.. _create-conf-label: Write topology using Python *************************** .. container:: hatnote Use Python to write topology files compatible with GROMACS .. container:: justify The objective of this extra tutorial is to use Python and write simple topology files that are compatible with GROMACS. The system consists in molecules and ions randomly placed in an empty box, and is used as a starting point in :ref:`bulk-solution-label`. Creating the GRO file ===================== .. container:: justify If you are only interested in learning GROMACS, jump directly to the actual GROMACS tutorial :ref:`bulk-solution-label`. .. include:: ../../non-tutorials/needhelp.rst What is a GRO file? ------------------- .. container:: justify A *.gro* file contains the initial positions and names of all the atoms of a simulation. The *.gro* file also contains the initial box size, and it can be read by GROMACS. .. container:: justify The typical structure of a *.gro* file is the following: .. code-block:: bw Name of the system number-of-atoms residue-number residue-name atom-name atom-number atom-positions (x3) # first atom residue-number residue-name atom-name atom-number atom-positions (x3) # second atom residue-number residue-name atom-name atom-number atom-positions (x3) # third atom (...) residue-number residue-name atom-name atom-number atom-positions (x3) # penultimate atom residue-number residue-name atom-name atom-number atom-positions (x3) # last atom box-size (x3) .. container:: justify One particularity of *.gro* file format is that each column must be located at a fixed position, see |conf.gro-manual|. .. |conf.gro-manual| raw:: html the GROMACS manual Residue definition ------------------ .. admonition:: About residue :class: info In GROMACS, a residue refers to a group of one or more atoms that are covalently linked and considered as a single unit within a molecule, ion, etc. .. container:: justify Open a blank Python script, call it *molecules.py*, and copy the following lines in it: .. code-block:: python import numpy as np # define SO4 ion def SO4_ion(): Position = np.array([[0.1238, 0.0587, 0.1119], \ [0.0778, 0.1501, -0.1263], \ [-0.0962, 0.1866, 0.0623], \ [-0.0592, -0.0506, -0.0358],\ [0.0115, 0.0862, 0.0030]]) Type = ['OS', 'OS', 'OS', 'OS', 'SO'] Name = ['O1', 'O2', 'O3', 'O4', 'S1'] Resname = 'SO4' return Position, Type, Resname, Name # define Na ion def Na_ion(): Position = np.array([[0, 0, 0]]) Type = ['Na'] Name = ['Na1'] Resname = 'Na' return Position, Type, Resname, Name # define water molecule def H20_molecule(): Position = np.array([[ 0. , 0. , 0. ], \ [ 0.05858, 0.0757 , 0. ], \ [ 0.05858, -0.0757 , 0. ], \ [ 0.0104 , 0. , 0. ]]) Type = ['OW', 'HW', 'HW', 'MW'] Name = ['OW1', 'HW1', 'HW2', 'MW1'] Resname = 'Sol' return Position, Type, Resname, Name .. container:: justify Each function corresponds to a residue, and contains the positions, types, and names of all the atoms, as well as the names of the residues. These functions will be called every time we need to place a residue in our system. .. container:: justify The water molecule contains a massless point (TIP4P model) in addition to the oxygen and hydrogens atoms :cite:`abascal2005general`. .. figure:: ../figures/create-GRO-python/molecule-light.png :alt: Gromacs tutorial : Initial water molecule, sodium, and sulfide ions. :class: only-light .. figure:: ../figures/create-GRO-python/molecule-dark.png :alt: Gromacs tutorial : Initial water molecule, sodium, and sulfide ions. :class: only-dark .. container:: figurelegend From left to right, the sulfide ion (:math:`\text{SO}_4^{2-}`), the sodium ion (:math:`\text{Na}^{+}`), and the water molecules (:math:`\text{H}_2\text{O}`). Oxygen atoms are in red, hydrogen atoms in white, sodium atoms in blue, and sulfur atoms in yellow. The fourth massless point (MW) of the water molecule is not visible. Creating the GRO file --------------------- .. container:: justify Here, we define some of the basic parameters of the simulation, such as the number of residues and the box size. .. container:: justify Next to the *molecule.py* file, create a new Python file called *generategro.py*, and copy the following lines into it: .. code-block:: python import numpy as np from molecules import SO4_ion, Na_ion, H20_molecule # define the box size Lx, Ly, Lz = [3.36]*3 box = np.array([Lx, Ly, Lz]) .. container:: justify Here, *box* is an array containing the box size along all 3 coordinates of space, respectively *Lx*, *Ly*, and *Lz*. A cubic box of lateral dimension :math:`3.6 ~ \text{nm}` is used. .. container:: justify Let us choose a salt concentration, and calculate the number of ions and water molecules accordingly, while also choosing the total number of residues (here I call residue either a molecule or an ion). Add the following to *generategro.py*: .. code-block:: python Mh2o = 0.018053 # kg/mol - water ntotal = 720 # total number of molecule c = 1.5 # desired concentration in mol/L nion = c*ntotal*Mh2o/(3*(1+Mh2o*c)) # desired number for the SO4 ion nwater = ntotal - 3*nion # desired number of water .. container:: justify Let us also choose typical cutoff distances (in nanometer) for each species. These cutoffs will be used to ensure that no species are inserted too close to one another, as it would make the simulation crash later: .. code-block:: python dSO4 = 0.45 dNa = 0.28 dSol = 0.28 .. container:: justify Let us initialize several counters and several lists. The lists will be used for storing all the data about the atoms: .. code-block:: python cpt_residue = 0 cpt_atoms = 0 cpt_SO4 = 0 cpt_Na = 0 cpt_Sol = 0 all_positions = [] all_resnum = [] all_resname = [] all_atname = [] all_attype = [] .. container:: justify Let us first add a number *nion* of :math:`\text{SO}_4^{2-}` ions at random locations. To avoid overlap, let us only insert ion if no other ions is already located at a distance closer than *dSO4*: .. code-block:: python # add SO4 randomly atpositions, attypes, resname, atnames = SO4_ion() while cpt_SO4 < np.int32(nion): x_com, y_com, z_com = generate_random_location(box) d = search_closest_neighbor(np.array(all_positions), atpositions + np.array([x_com, y_com, z_com]), box) if d < dSO4: add_residue = False else: add_residue = True if add_residue == True: cpt_SO4 += 1 cpt_residue += 1 for atposition, attype, atname in zip(atpositions, attypes, atnames): cpt_atoms += 1 x_at, y_at, z_at = atposition all_positions.append([x_com+x_at, y_com+y_at, z_com+z_at]) all_resnum.append(cpt_residue) all_resname.append(resname) all_atname.append(atname) all_attype.append(attype) .. container:: justify Here, two functions are used: *generate_random_location* and *search_closest_neighbor*. Let us define those two functions. Create a new Python script, call it *utils.py*, and copy the following lines in it: .. code-block:: python import numpy as np from numpy.linalg import norm def generate_random_location(box): """Generate a random location within a given box.""" return np.random.rand(3)*box def search_closest_neighbor(XYZ_neighbor, XYZ_molecule, box): """Search neighbor in a box and return the closest distance. If the neighbor list is empty, then the box size is returned. Periodic boundary conditions are automatically accounted """ if len(np.array(XYZ_neighbor)) == 0: min_distance = np.max(box) else: min_distance = np.max(box) for XYZ_atom in XYZ_molecule: dxdydz = np.remainder(XYZ_neighbor - XYZ_atom + box/2., box) - box/2. min_distance = np.min([min_distance,np.min(norm(dxdydz,axis=1))]) return min_distance .. container:: justify The *generate_random_location* function simply generates 3 random values within the box. The *search_closest_neighbor* looks for the minimum distance between existing atoms (if any) and the new residue. .. container:: justify Let us do the same for the :math:`\text{Na}^{+}` ion : .. code-block:: python # Import the functions from the utils file from utils import generate_random_location, search_closest_neighbor # add Na randomly atpositions, attypes, resname, atnames = Na_ion() while cpt_Na < np.int32(nion*2): x_com, y_com, z_com = generate_random_location(box) d = search_closest_neighbor(np.array(all_positions), atpositions + np.array([x_com, y_com, z_com]), box) if d < dNa: add_residue = False else: add_residue = True if add_residue == True: cpt_Na += 1 cpt_residue += 1 for atposition, attype, atname in zip(atpositions, attypes, atnames): cpt_atoms += 1 x_at, y_at, z_at = atposition all_positions.append([x_com+x_at, y_com+y_at, z_com+z_at]) all_resnum.append(cpt_residue) all_resname.append(resname) all_atname.append(atname) all_attype.append(attype) .. container:: justify Let us also insert water molecules on a 3D regular grid with spacing of *dSol* (only if no overlap exists): .. code-block:: python # add water randomly atpositions, attypes, resname, atnames = H20_molecule() for x_com in np.arange(dSol/2, Lx, dSol): for y_com in np.arange(dSol/2, Ly, dSol): for z_com in np.arange(dSol/2, Lz, dSol): d = search_closest_neighbor(np.array(all_positions), atpositions + np.array([x_com, y_com, z_com]), box) if d < dSol: add_residue = False else: add_residue = True if (add_residue == True) & (cpt_Sol < np.int32(nwater)): cpt_Sol += 1 cpt_residue += 1 for atposition, attype, atname in zip(atpositions, attypes, atnames): cpt_atoms += 1 x_at, y_at, z_at = atposition all_positions.append([x_com+x_at, y_com+y_at, z_com+z_at]) all_resnum.append(cpt_residue) all_resname.append(resname) all_atname.append(atname) all_attype.append(attype) if cpt_Sol >= np.int32(nwater): break print(cpt_Sol, 'out of', np.int32(nwater), 'water molecules created') .. container:: justify Let us ask Python to print a few information such as the actual concentration: .. code-block:: python print('Lx = '+str(Lx)+' nm, Ly = '+str(Ly)+' nm, Lz = '+str(Lz)+' nm') print(str(cpt_Na)+' Na ions') print(str(cpt_SO4)+' SO4 ions') print(str(cpt_Sol)+' Sol mols') Vwater = cpt_Sol/6.022e23*0.018 # kg or litter Naddion = (cpt_Na+cpt_SO4)/6.022e23 # mol cion = Naddion/Vwater print('The ion concentration is '+str(np.round(cion,2))+' mol per litter') .. container:: justify Finally, let us write the configuration (.gro) file: .. code-block:: python :caption: *to be copied in generategro.py* # write conf.gro f = open('conf.gro', 'w') f.write('Na2SO4 solution\n') f.write(str(cpt_atoms)+'\n') cpt = 0 for resnum, resname, atname, position in zip(all_resnum, all_resname, all_atname, all_positions): x, y, z = position cpt += 1 f.write("{: >5}".format(str(resnum))) # residue number (5 positions, integer) f.write("{: >5}".format(resname)) # residue name (5 characters) f.write("{: >5}".format(atname)) # atom name (5 characters) f.write("{: >5}".format(str(cpt))) # atom number (5 positions, integer) f.write("{: >8}".format(str("{:.3f}".format(x)))) # position (in nm, x y z in 3 columns, each 8 positions with 3 decimal places) f.write("{: >8}".format(str("{:.3f}".format(y)))) # position (in nm, x y z in 3 columns, each 8 positions with 3 decimal places) f.write("{: >8}".format(str("{:.3f}".format(z)))) # position (in nm, x y z in 3 columns, each 8 positions with 3 decimal places) f.write("\n") f.write("{: >10}".format(str("{:.5f}".format(Lx)))) # box size f.write("{: >10}".format(str("{:.5f}".format(Ly)))) # box size f.write("{: >10}".format(str("{:.5f}".format(Lz)))) # box size f.write("\n") f.close() Final system ------------ .. container:: justify Run the *generategro.py* file using Python. This is what appear in the terminal: .. code-block:: bw 701 out of 701 water molecules created Lx = 3.36 nm, Ly = 3.36 nm, Lz = 3.36 nm 12 Na ions 6 SO4 ions 701 Sol mols The ion concentration is 1.43 mol per litter .. container:: justify You can check the final system using VMD by typing in a terminal: .. code-block:: bash vmd conf.gro .. figure:: ../figures/create-GRO-python/system-light.png :alt: Gromacs tutorial - generated topology :class: only-light .. figure:: ../figures/create-GRO-python/system-dark.png :alt: Gromacs tutorial - generated topology :class: only-dark .. container:: figurelegend The primary system is located within the blue box. The replicated periodic images are also represented. .. container:: justify There is some vacuum left in the box. It is not an issue as energy minimization and molecular dynamics will help equilibrate the system. Creating the TOP file ===================== .. container:: justify A topology (.top) file defines the parameters required for the simulation, such as masses, Lennard-Jones parameters, or bonds. .. container:: justify Within the same Python script, write: .. code-block:: python # write topol.top f = open('topol.top', 'w') f.write('#include "ff/forcefield.itp"\n') f.write('#include "ff/h2o.itp"\n') f.write('#include "ff/na.itp"\n') f.write('#include "ff/so4.itp"\n\n') f.write('[ System ]\n') f.write('Na2SO4 solution\n\n') f.write('[ Molecules ]\n') f.write('SO4 '+ str(cpt_SO4)+'\n') f.write('Na '+ str(cpt_Na)+'\n') f.write('SOL '+ str(cpt_Sol)+'\n') f.close() Write parameters ---------------- .. container:: justify Here, the force field parameters (i.e. the *.itp* files) are written. Default parameters ------------------ .. container:: justify Create a folder called *ff/*. Within *ff/*, create a new empty file named *forcefield.itp*, and copy the following in it: .. code-block:: bw [ defaults ] ; nbfunc comb-rule gen-pairs fudgeLJ fudgeQQ 1 2 no 1.0 0.833 [ atomtypes ] ; name at.num mass charge ptype sigma epsilon Na 11 22.9900 1.0000 A 0.23100 0.45000 OS 8 15.9994 -1.0000 A 0.38600 0.12 SO 16 32.0600 2.0000 A 0.35500 1.0465 HW 1 1.0079 0.5270 A 0.00000 0.00000 OW 8 15.9994 0.0000 A 0.31650 0.77323 MW 0 0.0000 -1.0540 D 0.00000 0.00000 [ bondtypes ] ; i j func b0 kb SO OS 1 0.15 3.7656e4 [ angletypes ] ; i j k func theta k0 OS SO OS 1 109.5 520 .. container:: justify The |forcefield.itp| file is used to define basic combination rules, as well as atom types, bond types, and angle types. .. |forcefield.itp| raw:: html forcefield.itp .. container:: justify With comb-rule = 2, the mixing rule is calculated as :math:`\epsilon_{ij} = \sqrt{\epsilon_{ii} \epsilon_{jj}}`, :math:`\sigma_{ij} = (\sigma_{ii}+\sigma_{jj})/2`. FudgeLJ and fudgeQQ are the factors by which to multiply Lennard-Jones and Coulomb 1-4 interactions, respectively. You can refer to the |gromacs-manual| for more information. .. |gromacs-manual| raw:: html GROMACS manual .. container:: justify The |forcefield.itp| file also contains information about the atoms, such their masses and Lennard-Jones parameters sigma and epsilon, as well as some parameters for the bond and angle constraints that will be necessary for the SO4 ions. .. container:: justify Notice that the particle with name MW is of type 'D' when all the other particles are of type 'A' for atoms. This is because MW is the virtual massless site of our 4 points rigid water model, see this |tip4p-wiki| page for details. .. |tip4p-wiki| raw:: html wiki Sodium ion ---------- .. container:: justify Let us create a file named *na.itp* for the Sodium ion (|na.itp|): .. |na.itp| raw:: html na.itp .. code-block:: bw [ moleculetype ] ; molname nrexcl Na 1 [ atoms ] ; id at-type res-nr res-name at-name cg-nr charge mass 1 Na 1 Na Na1 1 1.000 22.9900 .. container:: justify The 'molecule' named *Na* for a residue with one single atom, of type *Na* and name *Na1*, charge +1.0 and mass 22.990 g/mol. Sulfate ion ----------- .. container:: justify The file *so4.itp* for the sulfate ion is more complex than the one for the sodium ion, as the residue is made of 5 atoms that are bonded together and maintained by angular constrained (|so4.itp|). .. |so4.itp| raw:: html so4.itp .. container:: justify The *exclusions* ensures that atoms from the same residue do not interact through LJ and Coulomb interactions. .. code-block:: bw [moleculetype] ; name nrexcl SO4 1 [ atoms ] ; id at-type res-nr res-name at-name cg-nr charge mass 1 OS 1 SO4 O1 1 -1.000 15.9994 2 OS 1 SO4 O2 1 -1.000 15.9994 3 OS 1 SO4 O3 1 -1.000 15.9994 4 OS 1 SO4 O4 1 -1.000 15.9994 5 SO 1 SO4 S1 1 2.000 32.0600 [ bonds ] ; ai aj funct c0 c1 1 5 1 0.1520 3.7656e4 2 5 1 0.1520 3.7656e4 3 5 1 0.1520 3.7656e4 4 5 1 0.1520 3.7656e4 [ angles ] ; ai aj ak funct angle fc 1 5 2 1 109.5 520 1 5 3 1 109.5 520 1 5 4 1 109.5 520 2 5 3 1 109.5 520 2 5 4 1 109.5 520 3 5 4 1 109.5 520 [exclusions] 1 2 3 4 5 2 1 3 4 5 3 1 2 4 5 4 1 2 3 5 5 1 2 3 4 Water molecule -------------- .. container:: justify Finally, create a file named *h2o.itp* for the water molecule (|h2o.itp|). Settle parameters are added to ensure that the water molecule remains rigid: .. |h2o.itp| raw:: html h2o.itp .. code-block:: bw [ moleculetype ] ; molname nrexcl SOL 2 [ atoms ] ; id at-type res-nr res-name at-name cg-nr charge mass 1 OW 1 SOL OW1 1 0.000 15.9994 2 HW 1 SOL HW1 1 0.527 1.0079 3 HW 1 SOL HW2 1 0.527 1.0079 4 MW 1 SOL MW1 1 -1.054 0.0000 [ settles ] ; i funct doh dhh 1 1 0.09572 0.15139 [ virtual_sites3 ] ; Vsite from funct a b 4 1 2 3 1 0.089608 0.089608 [ exclusions ] 1 2 3 4 2 1 3 4 3 1 2 4 4 1 2 3 .. container:: justify To continue and use those files for running a molecular dynamics simulation with GROMACS, go to :ref:`bulk-solution-label`.