Calculating and estimating sigma profiles

Sigma profiles are one of the fundamental pieces of a COSMO-RS/-SAC calculation. They are also widely used as an important empirical descriptor for a molecule’s behavior in a solution as well as for a molecule’s properties in a number of applications. In the standard COSMO-RS/-SAC workflow, sigma profiles are generated after a sequence of DFT calculations which – for large molecular systems – can take considerable time to complete. For computationally expensive systems or high-throughput screening applications, it is sometimes advantageous to approximate sigma profiles using tools like fast_sigma from AMS.

In the following python script, we generate sigma profiles for n-Hexanoic acid using the two approaches discussed above. The function calc_sigma_profile will generate sigma profiles from .coskf files, and the function fast_sigma will generate sigma profiles from SMILES strings using the fast_sigma tool.

Python code

[show/hide code]
import os
import numpy as np
import matplotlib.pyplot as plt
from scm.utils.runsubprocess import RunSubprocess
from scm.plams import *
import subprocess

##################  Note: Be sure to add the path to your own AMSCRS directory here  ##################
database_path = os.getcwd()

if not os.path.exists(database_path):
    raise OSError(f'The provided path does not exist. Exiting.')

#suppress plams output
config.log.stdout = 0

class SigmaProfile:
    def __init__(self,chdens,profiles,profile_names):
        if len(profiles) != len(profile_names):
            print("Error: profiles_names and profiles of different sizes")
        self.chdens   = chdens.flatten() if isinstance(chdens,np.ndarray) else chdens
        self.profiles = {name:prof.flatten() if isinstance(prof,np.ndarray) else prof for name,prof in zip(profile_names,profiles)}

    def __str__(self):
        line = "─"*(15*(1+len(self.profiles)))
        ret =  line + '\n'+ "".join( ["Charge Dens.".ljust(15)]+[name.ljust(15) for name in self.profiles] ) + '\n' + line + '\n'
        for i in range(len(self.chdens)):
            ret += "{0:.5g}".format(self.chdens[i]).ljust(15) + "".join(["{0:.5g}".format(v[i]).ljust(15) for k,v in self.profiles.items()])
            ret += '\n'
        return ret

def fast_sigma( smiles ):

    results_file =  "tmp_results18954.crskf"
    subprocess_string = " --smiles '" + smiles + "'"

    if not os.path.isfile(os.path.join( os.path.expandvars("$AMSBIN") , "fast_sigma" )):
        kf_and_sys_exit("ERROR: cannot find fast_sigma ... has amsbashrc been executed?")

    fs = os.path.join( os.path.expandvars("$AMSBIN") , "fast_sigma" )
    scm_sp = RunSubprocess( fs + subprocess_string + " -o " + results_file )

    if os.path.isfile(results_file):
        crskf   =    KFFile( results_file )
        res     =    crskf.read_section( "PURESIGMAPROFILE"  )
        sp = SigmaProfile(chdens=res['chdval'],profiles=[res['profil'],res['hbprofil']],profile_names=["total_profile","HB_profile"])
        return sp, scm_sp
        return None, scm_sp

def calc_sigma_profile(coskf_file,cosmosac=False):

    # initialize settings object
    settings = Settings() = 'PURESIGMAPROFILE'

    # set the number of compounds
    compounds = [Settings()]
    compounds[0]._h = os.path.join( database_path, coskf_file )

    # to change to the COSMOSAC2013 method
    if cosmosac:
        settings.input.method = 'COSMOSAC2013'

    # specify the compounds as the compounds to be used in the calculation
    settings.input.compound = compounds
    # create a job that can be run by COSMO-RS
    my_job = CRSJob(settings=settings)

    out =
    res = out.get_results()

    if cosmosac:
        prof_len = len(res['hbprofil'])//3
        sp = SigmaProfile(chdens=res['chdval'],profiles=[res['profil']]+[res['hbprofil'][i*prof_len:(i+1)*prof_len] for i in range(3) ],profile_names=["total_profile","HB","HB-OH","HB-OT"])
        sp = SigmaProfile(chdens=res['chdval'],profiles=[res['profil'],res['hbprofil']],profile_names=["total_profile","HB_profile"])
    return sp

# regular way to generate a sigma profile from a .coskf file
filename = "n-Hexanoic_acid.coskf"
sp = calc_sigma_profile(filename,cosmosac=False)

# way using the fast_sigma estimation method
fs_sp, err = fast_sigma("CCCCCC(=O)O")
if fs_sp is None or len(err[1])>0:
    print("fast_sigma generated the following output:\n"+err[1])

plt.xlabel("σ value (e/A^2)")

plt.plot(sp.chdens   ,   sp.profiles['total_profile'],label="Calculated sigma profile")
if fs_sp is not None:
    plt.plot(fs_sp.chdens,fs_sp.profiles['total_profile'],label="Estimated sigma profile")

plt.legend(loc='upper right')


This code produces the following output: