Atlantic cod is composed of multiple migratory and stationary populations widely distributed in the North Atlantic Ocean. The Northeast Arctic cod (NEAC) population in the Barents Sea undertakes annual spawning migrations to the northern Norwegian coast. Although spawning occurs sympatrically with the stationary Norwegian coastal cod (NCC), phenotypic and genetic differences between NEAC and NCC are maintained. In this study, we resolve the enigma by revealing the mechanisms underlying these differences. Extended linkage disequilibrium (LD) and population divergence were demonstrated in a 17.4-Mb region on linkage group 1 (LG1) based on genotypes of 494 SNPs from 192 parents of farmed families of NEAC, NCC or NEACxNCC crosses. Linkage analyses revealed two adjacent inversions within this region that repress meiotic recombination in NEACxNCC crosses. We identified a NEAC-specific haplotype consisting of 186 SNPs that was fixed in NEAC sampled from the Barents Sea, but segregating under Hardy-Weinberg equilibrium in eight NCC stocks. Comparative genomic analyses determine the NEAC configuration of the inversions to be the derived state and date it to ~1.6-2.0 Mya. The haplotype block harbours 763 genes, including candidates regulating swim bladder pressure, haem synthesis and skeletal muscle organization conferring adaptation to long-distance migrations and vertical movements down to large depths. Our results suggest that the migratory ecotype experiences strong directional selection for the two adjacent inversions on LG1. Despite interbreeding between NEAC and NCC, the inversions are maintaining genetic differentiation, and we hypothesize the co-occurrence of multiple adaptive alleles forming a 'supergene' in the NEAC population.

The NIMA (never in mitosis, gene A)-related kinase-6 (NEK6), which is implicated in cell cycle control and plays significant roles in tumorigenesis, is an attractive target for the development of novel anti-cancer drugs. Here we describe the discovery of a potent ATP site-directed inhibitor of NEK6 identified by virtual screening, adopting both structure- and ligand-based techniques. Using a homology-built model of NEK6 as well as the pharmacophoric features of known NEK6 inhibitors we identified novel binding scaffolds. Twenty-five compounds from the top ranking hits were subjected to in vitro kinase assays. The best compound, i.e. compound 8 ((5Z)-2-hydroxy-4-methyl-6-oxo-5-[(5-phenylfuran-2-yl)methylidene]-5,6-dihydropyridine-3-carbonitrile), was able to inhibit NEK6 with low micromolar IC50 value, also displaying antiproliferative activity against a panel of human cancer cell lines. Our results suggest that the identified inhibitor can be used as lead candidate for the development of novel anti-cancer agents, thus opening the possibility of new therapeutic strategies.

The spike glycoprotein (S) of the SARS‐CoV‐2 virus surface plays a key role in receptor binding and virus entry. The S protein uses the angiotensin converting enzyme (ACE2) for entry into the host cell and binding to ACE2 occurs at the receptor binding domain (RBD) of the S protein. Therefore, the protein‐protein interactions (PPIs) between the SARS‐CoV‐2 RBD and human ACE2, could be attractive therapeutic targets for drug discovery approaches designed to inhibit the entry of SARS‐CoV‐2 into the host cells. Herein, with the support of machine learning approaches, we report structure‐based virtual screening as an effective strategy to discover PPIs inhibitors from ZINC database. The proposed computational protocol led to the identification of a promising scaffold which was selected for subsequent binding mode analysis and that can represent a useful starting point for the development of new treatments of the SARS‐CoV‐2 infection.

The acetylglucosaminyltransferase-like protein LARGE1 is an enzyme that is responsible for the final steps of the post-translational modifications of dystroglycan (DG), a membrane receptor that links the cytoskeleton with the extracellular matrix in the skeletal muscle and in a variety of other tissues. LARGE1 acts by adding the repeating disaccharide unit [-3Xyl-α1,3GlcAβ1-] to the extracellular portion of the DG complex (α-DG); defects in the LARGE1 gene result in an aberrant glycosylation of α-DG and consequent impairment of its binding to laminin, eventually affecting the connection between the cell and the extracellular environment. In the skeletal muscle, this leads to degeneration of the muscular tissue and muscular dystrophy. So far, a few missense mutations have been identified within the LARGE1 protein and linked to congenital muscular dystrophy, and because no structural information is available on this enzyme, our understanding of the molecular mechanisms underlying these pathologies is still very limited. Here, we generated a 3D model structure of the two catalytic domains of LARGE1, combining different molecular modeling approaches. Furthermore, by using molecular dynamics simulations, we analyzed the effect on the structure and stability of the first catalytic domain of the pathological missense mutation S331F that gives rise to a severe form of muscle–eye–brain disease.