LAWS: Local alignment for water sites-Tracking ordered water in simulations.

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.

Functional protein dynamics in a crystal.

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.