The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.
Intrinsically disordered proteins (IDPs) adopt heterogeneous conformational ensembles in solution. The properties of the conformational ensemble are dependent upon the solution conditions, including the presence of ions, temperature, and crowding, and often directly impact biological function. Many in vitro investigations focus on the properties of IDPs under dilute conditions, rather than the crowded environment found in vivo. Due to their heterogeneous nature, the study of IDPs under crowded conditions is challenging both experimentally and computationally. Despite this, such studies are worth pursuing due to the insight gained into biologically relevant phenomena. Here, we study the highly charged IDP Histatin 5 under self-crowded conditions in low and high salt conditions. A combination of small-angle X-ray scattering and different simulation models, spanning a range of computational complexity and detail, is used. Most models are found to have limited application when compared to results from experiments. The best performing model is the highly coarse-grained, bead-necklace model. This model shows that Histatin 5 has a conserved radius of gyration and a decreasing flexibility with increasing protein concentration. Due to its computational efficiency, we propose that it is a suitable model to study crowded IDP solutions, despite its simplicity.
Intrinsically disordered proteins (IDP) are proteins that sample a heterogeneous ensemble of conformers in solution. An estimated 25–30% of all eukaryotic proteins belong to this class. In vivo , IDPs function under conditions that are highly crowded by other biological macromolecules. Previous research has highlighted that the presence of crowding agents can influence the conformational ensemble sampled by IDPs, resulting in either compaction or expansion. The effects of self-crowding of the disordered protein Histatin 5 has, in an earlier study, been found to have limited influence on the conformational ensemble. In this study, it is examined whether the short chain length of Histatin 5 can explain the limited effects of crowding observed, by introducing (Histatin 5) 2 , a tandem repeat of Histatin 5. By utilizing small-angle X-ray scattering, it is shown that the conformational ensemble is conserved at high protein concentrations, in resemblance with Histatin 5, although with a lowered protein concentration at which aggregation arises. Under dilute conditions, atomistic molecular dynamics and coarse-grained Monte Carlo simulations, as well as an established scaling law, predicted more extended conformations than indicated by experimental data, hence implying that (Histatin 5) 2 does not behave as a self-avoiding random walk.
Intrinsically disordered proteins (IDPs) are proteins that, in comparison with globular/structured proteins, lack a distinct tertiary structure. Here, we use the model IDP, Histatin 5, for studying its dynamical properties under self-crowding conditions with quasi-elastic neutron scattering in combination with full atomistic molecular dynamics (MD) simulations. The aim is to determine the effects of crowding on the center-of-mass diffusion as well as the internal diffusive behavior. The diffusion was found to decrease significantly, which we hypothesize can be attributed to some degree of aggregation at higher protein concentrations, (≥100 mg/mL), as indicated by recent small-angle X-ray scattering studies. Temperature effects are also considered and found to, largely, follow Stokes–Einstein behavior. Simple geometric considerations fail to accurately predict the rates of diffusion, while simulations show semiquantitative agreement with experiments, dependent on assumptions of the ratio between translational and rotational diffusion. A scaling law that previously was found to successfully describe the behavior of globular proteins was found to be inadequate for the IDP, Histatin 5. Analysis of the MD simulations show that the width of the distribution with respect to diffusion is not a simplistic mirroring of the distribution of radius of gyration, hence, displaying the particular features of IDPs that need to be accounted for.
Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.
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