Structure-oriented bioinformatic approach exploring histidine-rich clusters in proteins.

Spatially clustered histidines are commonly found in protein structures. The versatility of histidine coordination favors transition metal bindings, suggesting that spatially clustered histidines are potentially involved in metal binding and thereby play an important role in protein functions. We have applied a bioinformatic approach to identify and characterize histidine-rich clusters (HrCs) protein candidates with a focus on metal coordination. The computational analysis revealed over a thousand non-homologous HrC proteins with a large portion exhibiting interaction with transition metals, particularly zinc, copper and nickel. The results reflect that multiple histidines are apparently clustered together for the corroboration of both static and dynamical metal binding. The identified HrC proteins are correlated with microbial pathogenesis, offering useful information for drug design. This approach can be readily extended to other types of biological studies, where the relationship between single amino acid-rich clusters and their structural-functional relationships can be scrutinized.