PDB2INS: bridging the gap between small-molecule and macromolecular refinement

Area of Science:

• Crystallography
• Structural Biology
• Computational Chemistry

Background:

• Macromolecular structure determination relies on accurate refinement of atomic coordinates.
• The process of preparing input files for refinement software like SHELXL can be time-consuming and prone to errors.
• Automating the generation of refinement files can significantly improve efficiency in structural biology workflows.

Purpose of the Study:

• To introduce PDB2INS, an open-source Python program designed to automate the preparation of .ins and .hkl files for SHELXL refinement.
• To enable PDB2INS to retrieve necessary data directly from the Protein Data Bank (PDB) archive or PDB_REDO server using a PDB code.
• To assess the performance and success rate of PDB2INS in generating refinement-ready files for a large dataset of X-ray structures.

Main Methods:

• PDB2INS utilizes PDB codes to access atomic coordinates from PDB-format files and reflection data from mmCIF or PDB_REDO.
• The program automatically generates SHELX-format .ins and .hkl files, including necessary restraints.
• A dataset of 23,5974 X-ray structures from the PDB (2008-2018) with high-resolution data was used for testing.

Main Results:

• PDB2INS successfully generated input files for SHELXL without user intervention for 96% of the tested structures.
• The program automatically incorporated appropriate restraints and other necessary parameters for refinement.
• Subsequent refinement using SHELXL completed successfully for the majority of structures processed by PDB2INS.

Conclusions:

• PDB2INS is an effective tool for automating the preparation of crystallographic refinement files.
• The program enhances the efficiency and reduces potential errors in the structure refinement process.
• PDB2INS facilitates the use of SHELXL for a wide range of X-ray crystallographic datasets.