The C-terminal self-binding helical peptide of human estrogen-related receptor γ can be druggably targeted by a novel class of rationally designed peptidic antagonists
Zilong Li, Yue Peng, Haiyang Ye, Yunyi Zhang, Peng Zhou
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引用次数: 0
Abstract
Orphan nuclear estrogen-related receptor γ (ERRγ) has been recognized as a potential therapeutic target for cancer, inflammation and metabolic disorder. The ERRγ contains a regulatory AF2 helical tail linked C-terminally to its ligand-binding domain (LBD), which is a self-binding peptide (SBP) and serves as molecular switch to dynamically regulate the receptor alternation between active and inactive states by binding to and unbinding from the AF2-binding site on ERRγ LBD surface, respectively. Traditional ERRγ modulators are all small-molecule chemical ligands that can be classified into agonists and inverse agonists in terms of their action mechanism; the agonists stabilize the AF2 in ABS site with an agonist conformation, while the inverse agonists lock the AF2 out of the site to largely abolish ERRγ transcriptional activity. Here, a class of ERRγ peptidic antagonists was described to compete with native AF2 for the ABS site, thus blocking the active state of AF2 binding to ERRγ LBD domain. Self-inhibitory peptide was derived from the SBP-covering AF2 region and we expected it can rebind potently to the ABS site by reducing its intrinsic disorder and entropy cost upon the rebinding. Hydrocarbon stapling was employed to do so, which employed an all-hydrocarbon bridge across the [i, i + 4]-anchor residue pair in the N-terminal, middle or C-terminal region of the self-inhibitory peptide. As might be expected, it is revealed that the stapled peptides are good binders of ERRγ LBD domain and can effectively compete with the native AF2 helical tail for ERRγ ABS site, which exhibit a basically similar binding mode with AF2 to the site and form diverse noncovalent interactions with the site, thus conferring stability and specificity to the domain–peptide complexes.
期刊介绍:
This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.