def fetchPDBLigand(cci, filename=None): """Fetch PDB ligand data from PDB_ for chemical component *cci*. *cci* may be 3-letter chemical component identifier or a valid XML filename. If *filename* is given, XML file will be saved with that name. If you query ligand data frequently, you may configure ProDy to save XML files in your computer. Set ``ligand_xml_save`` option **True**, i.e. ``confProDy(ligand_xml_save=True)``. Compressed XML files will be save to ProDy package folder, e.g. :file:`/home/user/.prody/pdbligands`. Each file is around 5Kb when compressed. This function is compatible with PDBx/PDBML v 4.0. Ligand data is returned in a dictionary. Ligand coordinate atom data with *model* and *ideal* coordinate sets are also stored in this dictionary. Note that this dictionary will contain data that is present in the XML file and all Ligand Expo XML files do not contain every possible data field. So, it may be better if you use :meth:`dict.get` instead of indexing the dictionary, e.g. to retrieve formula weight (or relative molar mass) of the chemical component use ``data.get('formula_weight')`` instead of ``data['formula_weight']`` to avoid exceptions when this data field is not found in the XML file. URL and/or path of the XML file are returned in the dictionary with keys ``url`` and ``path``, respectively. Following example downloads data for ligand STI (a.k.a. Gleevec and Imatinib) and calculates RMSD between model (X-ray structure 1IEP) and ideal (energy minimized) coordinate sets: .. ipython:: python from prody import * ligand_data = fetchPDBLigand('STI') ligand_data['model_coordinates_db_code'] ligand_model = ligand_data['model'] ligand_ideal = ligand_data['ideal'] transformation = superpose(ligand_ideal.noh, ligand_model.noh) calcRMSD(ligand_ideal.noh, ligand_model.noh)""" if not isinstance(cci, str): raise TypeError('cci must be a string') if isfile(cci): inp = openFile(cci) xml = inp.read() inp.close() url = None path = cci cci = splitext(splitext(split(cci)[1])[0])[0].upper() elif len(cci) > 4 or not cci.isalnum(): raise ValueError('cci must be 3-letters long and alphanumeric or ' 'a valid filename') else: xml = None cci = cci.upper() if SETTINGS.get('ligand_xml_save'): folder = join(getPackagePath(), 'pdbligands') if not isdir(folder): makePath(folder) xmlgz = path = join(folder, cci + '.xml.gz') if isfile(xmlgz): with openFile(xmlgz) as inp: xml = inp.read() else: path = None #url = ('http://ligand-expo.rcsb.org/reports/{0[0]}/{0}/{0}' # '.xml'.format(cci.upper())) url = 'http://www.pdb.org/pdb/files/ligand/{0}.xml'.format(cci.upper()) if not xml: #'http://www.pdb.org/pdb/files/ligand/{0}.xml' try: inp = openURL(url) except IOError: raise IOError('XML file for ligand {0} is not found online' .format(cci)) else: xml = inp.read() inp.close() if filename: out = openFile(filename, mode='w', folder=folder) out.write(xml) out.close() if SETTINGS.get('ligand_xml_save'): with openFile(xmlgz, 'w') as out: out.write(xml) import xml.etree.cElementTree as ET root = ET.XML(xml) if (root.get('{http://www.w3.org/2001/XMLSchema-instance}' 'schemaLocation') != 'http://pdbml.pdb.org/schema/pdbx-v40.xsd pdbx-v40.xsd'): LOGGER.warn('XML is not in PDBx/PDBML v 4.0 format, resulting ' 'dictionary may not contain all data fields') ns = root.tag[:root.tag.rfind('}')+1] len_ns = len(ns) dict_ = {'url': url, 'path': path} for child in list(root.find(ns + 'chem_compCategory')[0]): tag = child.tag[len_ns:] if tag.startswith('pdbx_'): tag = tag[5:] dict_[tag] = child.text dict_['formula_weight'] = float(dict_.get('formula_weight')) identifiers_and_descriptors = [] results = root.find(ns + 'pdbx_chem_comp_identifierCategory') if results: identifiers_and_descriptors.extend(results) results = root.find(ns + 'pdbx_chem_comp_descriptorCategory') if results: identifiers_and_descriptors.extend(results) for child in identifiers_and_descriptors: program = child.get('program').replace(' ', '_') type_ = child.get('type').replace(' ', '_') dict_[program + '_' + type_] = child[0].text dict_[program + '_version'] = child.get('program_version') dict_['audits'] = [(audit.get('action_type'), audit.get('date')) for audit in list(root.find(ns + 'pdbx_chem_comp_auditCategory'))] atoms = list(root.find(ns + 'chem_comp_atomCategory')) n_atoms = len(atoms) ideal_coords = np.zeros((n_atoms, 3)) model_coords = np.zeros((n_atoms, 3)) atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype) elements = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['element'].dtype) resnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['resname'].dtype) charges = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype) resnums = np.ones(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype) alternate_atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype) leaving_atom_flags = np.zeros(n_atoms, np.bool) aromatic_flags = np.zeros(n_atoms, np.bool) stereo_configs = np.zeros(n_atoms, np.bool) ordinals = np.zeros(n_atoms, int) name2index = {} for i, atom in enumerate(atoms): data = dict([(child.tag[len_ns:], child.text) for child in list(atom)]) name = data.get('pdbx_component_atom_id', 'X') name2index[name] = i atomnames[i] = name elements[i] = data.get('type_symbol', 'X') resnames[i] = data.get('pdbx_component_comp_id', 'UNK') charges[i] = float(data.get('charge', 0)) alternate_atomnames[i] = data.get('alt_atom_id', 'X') leaving_atom_flags[i] = data.get('pdbx_leaving_atom_flag') == 'Y' aromatic_flags[i] = data.get('pdbx_atomatic_flag') == 'Y' stereo_configs[i] = data.get('pdbx_stereo_config') == 'Y' ordinals[i] = int(data.get('pdbx_ordinal', 0)) model_coords[i, 0] = float(data.get('model_Cartn_x', 0)) model_coords[i, 1] = float(data.get('model_Cartn_y', 0)) model_coords[i, 2] = float(data.get('model_Cartn_z', 0)) ideal_coords[i, 0] = float(data.get('pdbx_model_Cartn_x_ideal', 0)) ideal_coords[i, 1] = float(data.get('pdbx_model_Cartn_y_ideal', 0)) ideal_coords[i, 2] = float(data.get('pdbx_model_Cartn_z_ideal', 0)) pdbid = dict_.get('model_coordinates_db_code') if pdbid: model = AtomGroup(cci + ' model ({0})'.format(pdbid)) else: model = AtomGroup(cci + ' model') model.setCoords(model_coords) model.setNames(atomnames) model.setResnames(resnames) model.setResnums(resnums) model.setElements(elements) model.setCharges(charges) model.setFlags('leaving_atom_flags', leaving_atom_flags) model.setFlags('aromatic_flags', aromatic_flags) model.setFlags('stereo_configs', stereo_configs) model.setData('ordinals', ordinals) model.setData('alternate_atomnames', alternate_atomnames) dict_['model'] = model ideal = model.copy() ideal.setTitle(cci + ' ideal') ideal.setCoords(ideal_coords) dict_['ideal'] = ideal bonds = [] warned = set() for bond in list(root.find(ns + 'chem_comp_bondCategory') or bonds): name_1 = bond.get('atom_id_1') name_2 = bond.get('atom_id_2') try: bonds.append((name2index[name_1], name2index[name_2])) except KeyError: if name_1 not in warned and name_1 not in name2index: warned.add(name_1) LOGGER.warn('{0} specified {1} in bond category is not ' 'a valid atom name.'.format(repr(name_1), cci)) if name_2 not in warned and name_2 not in name2index: warned.add(name_2) LOGGER.warn('{0} specified {1} in bond category is not ' 'a valid atom name.'.format(repr(name_2), cci)) if bonds: bonds = np.array(bonds, int) model.setBonds(bonds) ideal.setBonds(bonds) return dict_
def fetchPDBLigand(cci, filename=None): """Fetch PDB ligand data from PDB_ for chemical component *cci*. *cci* may be 3-letter chemical component identifier or a valid XML filename. If *filename* is given, XML file will be saved with that name. If you query ligand data frequently, you may configure ProDy to save XML files in your computer. Set ``ligand_xml_save`` option **True**, i.e. ``confProDy(ligand_xml_save=True)``. Compressed XML files will be save to ProDy package folder, e.g. :file:`/home/user/.prody/pdbligands`. Each file is around 5Kb when compressed. This function is compatible with PDBx/PDBML v 4.0. Ligand data is returned in a dictionary. Ligand coordinate atom data with *model* and *ideal* coordinate sets are also stored in this dictionary. Note that this dictionary will contain data that is present in the XML file and all Ligand Expo XML files do not contain every possible data field. So, it may be better if you use :meth:`dict.get` instead of indexing the dictionary, e.g. to retrieve formula weight (or relative molar mass) of the chemical component use ``data.get('formula_weight')`` instead of ``data['formula_weight']`` to avoid exceptions when this data field is not found in the XML file. URL and/or path of the XML file are returned in the dictionary with keys ``url`` and ``path``, respectively. Following example downloads data for ligand STI (a.k.a. Gleevec and Imatinib) and calculates RMSD between model (X-ray structure 1IEP) and ideal (energy minimized) coordinate sets: .. ipython:: python from prody import * ligand_data = fetchPDBLigand('STI') ligand_data['model_coordinates_db_code'] ligand_model = ligand_data['model'] ligand_ideal = ligand_data['ideal'] transformation = superpose(ligand_ideal.noh, ligand_model.noh) calcRMSD(ligand_ideal.noh, ligand_model.noh)""" if not isinstance(cci, str): raise TypeError('cci must be a string') if isfile(cci): inp = openFile(cci) xml = inp.read() inp.close() url = None path = cci cci = splitext(splitext(split(cci)[1])[0])[0].upper() elif len(cci) > 4 or not cci.isalnum(): raise ValueError('cci must be 3-letters long and alphanumeric or ' 'a valid filename') else: xml = None cci = cci.upper() if SETTINGS.get('ligand_xml_save'): folder = join(getPackagePath(), 'pdbligands') if not isdir(folder): makePath(folder) xmlgz = path = join(folder, cci + '.xml.gz') if isfile(xmlgz): with openFile(xmlgz) as inp: xml = inp.read() else: path = None #url = ('http://ligand-expo.rcsb.org/reports/{0[0]}/{0}/{0}' # '.xml'.format(cci.upper())) url = 'http://files.rcsb.org/ligands/download/{0}.xml'.format( cci.upper()) if not xml: #'http://www.pdb.org/pdb/files/ligand/{0}.xml' try: inp = openURL(url) except IOError: raise IOError( 'XML file for ligand {0} is not found online'.format(cci)) else: xml = inp.read() inp.close() if filename: out = openFile(filename, mode='w', folder=folder) out.write(xml) out.close() if SETTINGS.get('ligand_xml_save'): with openFile(xmlgz, 'w') as out: out.write(xml) import xml.etree.cElementTree as ET root = ET.XML(xml) if (root.get('{http://www.w3.org/2001/XMLSchema-instance}' 'schemaLocation') != 'http://pdbml.pdb.org/schema/pdbx-v40.xsd pdbx-v40.xsd'): LOGGER.warn('XML is not in PDBx/PDBML v 4.0 format, resulting ' 'dictionary may not contain all data fields') ns = root.tag[:root.tag.rfind('}') + 1] len_ns = len(ns) dict_ = {'url': url, 'path': path} for child in list(root.find(ns + 'chem_compCategory')[0]): tag = child.tag[len_ns:] if tag.startswith('pdbx_'): tag = tag[5:] dict_[tag] = child.text dict_['formula_weight'] = float(dict_.get('formula_weight')) identifiers_and_descriptors = [] results = root.find(ns + 'pdbx_chem_comp_identifierCategory') if results: identifiers_and_descriptors.extend(results) results = root.find(ns + 'pdbx_chem_comp_descriptorCategory') if results: identifiers_and_descriptors.extend(results) for child in identifiers_and_descriptors: program = child.get('program').replace(' ', '_') type_ = child.get('type').replace(' ', '_') dict_[program + '_' + type_] = child[0].text dict_[program + '_version'] = child.get('program_version') dict_['audits'] = [ (audit.get('action_type'), audit.get('date')) for audit in list(root.find(ns + 'pdbx_chem_comp_auditCategory')) ] atoms = list(root.find(ns + 'chem_comp_atomCategory')) n_atoms = len(atoms) ideal_coords = np.zeros((n_atoms, 3)) model_coords = np.zeros((n_atoms, 3)) atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype) elements = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['element'].dtype) resnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['resname'].dtype) charges = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype) resnums = np.ones(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype) alternate_atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype) leaving_atom_flags = np.zeros(n_atoms, np.bool) aromatic_flags = np.zeros(n_atoms, np.bool) stereo_configs = np.zeros(n_atoms, np.bool) ordinals = np.zeros(n_atoms, int) name2index = {} for i, atom in enumerate(atoms): data = dict([(child.tag[len_ns:], child.text) for child in list(atom)]) name = data.get('pdbx_component_atom_id', 'X') name2index[name] = i atomnames[i] = name elements[i] = data.get('type_symbol', 'X') resnames[i] = data.get('pdbx_component_comp_id', 'UNK') charges[i] = float(data.get('charge', 0)) alternate_atomnames[i] = data.get('alt_atom_id', 'X') leaving_atom_flags[i] = data.get('pdbx_leaving_atom_flag') == 'Y' aromatic_flags[i] = data.get('pdbx_atomatic_flag') == 'Y' stereo_configs[i] = data.get('pdbx_stereo_config') == 'Y' ordinals[i] = int(data.get('pdbx_ordinal', 0)) model_coords[i, 0] = float(data.get('model_Cartn_x', 0)) model_coords[i, 1] = float(data.get('model_Cartn_y', 0)) model_coords[i, 2] = float(data.get('model_Cartn_z', 0)) ideal_coords[i, 0] = float(data.get('pdbx_model_Cartn_x_ideal', 0)) ideal_coords[i, 1] = float(data.get('pdbx_model_Cartn_y_ideal', 0)) ideal_coords[i, 2] = float(data.get('pdbx_model_Cartn_z_ideal', 0)) pdbid = dict_.get('model_coordinates_db_code') if pdbid: model = AtomGroup(cci + ' model ({0})'.format(pdbid)) else: model = AtomGroup(cci + ' model') model.setCoords(model_coords) model.setNames(atomnames) model.setResnames(resnames) model.setResnums(resnums) model.setElements(elements) model.setCharges(charges) model.setFlags('leaving_atom_flags', leaving_atom_flags) model.setFlags('aromatic_flags', aromatic_flags) model.setFlags('stereo_configs', stereo_configs) model.setData('ordinals', ordinals) model.setData('alternate_atomnames', alternate_atomnames) dict_['model'] = model ideal = model.copy() ideal.setTitle(cci + ' ideal') ideal.setCoords(ideal_coords) dict_['ideal'] = ideal bonds = [] warned = set() for bond in list(root.find(ns + 'chem_comp_bondCategory') or bonds): name_1 = bond.get('atom_id_1') name_2 = bond.get('atom_id_2') try: bonds.append((name2index[name_1], name2index[name_2])) except KeyError: if name_1 not in warned and name_1 not in name2index: warned.add(name_1) LOGGER.warn('{0} specified {1} in bond category is not ' 'a valid atom name.'.format(repr(name_1), cci)) if name_2 not in warned and name_2 not in name2index: warned.add(name_2) LOGGER.warn('{0} specified {1} in bond category is not ' 'a valid atom name.'.format(repr(name_2), cci)) if bonds: bonds = np.array(bonds, int) model.setBonds(bonds) ideal.setBonds(bonds) return dict_
def parseNMD(filename, type=NMA): """Returns :class:`.NMA` and :class:`.AtomGroup` instances storing data parsed from *filename* in :file:`.nmd` format. Type should be :class:`.NMA` or a subclass such as :class:`.PCA`, :class:`.ANM`, or :class:`.GNM`.""" if isinstance(type, str): type = type.upper().strip() if 'ANM' in type: type = ANM elif 'GNM' in type: type = GNM elif 'PCA' in type or 'EDA' in type: type = PCA elif type == 'NMA': type = NMA else: type = None if not issubclass(type, NMA): raise TypeError('type must be NMA, ANM, GNM, or PCA') atomic = {} atomic.update([(label, None) for label in NMD_LABEL_MAP]) atomic['coordinates'] = None atomic['name'] = None modes = [] with open(filename) as nmd: for i, line in enumerate(nmd): try: label, data = line.split(None, 1) except ValueError: pass if label == 'mode': modes.append((i + 1, data)) elif label in atomic: if atomic[label] is None: atomic[label] = (i + 1, data) else: LOGGER.warn('Data label {0} is found more than once in ' '{1}.'.format(repr(label), repr(filename))) name = atomic.pop('name', '')[1].strip() or splitext(split(filename)[1])[0] ag = AtomGroup(name) dof = None n_atoms = None line, coords = atomic.pop('coordinates', None) if coords is not None: coords = np.fromstring(coords, dtype=float, sep=' ') dof = coords.shape[0] if dof % 3 != 0: LOGGER.warn('Coordinate data in {0} at line {1} is corrupt ' 'and will be omitted.'.format(repr(filename), line)) else: n_atoms = dof // 3 coords = coords.reshape((n_atoms, 3)) ag.setCoords(coords) from prody.atomic import ATOMIC_FIELDS for label, data in atomic.items(): # PY3K: OK if data is None: continue line, data = data data = data.split() if n_atoms is None: n_atoms = len(data) dof = n_atoms * 3 elif len(data) != n_atoms: LOGGER.warn('Data with label {0} in {1} at line {2} is ' 'corrupt, expected {2} values, parsed {3}.'.format( repr(label), repr(filename), line, n_atoms, len(data))) continue label = NMD_LABEL_MAP[label] data = np.array(data, dtype=ATOMIC_FIELDS[label].dtype) ag.setData(label, data) if not modes: return None, ag length = len(modes[0][1].split()) is3d = length > n_atoms + 2 if dof is None: dof = length - (length % 3) elif not is3d: # GNM dof = n_atoms array = np.zeros((dof, len(modes))) less = 0 eigvals = [] count = 0 for i, (line, mode) in enumerate(modes): mode = np.fromstring(mode, dtype=float, sep=' ') diff = len(mode) - dof if diff < 0 or diff > 2: LOGGER.warn('Mode data in {0} at line {1} is corrupt.'.format( repr(filename), line)) continue array[:, i - less] = mode[diff:] count += 1 eigvals.append(mode[:diff]) if count == 0: return None, ag try: eigvals = np.array(eigvals, dtype=float) except TypeError: LOGGER.warn('Failed to parse eigenvalues from {0}.'.format( repr(filename))) if eigvals.shape[1] > 2: LOGGER.warn('Failed to parse eigenvalues from {0}.'.format( repr(filename))) eigvals = None elif eigvals.shape[1] == 1: if np.all(eigvals % 1 == 0): LOGGER.warn('Failed to parse eigenvalues from {0}.'.format( repr(filename))) eigvals = None else: eigvals = eigvals.flatten()**2 else: eigvals = eigvals[:, 1]**2 nma = type(name) if type != PCA: eigvals = 1. / eigvals if count != array.shape[1]: array = array[:, :count].copy() nma.setEigens(array, eigvals) return nma, ag
def parseNMD(filename, type=None): """Return :class:`.NMA` and :class:`.AtomGroup` instances storing data parsed from *filename* in :file:`.nmd` format. Type of :class:`.NMA` instance, e.g. :class:`.PCA`, :class:`.ANM`, or :class:`.GNM` will be determined based on mode data.""" assert not isinstance(type, NMA), 'type must be NMA, ANM, GNM, or PCA' atomic = {} atomic.update([(label, None) for label in NMD_LABEL_MAP]) atomic['coordinates'] = None atomic['name'] = None modes = [] with open(filename) as nmd: for i, line in enumerate(nmd): try: label, data = line.split(None, 1) except ValueError: pass if label == 'mode': modes.append((i + 1, data)) elif label in atomic: if atomic[label] is None: atomic[label] = (i + 1, data) else: LOGGER.warn('Data label {0} is found more than once in ' '{1}.'.format(repr(label), repr(filename))) name = atomic.pop('name', '')[1].strip() or splitext(split(filename)[1])[0] ag = AtomGroup(name) dof = None n_atoms = None line, coords = atomic.pop('coordinates', None) if coords is not None: coords = np.fromstring(coords, dtype=float, sep=' ') dof = coords.shape[0] if dof % 3 != 0: LOGGER.warn('Coordinate data in {0} at line {1} is corrupt ' 'and will be omitted.'.format(repr(filename), line)) else: n_atoms = dof / 3 coords = coords.reshape((n_atoms, 3)) ag.setCoords(coords) from prody.atomic import ATOMIC_FIELDS for label, data in atomic.items(): # PY3K: OK if data is None: continue line, data = data data = data.split() if n_atoms is None: n_atoms = len(data) dof = n_atoms * 3 elif len(data) != n_atoms: LOGGER.warn('Data with label {0} in {1} at line {2} is ' 'corrupt, expected {2} values, parsed {3}.'.format( repr(label), repr(filename), line, n_atoms, len(data))) continue label = NMD_LABEL_MAP[label] data = np.array(data, dtype=ATOMIC_FIELDS[label].dtype) ag.setData(label, data) if not modes: return None, ag length = len(modes[0][1].split()) is3d = length > n_atoms + 2 if dof is None: dof = length - (length % 3) elif not is3d: # GNM dof = n_atoms array = np.zeros((dof, len(modes))) less = 0 eigvals = [] count = 0 for i, (line, mode) in enumerate(modes): mode = np.fromstring(mode, dtype=float, sep=' ') diff = len(mode) - dof if diff < 0 or diff > 2: LOGGER.warn('Mode data in {0} at line {1} is corrupt.' .format(repr(filename), line)) continue array[:, i - less] = mode[diff:] count += 1 eigvals.append(mode[:diff]) if count == 0: return None, ag try: eigvals = np.array(eigvals, dtype=float) except TypeError: LOGGER.warn('Failed to parse eigenvalues from {0}.' .format(repr(filename))) if eigvals.shape[1] > 2: LOGGER.warn('Failed to parse eigenvalues from {0}.' .format(repr(filename))) eigvals = None elif eigvals.shape[1] == 1: if np.all(eigvals % 1 == 0): LOGGER.warn('Failed to parse eigenvalues from {0}.' .format(repr(filename))) eigvals = None else: eigvals = eigvals.flatten() ** 2 else: eigvals = eigvals[:, 1] ** 2 if is3d: if eigvals is not None and np.all(eigvals[:-1] >= eigvals[1:]): nma = PCA(name) else: nma = ANM(name) else: nma = GNM(name) if count != array.shape[1]: array = array[:, :count].copy() nma.setEigens(array, eigvals) return nma, ag