diff --git a/prody/dynamics/functions.py b/prody/dynamics/functions.py
index 0cdb961e3..e565101ba 100644
--- a/prody/dynamics/functions.py
+++ b/prody/dynamics/functions.py
@@ -512,7 +512,7 @@ def parseScipionModes(metadata_file, title=None, pdb=None, parseIndices=False):
 
 
 def writeScipionModes(output_path, modes, write_star=False, scores=None,
-                      only_sqlite=False, collectivityThreshold=0.):
+                      only_sqlite=False, collectivityThreshold=0., norm=True):
     """Writes *modes* to a set of files that can be recognised by Scipion.
     A directory called **"modes"** will be created if it doesn't already exist. 
     Filenames inside will start with **"vec"** and have the mode number as the extension.
@@ -538,6 +538,10 @@ def writeScipionModes(output_path, modes, write_star=False, scores=None,
     :arg collectivityThreshold: collectivity threshold below which modes are not enabled
         Default is 0.
     :type collectivityThreshold: float
+
+    :arg norm: whether to normalize mode vectors before calculating collectivities
+        Default is **True**
+    :type norm: bool
     """
     if not isinstance(output_path, str):
         raise TypeError('output_path should be a string, not {0}'
@@ -567,6 +571,10 @@ def writeScipionModes(output_path, modes, write_star=False, scores=None,
         raise TypeError('collectivityThreshold should be float, not {0}'
                         .format(type(collectivityThreshold)))
 
+    if not isinstance(norm, bool):
+        raise TypeError('norm should be boolean, not {0}'
+                        .format(type(norm)))    
+
     if modes.numModes() == 1 and not isinstance(modes, (NMA, ModeSet)):
         old_modes = modes
         modes = NMA(old_modes)
@@ -586,6 +594,12 @@ def writeScipionModes(output_path, modes, write_star=False, scores=None,
             modefiles.append(writeArray(modes_dir + 'vec.{0}'.format(mode_num),
                                         mode.getArray(), '%12.4e', ''))
 
+    if norm:
+        eigvecs = modes.getEigvecs()
+        eigvecs /= np.array([((evecs[:, i]) ** 2).sum() ** 0.5
+                             for i in range(evecs.shape[1])])
+        modes.setEigens(eigvecs, eigvals)
+
     if modes.numModes() > 1:
         order = modes.getIndices()
         collectivities = list(calcCollectivity(modes))