One of the most important lessons we have learned from sequencing the human genome is that not all proteins have a 3D structure. In fact, a large part of the human proteome is made up of intrinsically disordered proteins (IDPs) which can adopt multiple structures, and therefore, multiple functions, depending on the ligands with which they interact. Under these conditions, one can wonder about the value of algorithms developed for predicting the structure of proteins, in particular AlphaFold, an AI which claims to have solved the problem of protein structure. In a recent study, we highlighted a particular weakness of AlphaFold for membrane proteins. Based on this observation, we have proposed a paradigm, referred to as “Epigenetic Dimension of Protein Structure” (EDPS), which takes into account all environmental parameters that control the structure of a protein beyond the amino acid sequence (hence “epigenetic”). In this new study, we compare the reliability of the AlphaFold and Robetta algorithms’ predictions for a new set of membrane proteins involved in human pathologies. We found that Robetta was generally more accurate than AlphaFold for ascribing a membrane-compatible topology. Raft lipids (e.g., gangliosides), which control the structural dynamics of membrane protein structure through chaperone effects, were identified as major actors of the EDPS paradigm. We conclude that the epigenetic dimension of a protein structure is an intrinsic weakness of AI-based protein structure prediction, especially AlphaFold, which warrants further development.

We analyzed the epitope evolution of the spike protein in 1,860,489 SARS-CoV-2 genomes. The structural dynamics of these epitopes was determined by molecular modeling approaches. The D614G mutation, selected in the first months of the pandemic, is still present in currently circulating SARS-CoV-2 strains. This mutation facilitates the conformational change leading to the demasking of the ACE2 binding domain. D614G also abrogated the binding of facilitating antibodies to a linear epitope common to SARS-CoV-1 and SARS-CoV-2. The main neutralizing epitope of the N-terminal domain (NTD) of the spike protein showed extensive structural variability in SARS-CoV-2 variants, especially Delta and Omicron. This epitope is located on the flat surface of the NTD, a large electropositive area which binds to electronegatively charged lipid rafts of host cells. A facilitating epitope located on the lower part of the NTD appeared to be highly conserved among most SARS-CoV-2 variants, which may represent a risk of antibody-dependent enhancement (ADE). Overall, this retrospective analysis revealed an early divergence between conserved (facilitating) and variable (neutralizing) epitopes of the spike protein. These data aid in the designing of new antiviral strategies that could help to control COVID-19 infection by mimicking neutralizing antibodies or by blocking facilitating antibodies.

Serotonin is distinct among synaptic neurotransmitters because it is amphipathic and released from synaptic vesicles at concentrations superior to its water solubility limit (270 mM in synaptic vesicles for a solubility limit of 110 mM). Hence, serotonin is mostly aggregated in the synaptic cleft, due to extensive aromatic stacking. This important characteristic has received scant attention, as most representations of the serotonergic synapse take as warranted that serotonin molecules are present as monomers after synaptic vesicle exocytosis. Using a combination of in silico and physicochemical approaches and a new experimental device mimicking synaptic conditions, we show that serotonin aggregates are efficiently dissolved by gangliosides (especially GM1) present in postsynaptic membranes. This initial interaction, driven by electrostatic forces, attracts serotonin from insoluble aggregates and resolves micelles into monomers. Serotonin also interacts with cholesterol via a set of CH-π and van der Waals interactions. Thus, gangliosides and cholesterol act together as a functional serotonin-collecting funnel on brain cell membranes. Based on this unique mode of interaction with postsynaptic membranes, we propose a new model of serotonergic transmission that takes into account the post-exocytosis solubilizing effect of gangliosides and cholesterol on serotonin aggregates.