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The multiple-solvent crystal structure (MSCS) approach uses high concentrations of organic solvents to characterize the interactions and effects of solvents on proteins. Here, the method has been further developed and an MSCS data-handling pipeline is presented that uses the Detection of Related Solvent Positions (DRoP) program to improve data quality. DRoP is used to selectively model conserved water molecules, so that an advanced stage of structural refinement is reached quickly. This allows the placement of organic molecules more accurately and convergence on high-quality maps and structures. This pipeline was applied to the chromatin-associated protein barrier-to-autointegration factor (BAF), resulting in structural models with better than average statistics. DRoP and Phenix Structure Comparison were used to characterize the data sets and to identify a binding site that overlaps with the interaction site of BAF with emerin. The conserved water-mediated networks identified by DRoP suggested a mechanism by which water molecules are used to drive the binding of DNA. Normalized and differential B-factor analysis is shown to be a valuable tool to characterize the effects of specific solvents on defined regions of BAF. Specific solvents are identified that cause stabilization of functionally important regions of the protein. This work presents tools and a standardized approach for the analysis and comprehension of MSCS data sets.

Supporting information

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Portable Document Format (PDF) file https://doi.org/10.1107/S2059798320011341/gi5026sup1.pdf
Supplementary Tables and Figures,

PDB references: barrier-to-autointegration factor, 6unt; 6ure; 6urj; 6urk; 6url; 6urn; 6urr; 6urz; 6us0; 6us1; 6us7; 6usb; 6usd; 6usi


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