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Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins.

Intrinsically disordered proteins (IDPs) play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and forcefields. Nevertheless, differences in fine details emerge from varying forcefield/sampling method combinations. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which can be common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field/enhanced sampling method combinations for accurate structural and thermodynamic information in the study of general disordered proteins.

In this work we quantified the role of electrostatic interactions in the self-assembly of a model amphiphilic peptide (RADA 16-I) into fibrillar structures by a combination of size exclusion chromatography and molecular simulations. For the peptide under investigation, it is found that a net charge of +0.75 represents the ideal condition to promote the formation of regular amyloid fibrils. Lower net charges favor the formation of amorphous precipitates, while larger net charges destabilize the fibrillar aggregates and promote a reversible dissociation of monomers from the ends of the fibrils. By quantifying the dependence of the equilibrium constant of this reversible reaction on the pH value and the peptide net charge, we show that electrostatic interactions contribute largely to the free energy of fibril formation. The addition of both salt and a charged destabilizer (guanidinium hydrochloride) at moderate concentration (0.3-1 M) shifts the monomer-fibril equilibrium toward the fibrillar state. Whereas the first effect can be explained by charge screening of electrostatic repulsion only, the promotion of fibril formation in the presence of guanidinium hydrochloride is also attributed to modifications of the peptide conformation. The results of this work indicate that the global peptide net charge is a key property that correlates well with the fibril stability, although the peptide conformation and the surface charge distribution also contribute to the aggregation propensity.

The diffusion and aggregation of sodium fluorescein in aqueous solutions was investigated adopting density functional theory (DFT) and molecular dynamics (MD) simulations. First, DFT calculations in implicit water were used to determine minimum energy structure and atomic charges of the solute, which were then used as input for explicit water MD simulations. The self-diffusion coefficient of sodium fluorescein was calculated using the Einstein equation, computing the mean square displacement from 24 ns trajectories. The calculated diffusion coefficient, 0.42 · 10(-5) cm(2) s(-1), is in good agreement with literature experimental data. The simulations confirmed the tendency of fluorescein to form dimers. In order to achieve a deeper understanding of aggregation phenomena, the dimer geometry was investigated through DFT calculations both in vacuo and in implicit water using different functionals and solvation theories. The results showed that dimerization does not occur in vacuo, as charge repulsion dominates, and that the minimum energy dimer structure is symmetric and stabilized by edge-to-face π-π interactions. The interaction energy was computed both at the DFT level and through MD simulations using Umbrella Sampling. The free interaction energy calculated with the WHAM and Umbrella Integration protocol, -1.3 kcal/mol, is in good agreement with experimental data, while the value determined using DFT calculations is significantly smaller and depends largely from the chosen functional and the computational methodology used to determine the solute-solvent boundary surface.