Dataset Information

Immunoproteasome ?5i-Selective Dipeptidomimetic Inhibitors.

ABSTRACT: N,C-capped dipeptides belong to a class of noncovalent proteasome inhibitors. Herein we report that the insertion of a ?-amino acid into N,C-capped dipeptides markedly decreases their inhibitory potency against human constitutive proteasome ?5c, while maintaining potent inhibitory activity against human immunoproteasome ?5i, thereby achieving thousands-fold selectivity for ?5i over ?5c. Structure-activity relationship studies revealed that ?5c does not tolerate the ?-amino acid based dipeptidomimetics as does ?5i. In?vitro, one such compound was found to inhibit human T?cell proliferation. Compounds of this class may have potential as therapeutics for autoimmune and inflammatory diseases with less mechanism-based cytotoxicity than agents that also inhibit the constitutive proteasome.

SUBMITTER: Singh PK

PROVIDER: S-EPMC5760267 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Immunoproteasome β5i-Selective Dipeptidomimetic Inhibitors.

Singh Pradeep K PK Fan Hao H Jiang Xiuju X Shi Lei L Nathan Carl F CF Lin Gang G

ChemMedChem 20160825 19

N,C-capped dipeptides belong to a class of noncovalent proteasome inhibitors. Herein we report that the insertion of a β-amino acid into N,C-capped dipeptides markedly decreases their inhibitory potency against human constitutive proteasome β5c, while maintaining potent inhibitory activity against human immunoproteasome β5i, thereby achieving thousands-fold selectivity for β5i over β5c. Structure-activity relationship studies revealed that β5c does not tolerate the β-amino acid based dipeptidomi ...[more]

PMID: 27561172

Similar Datasets

Project description:The ubiquitin-proteasome system is responsible for the degradation of proteins and plays a critical role in key cellular processes. While the constitutive proteasome (cPS) is expressed in all eukaryotic cells, the immunoproteasome (iPS) is primarily induced during disease processes, and its inhibition is beneficial in the treatment of cancer, autoimmune disorders and neurodegenerative diseases. Oxathiazolones were reported to selectively inhibit iPS over cPS, and the inhibitory activity of several oxathiazolones against iPS was experimentally determined. However, the detailed mechanism of the chemical reaction leading to irreversible iPS inhibition and the key selectivity drivers are unknown, and separate characterization of the noncovalent and covalent inhibition steps is not available for several compounds. Here, we investigate the chemical reaction between oxathiazolones and the Thr1 residue of iPS by quantum mechanics/molecular mechanics (QM/MM) simulations to establish a plausible reaction mechanism and to determine the rate-determining step of covalent complex formation. The modelled binding mode and reaction mechanism are in line with the selective inhibition of iPS versus cPS by oxathiazolones. The kinact value of several ligands was estimated by constructing the potential of mean force of the rate-determining step by QM/MM simulations coupled with umbrella sampling. The equilibrium constant Ki of the noncovalent complex formation was evaluated by classical force field-based thermodynamic integration. The calculated Ki and kinact values made it possible to analyse the contribution of the noncovalent and covalent steps to the overall inhibitory activity. Compounds with similar intrinsic reactivities exhibit varying selectivities for iPS versus cPS owing to subtle differences in the binding modes that slightly affect Ki, the noncovalent affinity, and importantly alter kinact, the covalent reactivity of the bound compounds. A detailed understanding of the inhibitory mechanism of oxathiazolones is useful in designing iPS selective inhibitors with improved drug-like properties.

Dataset Information

Immunoproteasome ?5i-Selective Dipeptidomimetic Inhibitors.

Publications

Immunoproteasome β5i-Selective Dipeptidomimetic Inhibitors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets