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Connexin hemichannels (HCs) expressed at the plasma membrane of mammalian cells are of paramount importance for intercellular communication. In physiological conditions, HCs can form gap junction (GJ) channels, providing a direct diffusive path between neighbouring cells. In addition, unpaired HCs provide conduits for the exchange of solutes between the cytoplasm and the extracellular milieu, including messenger molecules involved in paracrine signalling. The synergistic action of membrane potential and Ca 2+ ions controls the gating of the large and relatively unselective pore of connexin HCs. The four orders of magnitude difference in gating sensitivity to the extracellular ([Ca 2+ ] e ) and the cytosolic ([Ca 2+ ] c ) Ca 2+ concentrations suggests that at least two different Ca 2+ sensors may exist. While [Ca 2+ ] e acts as a spatial modulator of the HC opening, which is most likely dependent on the cell layer, compartment, and organ, [Ca 2+ ] c triggers HC opening and the release of extracellular bursts of messenger molecules. Such molecules include ATP, cAMP, glutamate, NAD + , glutathione, D-serine, and prostaglandins. Lost or abnormal HC regulation by Ca 2+ has been associated with several diseases, including deafness, keratitis ichthyosis, palmoplantar keratoderma, Charcot-Marie-Tooth neuropathy, oculodentodigital dysplasia, and congenital cataracts. The fact that both an increased and a decreased Ca 2+ sensitivity has been linked to pathological conditions suggests that Ca 2+ in healthy cells finely tunes the normal HC function. Overall, further investigation is needed to clarify the structural and chemical modifications of connexin HCs during [Ca 2+ ] e and [Ca 2+ ] c variations. A molecular model that accounts for changes in both Ca 2+ and the transmembrane voltage will undoubtedly enhance our interpretation of the experimental results and pave the way for developing therapeutic compounds targeting specific HC dysfunctions.

Constitutive activation of receptor tyrosine kinases (RTKs) via different mutations has a strong impact on the development of severe human disorders, including cancer. Here we propose a putative activation scenario of RTKs, whereby transmembrane (TM) mutations can also promote higher-order oligomerization of the receptors that leads to the subsequent ligand-free activation. We illustrate this scenario using a computational modelling framework comprising sequence-based structure prediction and all-atom 1 µs molecular dynamics (MD) simulations in a lipid membrane for a previously characterised oncogenic TM mutation V536E in platelet-derived growth factor receptor alpha (PDGFRA). We show that in the course of MD simulations the mutant TM tetramer retains stable and compact configuration strengthened by tight protein-protein interactions, while the wild type TM tetramer demonstrates looser packing and a tendency to dissociate. Moreover, the mutation affects the characteristic motions of mutated TM helical segments by introducing additional non-covalent crosslinks in the middle of the TM tetramer, which operate as mechanical hinges. This leads to dynamic decoupling of the C-termini from the rigidified N-terminal parts and facilitates more pronounced possible displacement between the C-termini of the mutant TM helical regions that can provide more freedom for mutual rearrangement of the kinase domains located downstream. Our results for the V536E mutation in the context of PDGFRA TM tetramer allow for the possibility that the effect of oncogenic TM mutations can go beyond alternating the structure and dynamics of TM dimeric states and might also promote the formation of higher-order oligomers directly contributing to ligand-independent signalling effectuated by PDGFRA and other RTKs., Competing Interests: None., (© 2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.)

NADH:ubiquinone oxidoreductase (respiratory complex I) plays a major role in cellular energy metabolism. Complex I deficiencies are the most common cause of mitochondrial dysfunction. Patients suffering from a variety of neurodegenerative diseases carry numerous mutations in the mitochondrially encoded subunits of the complex. The biochemical consequences of these mutations are largely unknown because these genes are difficult to access experimentally. Here, we use Escherichia coli as a model system to characterize the effect of a 7 bps inversion in mtND1 (m.3902-3908inv7) that results in a triple mutation. The triple mutant grew poorly but contained a normal amount of the stably assembled variant. The variant showed no enzymatic activity, which might contribute to the deleterious effect of the mutation in humans., (© 2022 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Members of the mitochondrial carrier family (SLC25) transport a variety of compounds across the inner membrane of mitochondria. These transport steps provide building blocks for the cell and link the pathways of the mitochondrial matrix and cytosol. An increasing number of diseases and pathologies has been associated with their dysfunction. In this review, the molecular basis of these diseases is explained based on our current understanding of their transport mechanism.

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein-protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein-protein interactions, or providing modeled structural data for drug discovery targeting protein-protein interactions., (© 2018 Elsevier Inc. All rights reserved.)

Loss-of-function mutations of the enzyme alpha-galactosidase A (GLA) causes Fabry disease (FD), that is a rare and potentially fatal disease. Identification of these pathological mutations by sequencing is important because it allows an early treatment of the disease. However, before taking any treatment decision, if the mutation identified is unknown, we first need to establish if it is pathological or not. General bioinformatic tools (PolyPhen-2, SIFT, Condel, etc.) can be used for this purpose, but their performance is still limited. Here we present a new tool, specifically derived for the assessment of GLA mutations. We first compared mutations of this enzyme known to cause FD with neutral sequence variants, using several structure and sequence properties. Then, we used these properties to develop a family of prediction methods adapted to different quality requirements. Trained and tested on a set of known Fabry mutations, our methods have a performance (Matthews correlation: 0.56-0.72) comparable or better than that of the more complex method, Polyphen-2 (Matthews correlation: 0.61), and better than those of SIFT (Matthews correl.: 0.54) and Condel (Matthews correl.: 0.51). This result is validated in an independent set of 65 pathological mutations, for which our method displayed the best success rate (91.0%, 87.7%, and 73.8%, for our method, PolyPhen-2 and SIFT, respectively). These data confirmed that our specific approach can effectively contribute to the identification of pathological mutations in GLA, and therefore enhance the use of sequence information in the identification of undiagnosed Fabry patients., (© 2014 Wiley Periodicals, Inc.)