title: Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions.
abstract: Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.
authors.affiliation: Protagonist Pty Ltd, St Lucia, QLD, Australia. t.tran@protagonist.com.au
authors.forename: Tran T
authors.initials: TT
authors.lastname: Tran
authors.forename: Christina
authors.initials: C
authors.lastname: Kulis
authors.forename: Steven M
authors.initials: SM
authors.lastname: Long
authors.forename: Darryn
authors.initials: D
authors.lastname: Bryant
authors.forename: Peter
authors.initials: P
authors.lastname: Adams
authors.forename: Mark L
authors.initials: ML
authors.lastname: Smythe
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D016000:Cluster Analysis; D020650:Combinatorial Chemistry Techniques; D017076:Computer-Aided Design; D030562:Databases, Protein; D015195:Drug Design; D055808:Drug Discovery; D004353:Drug Evaluation, Preclinical; D057786:Peptidomimetics / Q000737:chemistry; D054730:Protein Interaction Domains and Motifs; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
chemical_list: D057786:Peptidomimetics; D011506:Proteins