Metastatic tumour recurrence due to failed treatments remains a major challenge of breast cancer clinical management. Here we report that interleukin-1 receptor-associated kinase 1 (IRAK1) is overexpressed in a subset of breast cancers, in particular triple-negative breast cancer (TNBC), where it acts to drive aggressive growth, metastasis and acquired resistance to paclitaxel treatment. We show that IRAK1 overexpression confers TNBC growth advantage through NF-κB-related cytokine secretion and metastatic TNBC cells exhibit gain of IRAK1 dependency, resulting in high susceptibility to genetic and pharmacologic inhibition of IRAK1. Importantly, paclitaxel treatment induces strong IRAK1 phosphorylation, an increase in inflammatory cytokine expression, enrichment of cancer stem cells and acquired resistance to paclitaxel treatment. Pharmacologic inhibition of IRAK1 is able to reverse paclitaxel resistance by triggering massive apoptosis at least in part through inhibiting p38-MCL1 pro-survival pathway. Our study thus demonstrates IRAK1 as a promising therapeutic target for TNBC metastasis and paclitaxel resistance.
Dual inhibition of serotonin and norepinephrine transporters (hSERT and hNET) gives greatly improved efficacy and tolerability for treating major depressive disorder (MDD) compared with selective reuptake inhibitors. Pioneer studies provided valuable information on structure, function, and pharmacology of drugs targeting both hSERT and hNET (serotonin-norepinephrine reuptake inhibitors, SNRIs), and the differential binding mechanism between SNRIs and selective inhibitors of 5-HT (SSRIs) or NE (sNRIs) to their corresponding targets was expected to be able to facilitate the discovery of a privileged drug-like scaffold with improved efficacy. However, the dual-target mechanism of SNRIs was still elusive, and the binding mode distinguishing SNRIs from SSRIs and sNRIs was also unclear. Herein, an integrated computational strategy was adopted to discover the binding mode shared by all FDA approved SNRIs. The comparative analysis of binding free energy at the per-residue level discovered that residues Phe335, Leu337, Gly338, and Val343 located at the transmembrane domain 6 (TM6) of hSERT (the corresponding residues Phe317, Leu319, Gly320, and Val325 in hNET) were the determinants accounting for SNRIs' dual-acting inhibition, while residues lining TM3 and 8 (Ile172, Ser438, Thr439, and Leu443 in hSERT; Val148, Ser419, Ser420, and Met424 in hNET) contributed less to the binding of SNRIs than that of SSRIs and sNRIs. Based on these results, the distances between an SNRI's centroid and the centroids of its two aromatic rings (measuring the depth of rings stretching into hydrophobic pockets) were discovered as the key to the SNRIs' dual-targeting mechanism. This finding revealed SNRIs' binding mechanism at an atomistic level, which could be further utilized as structural blueprints for the rational design of privileged drug-like scaffolds treating MDD.
Amitifadine, the only drug ever clinically tested in Phase 3 for treating depression, is a triple reuptake inhibitor (TRI) that simultaneously interacts with human monoamine transporters (MATs) including hSERT, hNET and hDAT. This novel multi-target strategy improves drug efficacy and reduces the toxic side effects of drugs. However, the binding modes accounting for amitifadine's polypharmacological mode of action are still elusive, and extensive exploration of the amitifadine-target interactions between amitifadine and MATs is urgently needed. In this study, a total of 0.63 μs molecular dynamics (MD) simulations with an explicit solvent as well as endpoint binding free energy (BFE) calculation were carried out. MD simulation results identified a shared binding mode involving eleven key residues at the S1 site of MATs for the binding of amitifadine, and the results of the BFE calculations were in good agreement with experimental reports. Moreover, by analyzing the per-residue energy contribution variation at the S1 site of three MATs and additional cross-mutagenesis simulations, the variation in the inhibition ratio of amitifadine between hSERT and two other MATs was discovered to mainly come from non-conserved residues (Y95, I172 and T439 in hNET and Y95, I172, A169 and T439 in hDAT). As the rational inhibition ratio of multi-target drugs among various therapeutic targets was found to be the key to their safety and tolerance, the findings of this study may further facilitate the rational design of more potent but less toxic multi-target antidepressant drugs.
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