PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations

By Todd J. Dolinsky, P. Czodrowski, Hui Li, Jens Erik Nielsen, Jan H. Jensen, Gerhard Klebe, Nathan A. Baker. Nucleic Acids Res., 2007

1,956 citations recorded by the source corpus.

Real-world observable physical and chemical characteristics are increasingly being calculated from the 3D structures of biomolecules. Methods for calculating pKa values, binding constants of ligands, and changes in protein stability are readily available, but often the limiting step in computational biology is the conversion of PDB structures into formats ready for use with biomolecular simulation software. The continued sophistication and integration of biomolecular simulation methods for systems- and genome-wide studies requires a fast, robust, physically realistic and standardized protocol for preparing macromolecular structures for biophysical algorithms. As described previously, the PDB2PQR web server addresses this need for electrostatic field calculations (Dolinsky et al., Nucleic Acids Research, 32, W665–W667, 2004). Here we report the significantly expanded PDB2PQR that includes the following features: robust standalone command line support, improved pKa estimation via the PROPKA framework, ligand parameterization via PEOE_PB charge methodology, expanded set of force fields and easily incorporated user-defined parameters via XML input files, and improvement of atom addition and optimization code. These features are available through a new web interface (http://pdb2pqr.sourceforge.net/), which offers users a wide range of options for PDB file conversion, modification and parameterization.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b87af3ded25ed61943ff0c69cb680743c33cda00

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Citations in the corpus

Improvements to the APBS biomolecular solvation software suite (2017, methodology): “The PDB2PQR software is part of the APBS suite that was developed to assist with the conversion of PDB files to PQR format.(38,39) In particular, PDB2PQR automatically sets up, executes, and optimizes the structure for Poisson–Boltzmann electrostatics calculations, outputting a PQR file that can be ”
Ligand Pose and Orientational Sampling in Molecular Docking (2013, background): “Other procedures for computing partial charges of ligand atoms and ligand desolvation terms besides AMSOL[116], like QEQUIL[117], PDB2PQR[118] or AM1BCC[119], could be tested.”
Biochemical and Structural Analysis of Common Cancer-Associated KRAS Mutations (2015, methodology): “Electrostatic maps of wild-type (WT) KRAS (PDB ID 4OBE) and KRAS G13D were generated using the PDB2PQR server (39, 40) with the PARSE force field and PROPKA to assign protonation states.”
Multi-Scale Representation Learning on Proteins (2022, methodology): “, 2001), PDB2PQR (Dolinsky et al., 2007) and multivalue (provided within the APBS suite).”
A computational study of the structure and function of human Zrt and Irt-like proteins metal transporters: An elevator-type transport mechanism predicted by AlphaFold2 (2022, methodology): “5.2, with the default PARSE force ﬁ eld, and the implemented PROPKA (Dolinsky et al., 2007; Olsson et al., 2011).”
CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting (2022, background): “CB-Dock2 will check the submitted protein, add the missing side-chain atoms (26,27) and hydrogen atoms, send notices about missing residues in a protein (28) and eliminate the co-crystallized waters as well as other het groups.”