The MAP kinase-interacting kinases (Mnk1 and Mnk2) are activated by ERK and are best known for phosphorylating the translation initiation factor eIF4E. Genetic knockout of the Mnks impaired the migration of embryonic fibroblasts both in two-dimensional wound-healing experiments and in three-dimensional migration assays. Furthermore, a novel and selective Mnk inhibitor, Mnk-I1, which potently blocks eIF4E phosphorylation, blocked the migration of fibroblasts and cancer cells, without exerting 'off-target' effects on other signalling pathways such as Erk. Mnk-I1 or genetic knockout of the Mnks decreased the expression of vimentin, a marker of mesenchymal cells, without affecting vimentin mRNA levels. Vimentin protein levels were much lower in Mnk1/2-knockout cells than in controls, although mRNA levels were similar. Our data suggest that the Mnks regulate the translation of the vimentin mRNA and the stability of the vimentin protein. Inhibition or genetic knockout of the Mnks increased the binding of eIF4E to the cytoplasmic FMRP-interacting protein 1 (CYFIP1), which binds the fragile-X mental retardation protein, FMRP, a translational repressor. Since FMRP binds mRNAs for proteins involved in metastasis, the Mnk-dependent release of CYFIP1 from eIF4E is expected to release the repression of translation of FMRP-bound mRNAs, potentially providing a molecular mechanism for the control of cell migration by the Mnks. As Mnk1/2 are not essential for viability, inhibition of the Mnks may be a useful approach to tackling cancer metastasis, a key process contributing to mortality in cancer patients.

As a great challenge in bioinformatics, enzyme function prediction is a significant step toward designing novel enzymes and diagnosing enzyme-related diseases. Existing studies mainly focus on the mono-functional enzyme function prediction. However, the number of multi-functional enzymes is growing rapidly, which requires novel computational methods to be developed. In this paper, following our previous work, DEEPre, which uses deep learning to annotate mono-functional enzyme's function, we propose a novel method, mlDEEPre, which is designed specifically for predicting the functionalities of multi-functional enzymes. By adopting a novel loss function, associated with the relationship between different labels, and a self-adapted label assigning threshold, mlDEEPre can accurately and efficiently perform multi-functional enzyme prediction. Extensive experiments also show that mlDEEPre can outperform the other methods in predicting whether an enzyme is a mono-functional or a multi-functional enzyme (mono-functional vs. multi-functional), as well as the main class prediction across different criteria. Furthermore, due to the flexibility of mlDEEPre and DEEPre, mlDEEPre can be incorporated into DEEPre seamlessly, which enables the updated DEEPre to handle both mono-functional and multi-functional predictions without human intervention.

The MAP kinase-interacting kinases (MNK1 and MNK2) are non-essential enzymes which are activated by MAP kinases. They are implicated in controlling protein synthesis. Here we show that mice in which the expression of either MNK1 or MNK2 has been knocked out (KO) are protected against adverse effects of high-fat feeding, and in distinct ways. High-fat diet (HFD)-fed MNK2-KO show less weight gain than wild-type animals, and improved glucose tolerance, better insulin sensitivity and markedly diminished adipose tissue inflammation. This suggests MNK2 plays a role in adipogenesis and/or lipogenesis and in macrophage biology. MNK1-KO/HFD mice show better glucose tolerance and insulin sensitivity, but gain weight and show similar adipose inflammation to WT animals. These data suggest MNK1 participates in mediating HFD-induced insulin resistance. Our findings reveal distinct roles for the MNKs in a novel area of disease biology, metabolic dysfunction, and suggests they are potential new targets for managing metabolic disease.

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