PlayMolecule ProteinPrepare: A Web Application for Protein Preparation for Molecular Dynamics Simulations

Protein preparation is a critical step in molecular simulations that consists of refining a Protein Data Bank (PDB) structure by assigning titration states and optimizing the hydrogen-bonding network. In this application note, we describe ProteinPrepare, a web application designed to interactively support the preparation of protein structures. Users can upload a PDB file, choose the solvent pH value, and inspect the resulting protonated residues and hydrogen-bonding network within a 3D web interface. Protonation states are suggested automatically but can be manually changed using the visual aid of the hydrogen-bonding network. Tables and diagrams provide estimated pKa values and charge states, with visual indication for cases where review is required. We expect the graphical interface to be a useful instrument to assess the validity of the preparation, but nevertheless, a script to execute the preparation offline with the High-Throughput Molecular Dynamics (HTMD) environment is also provided for noninteractive operations.

[1]  J. Ponder,et al.  Force fields for protein simulations. , 2003, Advances in protein chemistry.

[2]  K Schulten,et al.  VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.

[3]  J. Nielsen,et al.  The pKa Cooperative: A collaborative effort to advance structure‐based calculations of pKa values and electrostatic effects in proteins , 2011, Proteins.

[4]  C. Sander,et al.  Positioning hydrogen atoms by optimizing hydrogen‐bond networks in protein structures , 1996, Proteins.

[5]  Lin Li,et al.  DelPhi: a comprehensive suite for DelPhi software and associated resources , 2012, BMC biophysics.

[6]  Mallur S. Madhusudhan,et al.  Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins , 2013, Nucleic Acids Res..

[7]  Nathan A. Baker,et al.  Bayesian model aggregation for ensemble‐based estimates of protein pKa values , 2014, Proteins.

[8]  Jan H. Jensen,et al.  Graphical analysis of pH-dependent properties of proteins predicted using PROPKA , 2011, BMC Structural Biology.

[9]  Federico D. Sacerdoti,et al.  Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters , 2006, ACM/IEEE SC 2006 Conference (SC'06).

[10]  Ramu Anandakrishnan,et al.  H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations , 2012, Nucleic Acids Res..

[11]  Lisa J Lapidus,et al.  How fast is protein hydrophobic collapse? , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Nathan A. Baker,et al.  Electrostatics of nanosystems: Application to microtubules and the ribosome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[13]  E. Alexov,et al.  Combining conformational flexibility and continuum electrostatics for calculating pK(a)s in proteins. , 2002, Biophysical journal.

[14]  Gernot Kieseritzky,et al.  Optimizing pKA computation in proteins with pH adapted conformations , 2008, Proteins.

[15]  Jan H. Jensen,et al.  PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions. , 2011, Journal of chemical theory and computation.

[16]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[17]  D. Moss,et al.  Benchmarking pKa prediction , 2006, BMC Biochemistry.

[18]  Jan H. Jensen,et al.  Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa Values. , 2011, Journal of chemical theory and computation.

[19]  Frank Noé,et al.  HTMD: High-Throughput Molecular Dynamics for Molecular Discovery. , 2016, Journal of chemical theory and computation.

[20]  Holger Gohlke,et al.  The Amber biomolecular simulation programs , 2005, J. Comput. Chem..

[21]  J. Richardson,et al.  Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. , 1999, Journal of molecular biology.

[22]  Alexander S. Rose,et al.  NGL Viewer: a web application for molecular visualization , 2015, Nucleic Acids Res..

[23]  Peter M. Kasson,et al.  GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit , 2013, Bioinform..

[24]  Nathan A. Baker,et al.  Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins. , 2016, Methods in enzymology.

[25]  J. Nielsen.  Analysing the pH-dependent properties of proteins using pKa calculations. , 2007, Journal of molecular graphics & modelling.

[26]  Nathan A. Baker,et al.  PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations , 2004, Nucleic Acids Res..

[27]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[28]  Bernard R. Brooks,et al.  CHARMMing: A New, Flexible Web Portal for CHARMM , 2008, J. Chem. Inf. Model..

[29]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[30]  D. Case,et al.  Constant pH molecular dynamics in generalized Born implicit solvent , 2004, J. Comput. Chem..

[31]  M J Harvey,et al.  ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale. , 2009, Journal of chemical theory and computation.

[32]  H. Grubmüller,et al.  Constant pH Molecular Dynamics in Explicit Solvent with λ-Dynamics , 2011, Journal of chemical theory and computation.

[33]  Alexander D. MacKerell,et al.  CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field , 2015, Journal of chemical theory and computation.

[34]  Modesto Orozco,et al.  MDWeb and MDMoby: an integrated web-based platform for molecular dynamics simulations , 2012, Bioinform..

[35]  Gerhard Klebe,et al.  PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations , 2007, Nucleic Acids Res..