InSty - changes in calcStatisticsInteractions

prody/proteins/interactions.py

@@ -163,14 +163,13 @@ def get_energy(pair, source):
     try:
         # Python 3
         with pkg_resources.path('prody.proteins', 'tabulated_energies.txt') as file_path:
-            data = np.loadtxt(file_path, skiprows=1, dtype=str)
+            data = np.loadtxt(file_path, dtype=str)
     except: 
         # Python 2.7
         import pkg_resources
         file_path = pkg_resources.resource_filename('prody.proteins', 'tabulated_energies.txt')
         with open(file_path) as f:
-            data = np.loadtxt(f, skiprows=1, dtype=str)
-
+            data = np.loadtxt(f, dtype=str)
 
     sources = ["IB_nosolv", "IB_solv", "CS"]
     aa_pairs = []
@@ -180,21 +179,32 @@ def get_energy(pair, source):
 
     lookup = pair[0]+pair[1]
 
-    return data[np.where(np.array(aa_pairs)==lookup)[0]][0][2:][np.where(np.array(sources)==source)][0]
+    try:
+        data_results = data[np.where(np.array(aa_pairs)==lookup)[0]][0][2:][np.where(np.array(sources)==source)][0]
+    except ImportError:
+        raise ImportError('Please replace non-standard names of residues with standard names.')
+
+    return data_results
 
 
 def showPairEnergy(data, **kwargs):
     """Return energies when a list of interactions is given. Energies will be added to each pair of residues 
     at the last position in the list. Energy is based on the residue types and not on the distances.
-    The unit of energy is kcal/mol. The energies defined as 'IB_nosolv', 'IB_solv' are taken from XX and 
-    'CS' from YY.
+    The unit of energy is kcal/mol. The energies defined as 'IB_nosolv', 'IB_solv' are taken from [OK98]_ and 
+    'CS' from InSty paper.
 
     :arg data: list with interactions from calcHydrogenBonds() or other types
     :type data: list
 
     :arg energy_list_type: name of the list with energies 
                             default is 'IB_solv'
     :type energy_list_type: 'IB_nosolv', 'IB_solv', 'CS'
+
+
+    .. [OK98] Keskin O., Bahar I., Badretdinov A.Y., Ptitsyn O.B., Jernigan R.L., 
+    Empirical solvet-mediated potentials hold for both intra-molecular and 
+    inter-molecular inter-residues interactions,
+    *Protein Science* **1998** 7: 2578–2586.
     """
 
     if not isinstance(data, list):
@@ -1988,12 +1998,20 @@ def calcStatisticsInteractions(data, **kwargs):
     for element in elements:
         if element not in stats:
             values = [t[1] for t in interactions_list if t[0] == element]
-            stats[element] = {
-                "stddev": np.round(np.std(values),6),
-                "mean": np.round(np.mean(values),6),
-                "weight": np.round(float(len(values))/len(data), 6),
-                "energy": get_energy([element.split('-')[0][:3], element.split('-')[1][:3]], energy_list_type)
-            }
+
+            try:
+                stats[element] = {
+                    "stddev": np.round(np.std(values),6),
+                    "mean": np.round(np.mean(values),6),
+                    "weight": np.round(float(len(values))/len(data), 6),
+                    "energy": get_energy([element.split('-')[0][:3], element.split('-')[1][:3]], energy_list_type)
+                }
+            except:
+                stats[element] = {
+                    "stddev": np.round(np.std(values),6),
+                    "mean": np.round(np.mean(values),6),
+                    "weight": np.round(float(len(values))/len(data), 6)
+                }
 
     statistic = []
     for key, value in stats.items():
@@ -2002,8 +2020,11 @@ def calcStatisticsInteractions(data, **kwargs):
             LOGGER.info("  Average [Ang.]: {}".format(value['mean']))
             LOGGER.info("  Standard deviation [Ang.]: {0}".format(value['stddev']))
             LOGGER.info("  Weight: {0}".format(value['weight']))
-            LOGGER.info("  Energy [kcal/mol]: {0}".format(value['energy']))
-            statistic.append([key, value['weight'], value['mean'], value['stddev'], value['energy']])
+            try:
+                LOGGER.info("  Energy [kcal/mol]: {0}".format(value['energy']))
+                statistic.append([key, value['weight'], value['mean'], value['stddev'], value['energy']])
+            except:
+                statistic.append([key, value['weight'], value['mean'], value['stddev']])
         else: pass
 
     statistic.sort(key=lambda x: x[1], reverse=True)

prody/proteins/tabulated_energies.txt

@@ -398,3 +398,120 @@ PRO LYS 0.3	-0.5	0.0
 PRO ARG -0.17	-2.43	0.0
 PRO HIS 0.33	-1.8	0.0
 PRO PRO -0.03	-0.83	0.0
+GLY HSE 0.01	-2.47	0.0
+ALA HSE 0.01	-3.29	0.0
+VAL HSE -0.23	-4.14	-1.1
+ILE HSE -0.02	-4.55	-1.1
+LEU HSE 0.25	-4.85	-1.1
+CYS HSE -0.64	-4.79	-0.8
+MET HSE -0.17	-4.47	-0.5
+PHE HSE 0.79	-3.82	-0.6
+TYR HSE 0.34	-3.78	-1.1
+TRP HSE -0.05	-4.5	-1.7
+SER HSE -0.38	-3.12	-0.5
+THR HSE -0.05	-2.73	-0.5
+ASP HSE 0.0	-2.93	-0.4
+ASN HSE -0.52	-3.05	-1.2
+GLU HSE -0.1	-3.15	-0.4
+GLN HSE -0.31	-4.2	-1.2
+LYS HSE -0.01	-2.14	0.0
+ARG HSE 0.35	-3.24	-0.4
+HSE GLY 0.01	-2.47	0.0
+HSE ALA 0.01	-3.29	0.0
+HSE VAL -0.23	-4.14	-1.1
+HSE ILE -0.02	-4.55	-1.1
+HSE LEU 0.25	-4.85	-1.1
+HSE CYS -0.64	-4.79	-0.8
+HSE MET -0.17	-4.47	-0.5
+HSE PHE 0.79	-3.82	-0.6
+HSE TYR 0.34	-3.78	-1.1
+HSE TRP -0.05	-4.5	-1.7
+HSE SER -0.38	-3.12	-0.5
+HSE THR -0.05	-2.73	-0.5
+HSE ASP 0.0	-2.93	-0.4
+HSE ASN -0.52	-3.05	-1.2
+HSE GLU -0.1	-3.15	-0.4
+HSE GLN -0.31	-4.2	-1.2
+HSE LYS -0.01	-2.14	0.0
+HSE ARG 0.35	-3.24	-0.4
+HSE HSE 0.38	-3.08	-0.5
+HSE PRO 0.33	-1.8	0.0
+PRO HSE 0.33	-1.8	0.0
+GLY HSD 0.01	-2.47	0.0
+ALA HSD 0.01	-3.29	0.0
+VAL HSD -0.23	-4.14	-1.1
+ILE HSD -0.02	-4.55	-1.1
+LEU HSD 0.25	-4.85	-1.1
+CYS HSD -0.64	-4.79	-0.8
+MET HSD -0.17	-4.47	-0.5
+PHE HSD 0.79	-3.82	-0.6
+TYR HSD 0.34	-3.78	-1.1
+TRP HSD -0.05	-4.5	-1.7
+SER HSD -0.38	-3.12	-0.5
+THR HSD -0.05	-2.73	-0.5
+ASP HSD 0.0	-2.93	-0.4
+ASN HSD -0.52	-3.05	-1.2
+GLU HSD -0.1	-3.15	-0.4
+GLN HSD -0.31	-4.2	-1.2
+LYS HSD -0.01	-2.14	0.0
+ARG HSD 0.35	-3.24	-0.4
+HSD GLY 0.01	-2.47	0.0
+HSD ALA 0.01	-3.29	0.0
+HSD VAL -0.23	-4.14	-1.1
+HSD ILE -0.02	-4.55	-1.1
+HSD LEU 0.25	-4.85	-1.1
+HSD CYS -0.64	-4.79	-0.8
+HSD MET -0.17	-4.47	-0.5
+HSD PHE 0.79	-3.82	-0.6
+HSD TYR 0.34	-3.78	-1.1
+HSD TRP -0.05	-4.5	-1.7
+HSD SER -0.38	-3.12	-0.5
+HSD THR -0.05	-2.73	-0.5
+HSD ASP 0.0	-2.93	-0.4
+HSD ASN -0.52	-3.05	-1.2
+HSD GLU -0.1	-3.15	-0.4
+HSD GLN -0.31	-4.2	-1.2
+HSD LYS -0.01	-2.14	0.0
+HSD ARG 0.35	-3.24	-0.4
+HSD HSD 0.38	-3.08	-0.5
+HSD PRO 0.33	-1.8	0.0
+PRO HSD 0.33	-1.8	0.0
+GLY HSP 0.01	-2.47	0.0
+ALA HSP 0.01	-3.29	0.0
+VAL HSP -0.23	-4.14	-1.1
+ILE HSP -0.02	-4.55	-1.1
+LEU HSP 0.25	-4.85	-1.1
+CYS HSP -0.64	-4.79	-0.8
+MET HSP -0.17	-4.47	-0.5
+PHE HSP 0.79	-3.82	-0.6
+TYR HSP 0.34	-3.78	-1.1
+TRP HSP -0.05	-4.5	-1.7
+SER HSP -0.38	-3.12	-0.5
+THR HSP -0.05	-2.73	-0.5
+ASP HSP 0.0	-2.93	-0.4
+ASN HSP -0.52	-3.05	-1.2
+GLU HSP -0.1	-3.15	-0.4
+GLN HSP -0.31	-4.2	-1.2
+LYS HSP -0.01	-2.14	0.0
+ARG HSP 0.35	-3.24	-0.4
+HSP GLY 0.01	-2.47	0.0
+HSP ALA 0.01	-3.29	0.0
+HSP VAL -0.23	-4.14	-1.1
+HSP ILE -0.02	-4.55	-1.1
+HSP LEU 0.25	-4.85	-1.1
+HSP CYS -0.64	-4.79	-0.8
+HSP MET -0.17	-4.47	-0.5
+HSP PHE 0.79	-3.82	-0.6
+HSP TYR 0.34	-3.78	-1.1
+HSP TRP -0.05	-4.5	-1.7
+HSP SER -0.38	-3.12	-0.5
+HSP THR -0.05	-2.73	-0.5
+HSP ASP 0.0	-2.93	-0.4
+HSP ASN -0.52	-3.05	-1.2
+HSP GLU -0.1	-3.15	-0.4
+HSP GLN -0.31	-4.2	-1.2
+HSP LYS -0.01	-2.14	0.0
+HSP ARG 0.35	-3.24	-0.4
+HSP HSP 0.38	-3.08	-0.5
+HSP PRO 0.33	-1.8	0.0
+PRO HSP 0.33	-1.8	0.0