Topological side-chain classification of β-turns: Ideal motifs for peptidomimetic development

Summaryβ-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of β-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. β-turns have traditionally been classified into various types based on the backbone dihedral angles (φ2, ψ2, φ3 and ψ3). Indeed, 57–68% of β-turns are currently classified into 8 different backbone families (Type I, Type II, Type I′, Type II′, Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified β-turns). Although this classification of β-turns has been useful, the resulting β-turn types are not ideal for the design of β-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted β-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by Cα–Cβ vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four Cα–Cβ vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of β-turns. The mean structures of the nine clusters are useful for the development of β-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.