Divalent sulfur (S) forms a chalcogen bond (Ch-bond) via its σ-holes and a hydrogen bond (H-bond) via its lone pairs. The relevance of these interactions and their interplay for protein structure and function is unclear. Based on the analyses of the crystal structures of small organic/organometallic molecules and proteins and their molecular electrostatic surface potential, we show that the reciprocity of the substituent-dependent strength of the σ-holes and lone pairs correlates with the formation of either Ch-bond or H-bond. In proteins, cystines preferentially form Ch-bonds, metal-chelated cysteines form H-bonds, while methionines form either of them with comparable frequencies. This has implications for the positioning of these residues and their role in protein structure and function. Computational analyses reveal that the S-mediated interactions stabilise protein secondary structures by mechanisms such as helix capping and protecting free β-sheet edges by negative design. The study highlights the importance of S-mediated Ch-bond and H-bond for understanding protein folding and function, the development of improved strategies for protein/peptide structure prediction and design and structure-based drug discovery.

Phase separation plays an important role in the formation of membraneless compartments within the cell and intrinsically disordered proteins with low-complexity sequences can drive this compartmentalisation. Various intermolecular forces, such as aromatic–aromatic and cation–aromatic interactions, promote phase separation. However, little is known about how the ability of proteins to phase separate under physiological conditions is encoded in their energy landscapes and this is the focus of the present investigation. Our results provide a first glimpse into how the energy landscapes of minimal peptides that contain $ \pi $–$ \pi $ and cation–$ \pi $ interactions differ from the peptides that lack amino acids with such interactions. The peaks in the heat capacity ($ {C}_V $) as a function of temperature report on alternative low-lying conformations that differ significantly in terms of their enthalpic and entropic contributions. The $ {C}_V $ analysis and subsequent quantification of frustration of the energy landscape suggest that the interactions that promote phase separation lead to features (peaks or inflection points) at low temperatures in $ {C}_V $. More features may occur for peptides containing residues with better phase separation propensity and the energy landscape is more frustrated for such peptides. Overall, this work links the features in the underlying single-molecule potential energy landscapes to their collective phase separation behaviour and identifies quantities ($ {C}_V $ and frustration metric) that can be utilised in soft material design.

Sweden tops gender equality rankings, but Swedish academia is still lacking women in top positions. To address gender inequality in its faculty, Chalmers University of Technology has invested 300 million SEK (30 million Euros) over 10 years in Gender initiative for Excellence (Genie). Genie aims to increase the university’s success and excellence via gender equality efforts. In this editorial, we want to share insights on explicit efforts during Genie’s first 2.5 years with the goal to inspire and advise other universities and researchers.

The human protein Rad51 is double-edged in cancer contexts: on one hand, preventing tumourigenesis by eliminating potentially carcinogenic DNA damage and, on the other, promoting tumours by introducing new mutations. Understanding mechanistic details of Rad51 in homologous recombination (HR) and repair could facilitate design of novel methods, including CRISPR, for Rad51-targeted cancer treatment. Despite extensive research, however, we do not yet understand the mechanism of HR in sufficient detail, partly due to complexity, a large number of Rad51 protein units being involved in the exchange of long DNA segments. Another reason for lack of understanding could be that current recognition models of DNA interactions focus only on hydrogen bond-directed base pair formation. A more complete model may need to include, for example, the kinetic effects of DNA base stacking and unstacking (‘longitudinal breathing’). These might explain how Rad51 can recognize sequence identity of DNA over several bases long stretches with high accuracy, despite the fact that a single base mismatch could be tolerated if we consider only the hydrogen bond energy. We here propose that certain specific hydrophobic effects, recently discovered destabilizing stacking of nucleobases, may play a central role in this context for the function of Rad51.

The SARS-CoV-2 virus has made the largest pandemic of the 21st century, with hundreds of millions of cases and tens of millions of fatalities. Scientists all around the world are racing to develop vaccines and new pharmaceuticals to overcome the pandemic and offer effective treatments for COVID-19 disease. Consequently, there is an essential need to better understand how the pathogenesis of SARS-CoV-2 is affected by viral mutations and to determine the conserved segments in the viral genome that can serve as stable targets for novel therapeutics. Here, we introduce a text-mining method to estimate the mutability of genomic segments directly from a reference (ancestral) whole genome sequence. The method relies on calculating the importance of genomic segments based on their spatial distribution and frequency over the whole genome. To validate our approach, we perform a large-scale analysis of the viral mutations in nearly 80,000 publicly available SARS-CoV-2 predecessor whole genome sequences and show that these results are highly correlated with the segments predicted by the statistical method used for keyword detection. Importantly, these correlations are found to hold at the codon and gene levels, as well as for gene coding regions. Using the text-mining method, we further identify codon sequences that are potential candidates for siRNA-based antiviral drugs. Significantly, one of the candidates identified in this work corresponds to the first seven codons of an epitope of the spike glycoprotein, which is the only SARS-CoV-2 immunogenic peptide without a match to a human protein.

Although the consequences of the crowded cell environments may affect protein folding, function and misfolding reactions, these processes are often studied in dilute solutions in vitro. We here used biophysical experiments to investigate the amyloid fibril formation process of the fish protein apo-β-parvalbumin in solvent conditions that mimic steric and solvation aspects of the in vivo milieu. Apo-β-parvalbumin is a folded protein that readily adopts an amyloid state via a nucleation–elongation mechanism. Aggregation experiments in the presence of macromolecular crowding agents (probing excluded volume, entropic effects) as well as small molecule osmolytes (probing solvation, enthalpic effects) revealed that both types of agents accelerate overall amyloid formation, but the elongation step was faster with macromolecular crowding agents but slower in the presence of osmolytes. The observations can be explained by the steric effects of excluded volume favoring assembled states and that amyloid nucleation does not involve monomer unfolding. In contrast, the solvation effects due to osmolyte presence promote nucleation but not elongation. Therefore, the amyloid-competent nuclei must be compact with less osmolytes excluded from the surface than either the folded monomers or amyloid fibers. We conclude that, in contrast to other amyloidogenic folded proteins, amyloid formation of apo-β-parvalbumin is accelerated by crowded cell-like conditions due to a nucleation process that does not involve large-scale protein unfolding.