Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

ORPs are lipid-transport proteins belonging to the oxysterol-binding protein family. They facilitate the transfer of lipids between different intracellular membranes, such as the ER and plasma membrane. We have solved the crystal structure of the ORP8 lipid transport domain (ORD8). The ORD8 exhibited a β-barrel fold composed of anti-parallel β-strands, with three α-helices replacing β-strands on one side. This mixed alpha–beta structure was consistent with previously solved structures of ORP2 and ORP3. A large cavity (≈1860 ų) within the barrel was identified as the lipid-binding site. Although we were not able to obtain a lipid-bound structure, we used computer simulations based on our crystal structure to dock PS and PI4P molecules into the putative lipid-binding site of the ORD8. Comparative experiments between the short ORD8^ΔLid (used for crystallography) and the full-length ORD8 (lid containing) revealed the lid’s importance for stable lipid binding. Fluorescence assays revealed different transport efficiencies for PS and PI4P, with the lid slowing down transport and stabilizing cargo. Coarse-grained simulations highlighted surface-exposed regions and hydrophobic interactions facilitating lipid bilayer insertion. These findings enhance our comprehension of ORD8, its structure, and lipid transport mechanisms, as well as provide a structural basis for the design of potential inhibitors.

Galectin-3 is a protein involved in many intra- and extra-cellular processes. It has been identified as a diagnostic or prognostic biomarker for certain types of heart disease, kidney disease and cancer. Galectin-3 comprises a carbohydrate recognition domain (CRD) and an N-terminal domain (NTD), which is unstructured and contains eight collagen-like Pro-Gly-rich tandem repeats. While the structure of the CRD has been solved using protein crystallography, current knowledge about conformations of full-length galectin-3 is limited. To fill in this knowledge gap, we performed molecular dynamics (MD) simulations of full-length galectin-3. We systematically re-scaled the solute–solvent interactions in the Martini 3 force field to obtain the best possible agreement between available data from SAXS experiments and the ensemble of conformations generated in the MD simulations. The simulation conformations were found to be very diverse, as reflected, e.g., by (i) large fluctuations in the radius of gyration, ranging from about 2 to 5 nm, and (ii) multiple transient contacts made by amino acid residues in the NTD. Consistent with evidence from NMR experiments, contacts between the CRD and NTD were observed to not involve the carbohydrate-binding site on the CRD surface. Contacts within the NTD were found to be made most frequently by aromatic residues. Formation of fuzzy complexes with unspecific stoichiometry was observed to be mediated mostly by the NTD. Taken together, we offer a detailed picture of the conformational ensemble of full-length galectin-3, which will be important for explaining the biological functions of this protein at the molecular level.

Many intrinsically disordered proteins (IDPs) are known to undergo liquid–liquid phase separation (LLPS), which is a physical process that drives the formation of biomolecular condensates and membraneless organelles in biological cells. Molecular dynamics (MD) simulations provide valuable tools to explore both the molecular mechanisms of LLPS and the physical properties of biomolecular condensates. However, a direct comparison of MD simulation results with phase diagrams obtained experimentally is normally prevented not only by the high computational costs of simulating large biomacromolecular systems on sufficient timescales but also by conceptual challenges. Specifically, there currently seems to be no standard or unambiguous method of defining and determining volumes occupied by coexisting phases at the nanoscale, with typically no more than a few hundred biomacromolecules in the simulation box. The goal of this work is to fill in this gap in the methodology. Focusing on $\alpha$-synuclein as a model IDP, we test and compare three methods for determining the molecular density of protein nanodroplets, or clusters, generated in MD simulations or using other molecular modeling approaches. Two of the methods are based on approximating nanodroplets with homogeneous spheres and ellipsoids, respectively. The third method, which is expected to yield the most physically accurate results, is based on the SPACEBALL algorithm, with optimized, cluster-specific radii for volume probes. Our results contribute to the construction of accurate phase diagrams on the basis of MD simulations of IDP systems.