Merge branch 'prody:main' into prody-signint

prody/dynamics/clustenm.py

@@ -1076,7 +1076,7 @@ def run(self, cutoff=15., n_modes=3, gamma=1., n_confs=50, rmsd=1.0,
         self._sparse = kwargs.get('sparse', False)
         self._kdtree = kwargs.get('kdtree', False)
         self._turbo = kwargs.get('turbo', False)
-        self._nproc = kwargs.pop('nproc', None)
+        self._nproc = kwargs.pop('nproc', 0)
         if kwargs.get('zeros', False):
             LOGGER.warn('ClustENM cannot use zero modes so ignoring this kwarg')
 

prody/proteins/interactions.py

@@ -953,9 +953,11 @@ def calcChHydrogenBonds(atoms, **kwargs):
 
         ChainsHBs = [ i for i in HBS_calculations if str(i[2]) != str(i[5]) ]
         if not ChainsHBs:
-            ligand_name = list(set(atoms.select('all not protein and not ion').getResnames()))[0]
-            ChainsHBs = [ ii for ii in HBS_calculations if ii[0][:3] == ligand_name or ii[3][:3] == ligand_name ]
-
+            ligand_sel = atoms.select('all not protein and not ion')
+            if ligand_sel:
+                ligand_name = list(set(ligand_sel.getResnames()))[0]
+                ChainsHBs = [ ii for ii in HBS_calculations if ii[0][:3] == ligand_name or ii[3][:3] == ligand_name ]
+
         return ChainsHBs 
 
 
@@ -4398,8 +4400,43 @@ def saveInteractionsPDB(self, **kwargs):
             writePDB('filename', atoms, **kw)
             LOGGER.info('PDB file saved.')
 
-
-    def getFrequentInteractors(self, contacts_min=3):
+
+    def getInteractors(self, residue_name):
+        """ Provide information about interactions for a particular residue
+        
+        :arg residue_name: name of a resiude
+                            example: LEU234A, where A is a chain name
+        :type residue_name: str
+        """
+
+        atoms = self._atoms   
+        interactions = self._interactions
+
+        InteractionsMap = np.empty([atoms.select('name CA').numAtoms(),atoms.select('name CA').numAtoms()], dtype=object)
+        resIDs = list(atoms.select('name CA').getResnums())
+        resChIDs = list(atoms.select('name CA').getChids())
+        resIDs_with_resChIDs = list(zip(resIDs, resChIDs))
+        interaction_type = ['hb','sb','rb','ps','pc','hp','dibs']
+        ListOfInteractions = []
+
+        for nr,i in enumerate(interactions):
+            if i != []:
+                for ii in i: 
+                    m1 = resIDs_with_resChIDs.index((int(ii[0][3:]),ii[2]))
+                    m2 = resIDs_with_resChIDs.index((int(ii[3][3:]),ii[5]))
+                    ListOfInteractions.append(interaction_type[nr]+':'+ii[0]+ii[2]+'-'+ii[3]+ii[5])
+
+        aa_ListOfInteractions = []
+        for i in ListOfInteractions:
+            inter = i.split(":")[1:][0]
+            if inter.split('-')[0] == residue_name or inter.split('-')[1] == residue_name:
+                LOGGER.info(i)
+                aa_ListOfInteractions.append(i)
+
+        return aa_ListOfInteractions
+
+
+    def getFrequentInteractors(self, contacts_min=2):
         """Provide a list of residues with the most frequent interactions based 
         on the following interactions:
             (1) Hydrogen bonds (hb)
@@ -4411,7 +4448,7 @@ def getFrequentInteractors(self, contacts_min=3):
             (7) Disulfide bonds (disb)
         
         :arg contacts_min: Minimal number of contacts which residue may form with other residues, 
-                           by default 3.
+                           by default 2.
         :type contacts_min: int  """
 
         atoms = self._atoms   
@@ -4428,36 +4465,59 @@ def getFrequentInteractors(self, contacts_min=3):
                 for ii in i: 
                     m1 = resIDs_with_resChIDs.index((int(ii[0][3:]),ii[2]))
                     m2 = resIDs_with_resChIDs.index((int(ii[3][3:]),ii[5]))
-                    InteractionsMap[m1][m2] = interaction_type[nr]+':'+ii[0]+ii[2]+'-'+ii[3]+ii[5]
+
+                    if InteractionsMap[m1][m2] is None:
+                        InteractionsMap[m1][m2] = []
+
+                    InteractionsMap[m1][m2].append(interaction_type[nr] + ':' + ii[0] + ii[2] + '-' + ii[3] + ii[5])
 
-        ListOfInteractions = [ list(filter(None, InteractionsMap[:,j])) for j in range(len(interactions[0])) ]
-        ListOfInteractions = list(filter(lambda x : x != [], ListOfInteractions))
-        ListOfInteractions = [k for k in ListOfInteractions if len(k) >= contacts_min ]
-        ListOfInteractions_list = [ (i[0].split('-')[-1], [ j.split('-')[0] for j in i]) for i in ListOfInteractions ]
-        LOGGER.info('The most frequent interactions between:')
-        for res in ListOfInteractions_list:
+        ListOfInteractions = [list(filter(None, [row[j] for row in InteractionsMap])) for j in range(len(InteractionsMap[0]))]
+        ListOfInteractions = list(filter(lambda x: x != [], ListOfInteractions))
+        ListOfInteractions_flattened = [j for sublist in ListOfInteractions for j in sublist]
+
+        swapped_ListOfInteractions_list = []
+        for interaction_group in ListOfInteractions_flattened:
+            swapped_group = []
+            for interaction in interaction_group:
+                interaction_type, pair = interaction.split(':')
+                swapped_pair = '-'.join(pair.split('-')[::-1])
+                swapped_group.append("{}:{}".format(interaction_type, swapped_pair))
+            swapped_ListOfInteractions_list.append(swapped_group)
+
+        doubleListOfInteractions_list = ListOfInteractions_flattened+swapped_ListOfInteractions_list
+        ListOfInteractions_list = [(i[0].split('-')[-1], [j.split('-')[0] for j in i]) for i in doubleListOfInteractions_list]
+
+        merged_dict = {}
+        for aa, ii in ListOfInteractions_list:
+            if aa in merged_dict:
+                merged_dict[aa].extend(ii)
+            else:
+                merged_dict[aa] = ii
+
+        ListOfInteractions_list = [(key, value) for key, value in merged_dict.items()] 
+        ListOfInteractions_list2 = [k for k in ListOfInteractions_list if len(k[-1]) >= contacts_min]
+
+        for res in ListOfInteractions_list2:
             LOGGER.info('{0}  <--->  {1}'.format(res[0], '  '.join(res[1])))
 
-        LOGGER.info('Legend: hb-hydrogen bond, sb-salt bridge, rb-repulsive ionic bond, ps-Pi stacking interaction,'
-                             'pc-Cation-Pi interaction, hp-hydrophobic interaction, dibs-disulfide bonds')
+        LOGGER.info('\nLegend: hb-hydrogen bond, sb-salt bridge, rb-repulsive ionic bond, ps-Pi stacking interaction,'
+                             '\npc-Cation-Pi interaction, hp-hydrophobic interaction, dibs-disulfide bonds')
 
         try:
             from toolz.curried import count
         except ImportError:
             LOGGER.warn('This function requires the module toolz')
             return
 
-        LOGGER.info('The biggest number of interactions: {}'.format(max(map(count, ListOfInteractions))))
-
-        return ListOfInteractions_list
+        return ListOfInteractions_list2
 
 
-    def showFrequentInteractors(self, cutoff=5, **kwargs):
+    def showFrequentInteractors(self, cutoff=4, **kwargs):
         """Plots regions with the most frequent interactions.
         
         :arg cutoff: minimal score per residue which will be displayed.
                      If cutoff value is to big, top 30% with the higest values will be returned.
-                     Default is 5.
+                     Default is 4.
         :type cutoff: int, float
 
         Nonstandard resiudes can be updated in a following way:

prody/tests/proteins/test_insty.py

@@ -146,7 +146,7 @@ def testImportHpb(self):
             except ImportError:
                 imported_hpb = False
 
-        if sys.version_info[1] < 11:
+        if sys.version_info[1] < 13:
             self.assertTrue(imported_hpb)
         else:
             self.assertFalse(imported_hpb)

prody/utilities/catchall.py

@@ -739,6 +739,8 @@ def showMatrix(matrix, x_array=None, y_array=None, **kwargs):
         im = ax3.imshow(matrix, aspect=aspect, vmin=vmin, vmax=vmax,
                         norm=norm, cmap=cmap, origin=origin, **kwargs)
     else:
+        zeros_matrix = np.zeros(matrix.shape)
+        im = ax3.imshow(zeros_matrix, vmin=-1, vmax=1, cmap='seismic')
         plot_list = []
         for rows,cols in zip(np.where(matrix!=0)[0],np.where(matrix!=0)[1]):
             plot_list.append([cols,rows,matrix[rows,cols]])