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1.
J Comput Aided Mol Des ; 19(8): 551-66, 2005 Aug.
Article in English | MEDLINE | ID: mdl-16328857

ABSTRACT

Beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. Beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi2, psi2, phi3 and psi3). Indeed, 57-68% of beta-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 beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C(alpha)-C(beta) 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 C(alpha)-C(beta) vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.


Subject(s)
Molecular Mimicry , Peptides/chemistry , Protein Structure, Secondary , Proteins/chemistry , Algorithms , Cluster Analysis , Databases, Protein , Drug Design , Models, Molecular
2.
Magn Reson Chem ; 27(9): 852-862, 1989 Sep.
Article in English | MEDLINE | ID: mdl-34034428

ABSTRACT

Natural abundance 75 MHz 13 C NMR spectral assignments are reported for bovine and porcine zinc insulin in solution. A large number of protein resonances are well resolved, and approximately 80% of these have been assigned to either residue types or to specific sites within the protein. Assignment techniques included consideration of free amino acid or peptide shifts pH studies and comparison of sequence and spectral differences between bovine and porcine insulin, in addition to the use of NMR relaxation times. The DEPT spectral editing technique was also found to be particularly valuable as an assignment aid. This technique allows subspectra containing only CH, CH2 or CH3 carbon types to be generated. The method also produces signal enhancement relative to broad band decoupled 13 C NMR spectra of large proteins which generally have reduced nuclear Overhauser enhancements.

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