# # * This library is free software; you can redistribute it and/or # * modify it under the terms of the GNU Lesser General Public # * License as published by the Free Software Foundation; either # * version 2.1 of the License, or (at your option) any later version. # * # * This library is distributed in the hope that it will be useful, # * but WITHOUT ANY WARRANTY; without even the implied warranty of # * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # * Lesser General Public License for more details. # #propka3.0, revision 182 2011-08-09 #------------------------------------------------------------------------------------------------------- #-- -- #-- PROPKA: A PROTEIN PKA PREDICTOR -- #-- -- #-- VERSION 3.0, 01/01/2011, COPENHAGEN -- #-- BY MATS H.M. OLSSON AND CHRESTEN R. SONDERGARD -- #-- -- #------------------------------------------------------------------------------------------------------- # # #------------------------------------------------------------------------------------------------------- # References: # # Very Fast Empirical Prediction and Rationalization of Protein pKa Values # Hui Li, Andrew D. Robertson and Jan H. Jensen # PROTEINS: Structure, Function, and Bioinformatics 61:704-721 (2005) # # Very Fast Prediction and Rationalization of pKa Values for Protein-Ligand Complexes # Delphine C. Bas, David M. Rogers and Jan H. Jensen # PROTEINS: Structure, Function, and Bioinformatics 73:765-783 (2008) # # PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa predictions # Mats H.M. Olsson, Chresten R. Sondergard, Michal Rostkowski, and Jan H. Jensen # Journal of Chemical Theory and Computation, 7, 525-537 (2011) #------------------------------------------------------------------------------------------------------- from .lib import pka_print def resName2Type(resName=None): """ definition of which parameter-group each residues belongs to """ resType = {'C- ': "COO", 'ASP': "COO", 'GLU': "COO", 'HIS': "HIS", 'CYS': "CYS", 'TYR': "TYR", 'LYS': "LYS", 'ARG': "ARG", 'N+ ': "N+ ", 'SER': "ROH", 'THR': "ROH", 'ASN': "AMD", 'GLN': "AMD", 'TRP': "TRP"} if resName in resType: return resType[resName] else: return resType def getQs(resName=None): """ Returns a dictionary with residue charges """ Q = {'COO': -1.0, 'ASP': -1.0, 'GLU': -1.0, 'C- ': -1.0, 'TYR': -1.0, 'CYS': -1.0, 'HIS': 1.0, 'LYS': 1.0, 'ARG': 1.0, 'N+ ': 1.0} if resName in Q: return Q[resName] else: return Q def pKa_mod(resName=None): """ returns a dictionary with model/water pKa values """ pKa_mod = {'C- ': 3.20, 'ASP': 3.80, 'GLU': 4.50, 'HIS': 6.50, 'CYS': 9.00, 'TYR': 10.00, 'LYS': 10.50, 'ARG': 12.50, 'N+ ': 8.00, 'default': 20.00} if resName == None: return pKa_mod elif resName in pKa_mod: return pKa_mod[resName] else: # generic value for 'uninteresting' residues, e.g. ASN, GLN return 20.00 def getInteraction(): """ matrix for propka interactions; Note that only the LOWER part of the matrix is used! 'N' non-iterative interaction 'I' iterative interaction '-' no interaction """ # COO CYS TYR HIS N+ LYS ARG side_chain = {'COO': ["I", "I", "N", "I", "N", "N", "N"], 'CYS': ["I", "I", "N", "I", "N", "N", "N"], 'TYR': ["N", "N", "I", "I", "I", "I", "N"], 'HIS': ["I", "I", "I", "I", "N", "N", "N"], 'N+ ': ["N", "N", "I", "N", "I", "N", "N"], 'LYS': ["N", "N", "I", "N", "N", "I", "N"], 'ARG': ["N", "N", "N", "N", "N", "N", "I"], 'ROH': ["N", "N", "N", "-", "-", "-", "-"], 'AMD': ["N", "N", "N", "N", "N", "N", "N"], 'TRP': ["N", "N", "N", "-", "-", "-", "-"]} return side_chain # ------- Coulomb parameters --------- # def getCoulombParameters(label=None): """ storage of Coulomb default parameters """ CoulombParameters = {} CoulombParameters['Linear'] = {'cutoff': [4.0, 7.0], 'max_dpka': 2.40, 'scaled': True, } CoulombParameters['Coulomb'] = {'cutoff': [4.0, 10.0], 'diel': 80.00, 'scaled': True, } CoulombParameters['DistanceScaledCoulomb'] = {'cutoff': [4.0, 10.0], 'diel': [30.0, 160.0], 'scaled': False, } if label in CoulombParameters: return CoulombParameters[label] else: return CoulombParameters # ------- Desolvation parameters --------- # def getDesolvationParameters(label=None): """ storage of desolvation default parameters """ DesolvationParameters = {} DesolvationParameters['propka2'] = {'allowance': 400.00, 'prefactor': -0.01, 'local': -0.07, 'radii': getLocalRadii(), } DesolvationParameters['ContactModel'] = {'allowance': 400.00, 'prefactor': -0.01, 'local': -0.07, 'radii': getLocalRadii(), } DesolvationParameters['VolumeModel'] = {'allowance': 0.00, 'prefactor': -13.50, 'surface': 0.25, 'volume': getVanDerWaalsVolumes(), } DesolvationParameters['ScaledVolumeModel'] = {'allowance': 0.00, 'prefactor': -13.50, 'surface': 0.00, 'volume': getVanDerWaalsVolumes(), } if label in DesolvationParameters: return DesolvationParameters[label] else: return DesolvationParameters def getVanDerWaalsVolumes(): """ storing relative Van der Waals volumes for volume desolvation models """ # relative volume radius VanDerWaalsVolume = {'C': 1.40, # 20.58 1.70 all 'C' and 'CA' atoms 'C4': 2.64, # 38.79 2.10 hydrodphobic carbon atoms + unidentified atoms 'N': 1.06, # 15.60 1.55 all nitrogen atoms 'O': 1.00, # 14.71 1.52 all oxygen atoms 'S': 1.66, # 24.43 1.80 all sulphur atoms } return VanDerWaalsVolume def getLocalRadii(): """ local radii used in the 'propka2' and 'contact' desolvation models """ local_radius = {'ASP': 4.5, 'GLU': 4.5, 'HIS': 4.5, 'CYS': 3.5, 'TYR': 3.5, 'LYS': 4.5, 'ARG': 5.0, 'C- ': 4.5, 'N+ ': 4.5} return local_radius # ------- hydrogen-bond parameters --------- # def getHydrogenBondParameters(type=None): """ definitions of default back-bone or side-chain interaction parameters IMPORTANT: parameters with assigned to 'None' are given by the reverse (e.g. CYS-COO is given by COO-CYS) generated at the end. """ if type == "back-bone": # --- new back-bone parameter set --- # parameters determining the interaction with back-bone NH or CO groups parameters = {"COO": [-0.80, [2.00, 3.00]], "CYS": [-0.80, [3.00, 4.00]], "TYR": [-1.20, [2.20, 3.20]], "HIS": [ 0.80, [2.00, 3.00]], "N+ ": [ 0.80, [2.80, 3.80]], "LYS": [ 0.80, [2.80, 3.80]], "ARG": [ 0.80, [2.00, 3.00]]} elif type == "side-chain": # --- new side-chain parameter set --- # parameters determining the interaction with side-chain NH or CO groups # IMPORTANT: parameters with assigned to 'None' are given by the reverse # (e.g. CYS-COO is given by COO-CYS) generated at the end. parameters = {} parameters["COO"] = {"COO": [-0.80, [ 2.50, 3.50]], "CYS": [-0.80, [ 3.00, 4.00]], "TYR": [-0.80, [ 2.65, 3.65]], "HIS": [-0.80, [ 2.00, 3.00]], "N+ ": [-0.80, [ 2.85, 3.85]], "LYS": [-0.80, [ 2.85, 3.85]], "ARG": [-0.80, [ 1.85, 2.85]], "ROH": [-0.80, [ 2.65, 3.65]], "AMD": [-0.80, [ 2.00, 3.00]], "TRP": [-0.80, [ 2.00, 3.00]]} parameters["CYS"] = {"COO": None, "CYS": [-1.60, [ 3.00, 5.00]], "TYR": [-0.80, [ 3.50, 4.50]], "HIS": [-1.60, [ 3.00, 4.00]], "N+ ": [-2.40, [ 3.00, 4.50]], "LYS": [-1.60, [ 3.00, 4.00]], "ARG": [-1.60, [ 2.50, 4.00]], "ROH": [-1.60, [ 3.50, 4.50]], "AMD": [-1.60, [ 2.50, 3.50]], "TRP": [-1.60, [ 2.50, 3.50]]} parameters["TYR"] = {"COO": None, "CYS": None, "TYR": [ 0.80, [ 3.50, 4.50]], "HIS": [-0.80, [ 2.00, 3.00]], "N+ ": [-1.20, [ 3.00, 4.50]], "LYS": [-0.80, [ 3.00, 4.00]], "ARG": [-0.80, [ 2.50, 4.00]], "ROH": [-0.80, [ 3.50, 4.50]], "AMD": [-0.80, [ 2.50, 3.50]], "TRP": [-0.80, [ 2.50, 3.50]]} parameters["HIS"] = {"COO": None, "CYS": None, "TYR": None, "HIS": [ 0.00, [ 0.00, 0.00]], "N+ ": [ 0.00, [ 0.00, 0.00]], "LYS": [ 0.00, [ 0.00, 0.00]], "ARG": [ 0.00, [ 0.00, 0.00]], "ROH": [ 0.00, [ 0.00, 0.00]], "AMD": [ 0.80, [ 2.00, 3.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["N+ "] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": [ 0.00, [ 0.00, 0.00]], "LYS": [ 0.00, [ 0.00, 0.00]], "ARG": [ 0.00, [ 0.00, 0.00]], "ROH": [ 0.00, [ 0.00, 0.00]], "AMD": [ 0.00, [ 0.00, 0.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["LYS"] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": None, "LYS": [ 0.00, [ 0.00, 0.00]], "ARG": [ 0.00, [ 0.00, 0.00]], "ROH": [ 0.00, [ 0.00, 0.00]], "AMD": [ 0.00, [ 0.00, 0.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["ARG"] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": None, "LYS": None, "ARG": [ 0.00, [ 0.00, 0.00]], "ROH": [ 0.00, [ 0.00, 0.00]], "AMD": [ 0.00, [ 0.00, 0.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["ROH"] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": None, "LYS": None, "ARG": None, "ROH": [ 0.00, [ 0.00, 0.00]], "AMD": [ 0.00, [ 0.00, 0.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["AMD"] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": None, "LYS": None, "ARG": None, "ROH": None, "AMD": [ 0.00, [ 0.00, 0.00]], "TRP": [ 0.00, [ 0.00, 0.00]]} parameters["TRP"] = {"COO": None, "CYS": None, "TYR": None, "HIS": None, "N+ ": None, "LYS": None, "ARG": None, "ROH": None, "AMD": None, "TRP": [ 0.00, [ 0.00, 0.00]]} # updating parameter matrix to full matrix keys = list(parameters.keys()) for key1 in keys: for key2 in keys: if key2 not in parameters[key1]: parameters[key1][key2] == [ 0.00, [ 0.00, 0.00]] elif parameters[key1][key2] == None: parameters[key1][key2] = parameters[key2][key1] else: pka_print("cannot determine what type of hydrogen-bonding interactions you want type=\"%s\" ['back-bone', 'side-chain']" % (label)) sys.exit(9) return parameters