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Accurate modeling of protein-water interactions in molecular dynamics (MD) simulations is important for understanding the molecular basis of protein function. Data from x-ray crystallography can be useful in assessing the accuracy of MD simulations, in particular, the locations of crystallographic water sites (CWS) coordinated by the protein. Such a comparison requires special methodological considerations that take into account the dynamic nature of proteins. However, existing methods for analyzing CWS in MD simulations rely on global alignment of the protein onto the crystal structure, which introduces substantial errors in the case of significant structural deviations. Here, we propose a method called local alignment for water sites (LAWS), which is based on multilateration-an algorithm widely used in GPS tracking. LAWS considers the contacts formed by CWS and protein atoms in the crystal structure and uses these interaction distances to track CWS in a simulation. We apply our method to simulations of a protein crystal and to simulations of the same protein in solution. Compared with existing methods, LAWS defines CWS characterized by more prominent water density peaks and a less-perturbed protein environment. In the crystal, we find that all high-confidence crystallographic waters are preserved. Using LAWS, we demonstrate the importance of crystal packing for the stability of CWS in the unit cell. Simulations of the protein in solution and in the crystal share a common set of preserved CWS that are located in pockets and coordinated by residues of the same domain, which suggests that the LAWS algorithm will also be useful in studying ordered waters and water networks in general.

Elastin endows tissues such as skin, arterial walls, lung alveoli, and the uterus with extensibility and elasticity. Elastin and elastin-like peptides self-aggregate via a liquid-liquid phase separation process. Although elastin has been the object of biophysical investigation for over eighty years, the structural basis for the self-assembly and the mechanical properties of elastin remains controversial. Elastin is structurally heterogeneous and must be described by an ensemble of structures. As an essential step towards elucidating the structural ensemble of elastin, we combine molecular dynamics simulations and nuclear magnetic resonance (NMR) spectroscopy to study an elastin-like peptide modelled after the sequence of alternating hydrophobic and cross-linking domains of elastin. We perform extensive all-atom molecular dynamics simulations totalling hundreds of microseconds and obtain detailed structural and dynamic data by NMR on the same peptide sequences under the same thermodynamic conditions. Simulation and NMR results are in excellent agreement and show that although the peptide is highly disordered, it possesses a significant propensity for secondary structure. The cross-linking domains are characterized by fluctuating helical structure, whereas the hydrophobic domains adopt fluctuating hydrogen-bonded turns. The latter secondary structure elements are sparse, local, and transient. As a result, the individual domains do not form extensive interactions; they are collapsed but not compact, and they remain disordered and hydrated despite their predominantly hydrophobic character. Taken together, these findings resolve long-standing discrepancies between previous models of the structure and function of elastin. Importantly, these results also afford unprecedented insight into the physical and structural basis for the liquid-liquid phase separation of disordered proteins.

Elastin is the protein responsible for the elastic recoil of skin, arteries, and lungs. Elastin exhibits high resilience and remarkable durability; it also undergoes phase separation and self-organization into a fibrillar structure upon increasing temperature. These properties make elastin ideal for biomaterials applications. In order to investigate the molecular basis for elastin self-aggregation, we performed extensive atomistic molecular dynamics simulations of a monomer and an aggregate of eight elastin-like peptides in explicit water. These simulations required a total time of nearly 0.5 ms, and utilized simulated tempering distributed replica sampling, a method that relies on a random walk in temperature to enhance conformational sampling. We obtain a configurational ensemble of the elastin-like aggregate that resembles a “polymer melt” in which the chains are completely entangled with each other, but retain significant hydration and do not form a water-excluding hydrophobic core. Within the aggregate, the chains act to “solvate” each other: intramolecular interactions present in the monomer in aqueous solution are largely replaced by intermolecular interactions in the aggregate. As a result, the overall chain dimensions are similar to the expected dimensions of chains in an ideal solvent, a state in which chain entropy is maximized. This is the prediction of the Flory theorem for generic polymer chains within a polymer melt, but has never, to our knowledge, been observed before for an aggregate of polypeptide chains in atomistic detail. Finally, we note that our results are not consistent with the current model of elastin self-aggregation, which involves a conformational transition of a monomer towards a more “ordered” aggregation-prone state. Instead, we propose a model in which both the hydrophobic effect and the enhanced chain entropy afforded by the interactions with other peptides within the aggregate favour elastin self-aggregation.