This project aims to solve the structure of the crenarchaeal Sulfolobus acidocaldarius enzyme malate synthase. Other known malate synthase enzymes have been found to require a magnesium ion in the active site to carry out catalytic activities, but a study reported that S. acidocaldarius malate synthase does not require magnesium. This suggests a novel mechanism for this enzyme. Additionally, the mature S. acidocaldarius protein is approximately 100 residues larger than any other structurally characterized malate synthase. It has also been reported to form a dimer, while previously solved structures have only displayed monomeric, trimeric, and hexameric arrangements. We plan to determine the structure experimentally. However, major advances in the accuracy of protein structure prediction were made recently by AlphaFold, an artificial intelligence system developed by DeepMind, which has revolutionized the field and has largely solved the protein folding problem. A similar AI system, RoseTTAFold, developed by David Baker’s lab at the University of Washington, has been publicly available. Here, we report our analysis of the structure of this protein, predicted using both of these algorithms and of a predicted structural model for the dimeric form of the enzyme using ClusPro. Our results strongly support a conserved catalytic mechanism requiring magnesium, which is common with all previously solved malate synthase isoforms. KEYWORDS: Glyoxylate Cycle; Malate synthase; Protein Prediction; Thermophile; Sulfolobus acidocaldarius; Magnesium; AlphaFold; RoseTTAFold