FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries.

Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict .

Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles.

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson-Boltzmann theory to capture these phenomena.

Conformational ensembles of the human intrinsically disordered proteome.

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.

Floristic-Vegetational Features of Geranium argenteum, an Alpine-Apennine Species at Its Limit of Distribution in the Apennines.

We present a floristic-vegetational study on a plant community dominated by Geranium argenteum in the Sibillini Mountains (Central Apennines), at the southern limit of its distribution in the Apennines. It is a rare pioneer community located at an elevation of about 2100 m a.s.l. with northern exposure on the fractured rocky ridges and at the edges of the rocky detrital valleys on lithosol, with a prolonged presence of snowpack and gelifraction processes. The results of the phytosociological analysis allow us to propose the new Festuco italicae-Geranietum argentei association referred to as the Leontopodio nivalis-Elynion myosuroidis alliance (Carici rupestris-Kobresietea bellardii class). The comparison with the Alpine and the Northern Apennines phytocoenoses characterized by Geranium argenteum allows us to provide a new interpretation of the syntaxonomical framework concerning the Geranium argenteum communities within its Alpine-Apennine range in light of the new data presented in this paper. The new Festuco italicae-Geranietum argentei association represents a further contribution to the knowledge of the relict alpine vegetation of the Leontopodio nivalis-Elynion myosuroidis alliance in the Sibillini Mountains and thus in the Central Apennines. Finally, habitat monitoring will be essential for assessing the impacts of climate change on this fragile and narrowly restricted plant community.

Design of intrinsically disordered protein variants with diverse structural properties.

Intrinsically disordered proteins (IDPs) perform a wide range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Designing IDPs with specific structural or functional properties has, however, been difficult, in part because determining accurate conformational ensembles of IDPs generally requires a combination of computational modelling and experiments. Motivated by recent advancements in efficient physics-based models for simulations of IDPs, we have developed a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs with different levels of compaction and that vary more than 100 fold in their propensity to undergo phase separation, even while keeping a fixed amino acid composition. We experimentally tested designs of variants of the low-complexity domain of hnRNPA1 and find high accuracy in our computational predictions, both in terms of single-chain compaction and propensity to undergo phase separation. We analyze the sequence features that determine changes in compaction and propensity to phase separate and find an overall good agreement with previous findings for naturally occurring sequences. Our general, physics-based method enables the design of disordered sequences with specified conformational properties. Our algorithm thus expands the toolbox for protein design to include also the most flexible proteins and will enable the design of proteins whose functions exploit the many properties afforded by protein disorder.

The effect of linker conformation on performance and stability of a two-domain lytic polysaccharide monooxygenase.

A considerable number of lytic polysaccharide monooxygenases (LPMOs) and other carbohydrate-active enzymes are modular, with catalytic domains being tethered to additional domains, such as carbohydrate-binding modules, by flexible linkers. While such linkers may affect the structure, function, and stability of the enzyme, their roles remain largely enigmatic, as do the reasons for natural variation in length and sequence. Here, we have explored linker functionality using the two-domain cellulose-active ScLPMO10C from Streptomyces coelicolor as a model system. In addition to investigating the WT enzyme, we engineered three linker variants to address the impact of both length and sequence and characterized these using small-angle X-ray scattering, NMR, molecular dynamics simulations, and functional assays. The resulting data revealed that, in the case of ScLPMO10C, linker length is the main determinant of linker conformation and enzyme performance. Both the WT and a serine-rich variant, which have the same linker length, demonstrated better performance compared with those with either a shorter linker or a longer linker. A highlight of our findings was the substantial thermostability observed in the serine-rich variant. Importantly, the linker affects thermal unfolding behavior and enzyme stability. In particular, unfolding studies show that the two domains unfold independently when mixed, whereas the full-length enzyme shows one cooperative unfolding transition, meaning that the impact of linkers in biomass-processing enzymes is more complex than mere structural tethering.

FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries.

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict.

Clonality drives structural patterns and shapes the community assemblage of the Mediterranean Fagus sylvatica subalpine belt.

Past anthropogenic disturbances lowered the altitudinal distribution of the Mediterranean Fagus sylvatica forests below 2,000 m a.s.l. Accordingly, our current understanding of the southern distribution range of F. sylvatica forests is restricted to managed stands below this elevation, neglecting relic forests growing above. This study has shed light on the structure and species assemblage of an unmanaged relict subalpine F. sylvatica stand growing within the core of its southernmost glacial refugia and at its highest species range elevation limit (2,140 m a.s.l.) in southern Apennines (Italy). Here, tree biometric attributes and understory species abundances were assessed in eight permanent plots systematically positioned from 1,650 to 2,130 m a.s.l. In the subalpine belt, F. sylvatica had formed a dense clonal stem population that was layered downward on the steepest slopes. The density and spatial aggregation of the stems were increased, while their stature and crown size were decreased. Above 2,000 m, changes in tree growth patterns, from upright single-stemmed to procumbent multi-stemmed, and canopy layer architecture, with crowns packed and closer to the floor, were allowed for the persistence of understory herbaceous species of biogeographic interest. Clonal layering represents an adaptive regeneration strategy for the subalpine belt environmental constraints not previously recognized in managed Mediterranean F. sylvatica forests. The clonal structure and unique species assemblage of this relic forest highlight the value of its inclusion in the priority areas networks, representing a long-term management strategy of emblematic glacial and microclimatic refugia.

Improving Martini 3 for Disordered and Multidomain Proteins.

Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small-angle X-ray scattering (SAXS) data and that increasing the strength of protein-water interactions favors more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multidomain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems, our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range.

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties.

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles.

Owing to their plasticity, intrinsically disordered and multidomain proteins require descriptions based on multiple conformations, thus calling for techniques and analysis tools that are capable of dealing with conformational ensembles rather than a single protein structure. Here, we introduce DEER-PREdict, a software program to predict Double Electron-Electron Resonance distance distributions as well as Paramagnetic Relaxation Enhancement rates from ensembles of protein conformations. DEER-PREdict uses an established rotamer library approach to describe the paramagnetic probes which are bound covalently to the protein.DEER-PREdict has been designed to operate efficiently on large conformational ensembles, such as those generated by molecular dynamics simulation, to facilitate the validation or refinement of molecular models as well as the interpretation of experimental data. The performance and accuracy of the software is demonstrated with experimentally characterized protein systems: HIV-1 protease, T4 Lysozyme and Acyl-CoA-binding protein. DEER-PREdict is open source (GPLv3) and available at github.com/KULL-Centre/DEERpredict and as a Python PyPI package pypi.org/project/DEERPREdict.

The extracellular juncture domains in the intimin passenger adopt a constitutively extended conformation inducing restraints to its sphere of action.

Enterohemorrhagic and enteropathogenic Escherichia coli are among the most important food-borne pathogens, posing a global health threat. The virulence factor intimin is essential for the attachment of pathogenic E. coli to the intestinal host cell. Intimin consists of four extracellular bacterial immunoglobulin-like (Big) domains, D00-D2, extending into the fifth lectin subdomain (D3) that binds to the Tir-receptor on the host cell. Here, we present the crystal structures of the elusive D00-D0 domains at 1.5 Å and D0-D1 at 1.8 Å resolution, which confirms that the passenger of intimin has five distinct domains. We describe that D00-D0 exhibits a higher degree of rigidity and D00 likely functions as a juncture domain at the outer membrane-extracellular medium interface. We conclude that D00 is a unique Big domain with a specific topology likely found in a broad range of other inverse autotransporters. The accumulated data allows us to model the complete passenger of intimin and propose functionality to the Big domains, D00-D0-D1, extending directly from the membrane.

Ailanthus altissima Forests Determine a Shift in Herbaceous Layer Richness: A Paired Comparison with Hardwood Native Forests in Sub-Mediterranean Europe.

Ailanthus altissima is an invasive alien species (IAS) present throughout Europe and included in the list of alien species of Union concern. In sub-Mediterranean areas of central Italy, there is a lack of knowledge about this invasive species and its interactions with the native forest ecosystems. We aim to find what are the main differences in vegetation structure and floristic diversity between A. altissima forests and native forests through the assessment of the principal ecological parameters that differ between the forest types. We performed 38 phytosociological relevés and sampling of ecological parameters in A. altissima forest communities and neighboring native forests. We analyzed how species richness, diversity, life forms, life strategies, structural characteristics, and ecological parameters changed in A. altissima forests compared with native ones. We found that in A. altissima forests, there is a shift in herbaceous layer richness, with a higher presence of annual ruderal herbs and the absence of herbaceous species linked to the forest environment. The ecological parameters that diverge from the native forests were total nitrogen, total carbon, and C/N ratio. A. altissima forest communities could threaten the biodiversity of the native forest ecosystems in the sub-Mediterranean landscape, favoring ruderal species and inhibiting the presence of typical forest species.

Structure and dynamics of a nanodisc by integrating NMR, SAXS and SANS experiments with molecular dynamics simulations.

Nanodiscs are membrane mimetics that consist of a protein belt surrounding a lipid bilayer, and are broadly used for characterization of membrane proteins. Here, we investigate the structure, dynamics and biophysical properties of two small nanodiscs, MSP1D1ΔH5 and ΔH4H5. We combine our SAXS and SANS experiments with molecular dynamics simulations and previously obtained NMR and EPR data to derive and validate a conformational ensemble that represents the structure and dynamics of the nanodisc. We find that it displays conformational heterogeneity with various elliptical shapes, and with substantial differences in lipid ordering in the centre and rim of the discs. Together, our results reconcile previous apparently conflicting observations about the shape of nanodiscs, and pave the way for future integrative studies of larger complex systems such as membrane proteins embedded in nanodiscs.

One ring to rule them all: an ecosystem engineer fungus fosters plant and microbial diversity in a Mediterranean grassland.

Species coexistence in grasslands is regulated by several environmental factors and interactions with the soil microbial community. Here, the development of the Basidiomycetes fungus Agaricus arvensis, forming fairy rings, in a species-rich Mediterranean grassland, is described. Effects of the mycelial front on plants, fungi and bacteria were assessed by vegetation survey and next generation sequencing approaches. Our results showed a fungal-dependent shift in the community structure operated by a wave-like spread of fairy rings that decreased plant, fungal and bacterial diversity, indicating a detrimental effect of fairy rings on most species. The fairy rings induced successional processes in plants that enhanced the replacement of a community dominated by perennial plants with short-living and fast-growing plant species. In parallel, fungal and bacterial communities showed evident differences in species composition with several taxa associated within distinct sampling zone across the fairy rings. Notably, bacteria belonging to the Burkholderia genus and fungi of the genus Trichoderma increased in response to the advancing mycelium of A. arvensis. The profound changes in community composition and the overall increase in taxa diversity at ecosystemic scale suggest that fairy ring-forming fungi may act as ecosystem engineer species in Mediterranean grasslands.

Arginine "Magic": Guanidinium Like-Charge Ion Pairing from Aqueous Salts to Cell Penetrating Peptides.

It is a textbook knowledge that charges of the same polarity repel each other. For two monovalent ions in the gas phase at a close contact this repulsive interaction amounts to hundreds of kilojoules per mole. In aqueous solutions, however, this Coulomb repulsion is strongly attenuated by a factor equal to the dielectric constant of the medium. The residual repulsion, which now amounts only to units of kilojoules per mole, may be in principle offset by attractive interactions. Probably the smallest cationic pair, where a combination of dispersion and cavitation forces overwhelms the Coulomb repulsion, consists of two guanidinium ions in water. Indeed, by a combination of molecular dynamics with electronic structure calculations and electrophoretic, as well as spectroscopic, experiments, we have demonstrated that aqueous guanidinium cations form (weakly) thermodynamically stable like-charge ion pairs. The importance of pairing of guanidinium cations in aqueous solutions goes beyond a mere physical curiosity, since it has significant biochemical implications. Guanidinium chloride is known to be an efficient and flexible protein denaturant. This is due to the ability of the orientationally amphiphilic guanidinium cations to disrupt various secondary structural motifs of proteins by pairing promiscuously with both hydrophobic and hydrophilic groups, including guanidinium-containing side chains of arginines. The fact that the cationic guanidinium moiety forms the dominant part of the arginine side chain implies that the like-charge ion pairing may also play a role for interactions between peptides and proteins. Indeed, arginine-arginine pairing has been frequently found in structural protein databases. In particular, when strengthened by a presence of negatively charged glutamate, aspartate, or C-terminal carboxylic groups, this binding motif helps to stabilize peptide or protein dimers and is also found in or near active sites of several enzymes. The like-charge pairing of the guanidinium side-chain groups may also hold the key to the understanding of the arginine "magic", that is, the extraordinary ability of arginine-rich polypeptides to passively penetrate across cellular membranes. Unlike polylysines, which are also highly cationic but lack the ease in crossing membranes, polyarginines do not exhibit mutual repulsion. Instead, they accumulate at the membrane, weaken it, and might eventually cross in a concerted, "train-like" manner. This behavior of arginine-rich cell penetrating peptides can be exploited when devising smart strategies how to deliver in a targeted way molecular cargos into the cell.

Specific Cation Effects on SCN- in Bulk Solution and at the Air-Water Interface.

The large and sparsely hydrated thiocyanate anion, SCN-, plays a prominent role in the study of specific ion effects in biological, colloid, and atmospheric chemistry due to its extreme position in the Hofmeister series. Using atomistic modeling of aqueous SCN- solutions, we provide novel insight at the molecular scale into the experimentally observed differences in ion pairing, clustering, reorientation dynamics, mutual diffusion, and solubility between the sodium, Na+, and the potassium, K+, salt. Compared to KSCN, NaSCN has a less pronounced tendency to ion pairing; nevertheless, at high salt concentrations, we observe a strong attraction between Na+ cations and the nitrogen end of SCN-, resulting in larger and more closely packed ion clusters. To accurately model aqueous SCN- solutions in computer simulations, we develop a thermodynamically consistent force field rooted in quantum-chemical calculations and refined using the Kirkwood-Buff theory. The force field is compatible with the extended simple point charge and three-point optimal point charge classical water models and reproduces experimental activity derivatives and air-water surface tension for a wide range of salt concentrations.

Aggregate Size Dependence of Amyloid Adsorption onto Charged Interfaces.

Amyloid aggregates are associated with a range of human neurodegenerative disorders, and it has been shown that neurotoxicity is dependent on aggregate size. Combining molecular simulation with analytical theory, a predictive model is proposed for the adsorption of amyloid aggregates onto oppositely charged surfaces, where the interaction is governed by an interplay between electrostatic attraction and entropic repulsion. Predictions are experimentally validated against quartz crystal microbalance-dissipation experiments of amyloid beta peptides and fragmented fibrils in the presence of a supported lipid bilayer. Assuming amyloids as rigid, elongated particles, we observe nonmonotonic trends for the extent of adsorption with respect to aggregate size and preferential adsorption of smaller aggregates over larger ones. Our findings describe a general phenomenon with implications for stiff polyions and rodlike particles that are electrostatically attracted to a surface.