Protein–protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide–protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide–protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide–protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.
1 August 2017 in Computational Biology and Chemistry
Lacking effective targeted therapies, triple-negative breast cancer (TNBCs) is highly aggressive with development of metastasis especially brain, and remains clinically challenging breast cancer subtype to treat. Despite the survival dependency on the proteasome pathway genes, FDA-approved proteasome inhibitors induced minimal clinical response in breast cancer patients due to weak proteasome inhibition. Here, we show that a potent proteasome inhibitor Marizomib (Mzb) inhibits multiple proteasome catalytic activities and induces a better anti-tumor response in TNBC cell lines and patient-derived xenografts alone and in combination with the standard-of-care chemotherapy. Mechanistically, Mzb inhibits oxidative phosphorylation (OXPHOS) via PGC-1α suppression in conjunction with proteasome inhibition in TNBC cells. Mzb reduces lung and brain metastases by reducing the number of circulating tumor cells and the expression of multiple genes involved in the epithelial-to-mesenchymal transition. Furthermore, Mzb-induced OXPHOS inhibition upregulates glycolysis to meet the energetic demands of TNBC cells and, hence, combined inhibition of glycolysis with Mzb exposure leads to a synergistic anti-cancer activity. Collectively, our data provide a strong rationale for a clinical evaluation of Mzb in primary and metastatic TNBC patients. One Sentence Summary: Marizomib inhibits primary tumor growth, and also reduces lung and brain metastases in pre-clinical models of triple-negative breast cancer.