AA2UA is an open-source software package designed to convert all-atom Protein Data Bank (PDB) molecular models into their Coarse-Grained (CG) United Atom (UA) counterparts presented in the journal article entitled Introducing a force-matched united atom force field to explore larger spatiotemporal domains in molecular dynamics simulations of bitumen
Using Python 3.12 and Rdkit, the software
automatically reads .PDB files containing all-atom information of a molecular
system, extracts each molecule, determines higher order bonding information, assigns force field atom types and
masses, and generates a LAMMPS structure file with all the topologies
and force field definitions required
to run a LAMMPS simulations using the developed UA force field. AA2UA ensures a seamless conversion process,
making it easier for researchers to explore material properties without the extensive manual effort typically required
for such conversions.
Upon successfully installing Numpy, Numba and Rdkit, you are ready to run AA2UA. Follow the steps below to get started:
-
Run the Command: Execute the following command in your terminal or command prompt:
python aa2ua.py
By default, there are five .pdb files included in the
input/directory:ethylbenzene.pdb,phenol.pdb,pyrrole.pdb,thiophene.pdb, andmixture.pdb. These files correspond to all-atom mixtures of different organic molecules of various complexities. Upon executingpython aa2ua.py, all five files will be converted into their UA counterparts. -
Locating & Visualizing the Output: The results are exported into the
/outputsdirectory, with each structure.data file named after its corresponding input file. The resulting files can be easily visualized using OVITO. The ethylbenzene model, in its UA form, should look like this:
-
Loading into LAMMPS: Use the LAMMPS' read_data command in an input script to import the structure.data file generated by AA2UA.
This can be answered by analysing the type of systems compatible with the UA-CG force field developed by our team. As of now, only amorphous hydrocarbon systems are compatible, especially those whose composition is based on molecules used in the oil, gas, and asphalt industries. To get an idea of the variety of molecules that can be converted, refer to Table 2 in https://doi.org/10.1016/j.matdes.2024.112831.
A comprehensive flow diagram depicting the function calls during the program’s execution can be seen in the figure
below.
A description of all the functions, including their inputs and outputs ("docstring" style) follows the figure.
Description: Main execution flow of the script.
Description: Initializes the log file.
Parameters:
filename(str): Name of the log file (default: 'calls_log.txt').
Returns: None
Description: Logs a custom message to 'calls_log.txt'.
Parameters:
message(str): The text message to log.printmsg(bool): Whether to also print the message to the command line (default: False).
Returns: None
Description: Reads the contents of a PDB file and returns it as a list of lines.
Parameters:
filename(str): The path to the PDB file.
Returns: list: A list containing the lines of the file.
Description: Extracts box dimensions from PDB header.
Parameters:
pdb_header(str): PDB header containing box dimensions.
Returns: dict: Dictionary containing box dimensions.
Description: Extracts and groups molecules from a list of PDB file lines into separate blocks.
Parameters:
pdb_lines(list): The lines of a PDB file.
Returns: list: A list of molecule blocks, each represented as a list of lines.
Description: Generates a LAMMPS data file from molecule blocks.
Parameters:
molecule_blocks(list): A list of lists, where each inner list represents a molecule block in PDB format.output_file(str): The name of the output file to write the LAMMPS data.box_dimensions(dict): The dimensions of the simulation box.
Returns: None
Description: Determines bond orders for the molecule.
Parameters:
mol: RDKit molecule object.
Returns: None
Description: Removes hydrogen atoms from the molecule.
Parameters:
mol: RDKit molecule object.
Returns: rdkit.mol: RDKit molecule object with hydrogens removed.
Description: Generates a list of atom labels and their indices for a molecule.
Parameters:
mol: RDKit molecule object.
Returns: tuple: A tuple containing a list of atom index and label pairs, and the list of atoms.
The format for these labels is:
$atom_type-H$n_hydrogens-$hybridization-$degree-$is_in_ring-$is_aromatic
where:
- atom_type: The chemical symbol of the atom.
- n_hydrogens: The number of hydrogen atoms bonded to the atom.
- hybridization: The hybridization state of the atom.
- degree: The number of directly bonded neighbors.
- is_in_ring: A boolean indicating if the atom is part of a ring.
- is_aromatic: A boolean indicating if the atom is in an aromatic ring.
Description: Maps atom labels to force field types and updates the set of used atom types.
Parameters:
atom_info_list(list): A list of tuples where each tuple contains an atom index and its corresponding label.used_atom_types(set): A set of previously used atom types.
Returns: tuple: A tuple containing a dictionary mapping atom indices to their force field types, and the updated
set of used atom types. A ValueError is raised if any of the atoms in the molecule cannot be assigned with a force
field type.
A detailed description of all the 17 bead types in the UA the force field, identified from A through Q, can be found in
the figure below.
Description: Identifies and processes bond types, mapping them to unique integers.
Parameters:
bonds(list): A list of bonds in the molecule.atom_types(dict): A dictionary mapping atom indices to their force field types.bond_type_to_int(dict): A dictionary mapping bond type keys to integers.bond_type_index(int): The current index to be assigned to a new bond type.
Returns: tuple: A tuple containing a list of bond types with their atom indices, an updated bond type to integer
mapping, and the next bond type index.
process_angles(bonds: list, atom_types: dict, angle_type_to_int: dict, angle_type_index: int) -> tuple
Description: Identifies and processes angle types, mapping them to unique integers.
Parameters:
bonds(list): A list of bonds in the molecule.atom_types(dict): A dictionary mapping atom indices to their force field types.angle_type_to_int(dict): A dictionary mapping angle type keys to integers.angle_type_index(int): The current index to be assigned to a new angle type.
Returns: tuple: A tuple containing a list of angle types with their atom indices, an updated angle type to integer
mapping, and the next angle type index.
Description: Retrieves the 3D positions of non-hydrogen atoms in a molecule.
Parameters:
mol: RDKit molecule object.atoms(list): A list of atoms in the molecule.
Returns: dict: A dictionary mapping atom indices to their 3D positions.
Description: Converts atom types into unique integers.
Parameters:
used_atom_types(set): A set of atom types.
Returns: dict: A dictionary mapping each atom type to a unique integer.
write_lammps_file_header(file, total_atoms: int, total_bonds: int, total_angles: int, used_atom_types: set, bond_type_to_int: dict, angle_type_to_int: dict, box_dimensions: dict) -> None
Description: Writes the header information to a LAMMPS data file.
Parameters:
file: The file object to write the header information to.total_atoms(int): The total number of atoms.total_bonds(int): The total number of bonds.total_angles(int): The total number of angles.used_atom_types(set): A set of used atom types.bond_type_to_int(dict): A dictionary mapping bond type keys to integers.angle_type_to_int(dict): A dictionary mapping angle type keys to integers.box_dimensions(dict): A dictionary containing the dimensions of the simulation box.
Returns: None
Description: Writes mass information for each atom type to a LAMMPS data file.
Parameters:
file: The file object to write the mass information to.atom_type_to_int(dict): A dictionary mapping atom types to unique integers.
Returns: None
Description: Writes atom data to a LAMMPS data file.
Parameters:
file: The file object to write the atom information to.molecule_data(list): A list of dictionaries containing molecule information.atom_type_to_int(dict): A dictionary mapping atom types to unique integers.
Returns: None
Description: Writes bond data to a LAMMPS data file.
Parameters:
file: The file object to write the bond information to.molecule_data(list): A list of dictionaries containing molecule information.
Returns: None
Description: Writes angle data to a LAMMPS data file.
Parameters:
file: The file object to write the angle information to.molecule_data(list): A list of dictionaries containing molecule information.
Returns: None
AA2UA is licensed under the GNU General Public License (GPL), which is a widely used free software license that guarantees end users the freedom to run, study, share, and modify the software. The GPL license aims to ensure that the software remains free and open-source for all its users. For detailed terms and conditions, please refer to the full license text. The full text of the GPL license can be found at the official GNU website or included directly within this documentation.
For the full GPL license text, you may visit the GNU General Public License v3.0 website.
If you are using this script for your research, please cite Introducing a force-matched united atom force field to explore larger spatiotemporal domains in molecular dynamics simulations of bitumen (DOI: https://doi.org/10.1016/j.matdes.2024.112831).
The script was created by Eli I. Assaf ([email protected]), Xueyan Liu, and Sandra Erkens, all affiliated at TU Delft. The incentive of producing such script was to normalize the use of Python-based tools to perform MD simulations with relative ease.
This script is created under the research program Knowledge-based Pavement Engineering (KPE). KPE is a cooperation between Rijkswaterstaat, TNO, and TU Delft in which scientific and applied knowledge is gained about asphalt pavements and which contributes to the aim of Rijkswaterstaat to be completely climate neutral and to work according to the circular principle by 2030. The opinions expressed in these papers are solely from the authors.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent