insertion in biotin synthase), DNA repair and signal transduction. The most common clusters are the following: [Fe2S2], [Fe3S4] and [Fe4S4], and their primary function lies in the mediation of one-electron redox processes.

In these polymetallic systems, the Fe atoms present several oxidation states with unpaired electrons that can be coupled by magnetic interactions, giving rise to a dense manifold of ferro- and antiferromagnetic electronic states which may be separated by small energy differences. In this way, a detailed knowledge of the electron delocalization in the cluster in terms of Fe-Fe interactions is a key point in order to understand the properties of both the ground and excited states. The goal of this project is to use state-of-the-art DFT to benchmark the performance of these methods to model FeS clusters and their electronic excitations.

The candidate should have a basic knowledge on quantum mechanics (assumed in chemistry and physics BSc. students), and be eager to learn the basics of computational chemistry.

Supervisors: Xabier Lopez and Txema Mercero.

Status: Closed.