MitoNEET is a recently identified drug target for a commonly prescribed diabetes drug, Pioglitazone. It belongs to a previously uncharacterized ancient family of proteins for which the hallmark is the presence of a unique 39 amino acid CDGSH domain. In order to characterize the folding landscape of this novel fold, we performed thermodynamic simulations on MitoNEET using a structurebased model. Additionally, we implement a method of contact map clustering to partition out alternate pathways in folding. This cluster analysis reveals a detour late in folding and enables us to carefully examine the folding mechanism of each pathway rather than the macroscopic average. We observe that tightness in a region distal to the iron-sulfur cluster creates a constraint in folding and additionally appears to mediate communication in folding between the two domains of the protein. We demonstrate that by making changes at this site we are able to tweak the order of folding events in the cluster binding domain as well as decrease the barrier to folding.itoNEET is a recently identified outer mitochondrial membrane protein that unexpectedly binds the commonly prescribed type II diabetes drug Pioglitazone (1-3). It is now recognized as a new drug target in diabetes therapy as opposed to the traditional PPARg therapeutics (4). Mis-splicing of Miner1, the structural homolog of mitoNEET, results in the rare disease Wolfram syndrome that initially presents with diabetes and rapidly progresses to blindness and early death (5). In addition, Miner1 appears to play a significant role in aging and associated diseases. MitoNEET and Miner1 possess a unique homodimeric fold with a CDGSH iron-sulfur cluster binding domain and a strand swapped beta cap (3, 6-10). Because regulating the activity of this new drug target is an area of high interest, investigation of the folding and possible allosteric modulation of function in this family is now a major research focus.Energy landscape theory indicates that proteins have evolved to fold in a funneled fashion with minimal frustration (11-13). Because energetic frustration is sufficiently small, much of the heterogeneity in folding is dominated by the geometric constraints of the native structure. As a result, structure-based models are capable of capturing the main features of the transition state and intermediates formed during folding for many proteins (14-19). In addition, our analysis of the bottlenecks in folding have led to a deeper understanding of regulatory mechanisms operating in specific proteins. This led us to the hypothesis that functional regions in proteins may add roughness to the landscape because they are under separate evolutionary pressure than areas used for efficient folding. For example, structure-based simulations with adenylate kinase demonstrated that the introduction of frustration induced conformational transitions associated with enzymatic catalyisis through specific unfolding, or cracking (20,21). Folding simulations with Csk and IL-1β successfully captured long range c...