fix issue 285

polyply/data/martini3/citations.bib

@@ -56,3 +56,11 @@ @article{M3_PDMS
  year={2022},
  publisher={Royal Society of Chemistry}
 }
+
+@article{M3_GO,
+title={GōMartini 3: From large conformational changes in proteins to environmental bias corrections},
+author={Souza, Paulo C. T. and Araujo, Luis P. Borges and Brasnett, Chris and Moreira, Rodrigo A. and Grunewald, Fabian and Park, Peter and Wang, Liguo and Razmazma, Hafez and Borges-Araujo, Ana C. and Cofas-Vargas, Luis F. and Monticelli, Luca and Mera-Adasme, Raul and Melo, Manuel N. and Wu, Sangwook and Marrink, Siewert J. and Poma, Adolfo B. and Thallmair, Sebastian},
+url={https://www.biorxiv.org/content/10.1101/2024.04.15.589479v1},
+doi={10.1101/2024.04.15.589479},
+year={2024},
+}

polyply/src/generate_templates.py

@@ -174,19 +174,23 @@ def compute_volume(block, coords, nonbond_params, treshold=1e-18):
  res_center_of_geometry = center_of_geometry(points)
  geom_vects = np.zeros((n_atoms, 3))
  idx = 0
-
+ radii = []
  for node, coord in coords.items():
  atom_key = block.nodes[node]["atype"]
  rad = float(nonbond_params[frozenset([atom_key, atom_key])]["nb1"])
  diff = coord - res_center_of_geometry
  if np.linalg.norm(diff) > treshold:
  geom_vects[idx, :] = diff + u_vect(diff) * rad
  idx += 1
-
- if geom_vects.shape[0] > 1:
+ else:
+ radii.append(rad)
+ # make sure geom_vects is not just an array of zeros
+ # this can happen when multiple beads are stacked for
+ # example
+ if np.any(geom_vects):
  radgyr = radius_of_gyration(geom_vects)
  else:
- radgyr = rad
+ radgyr = max(radii)
 
  return radgyr
 

polyply/src/minimizer.py

@@ -166,7 +166,7 @@ def optimize_geometry(block, coords, inter_types=[], tolerance={"angles": 5,
  """
  n_atoms = len(coords)
  atom_to_idx = OrderedDict(zip(list(coords.keys()), range(0, n_atoms)))
- positions = np.array(list(coords.values()))
+ positions = np.ravel(np.array(list(coords.values())))
 
  def target_function(positions):
  energy = 0
@@ -183,7 +183,8 @@ def target_function(positions):
  energy += new
  return energy
 
- opt_results = scipy.optimize.minimize(target_function, positions, method='L-BFGS-B',
+ opt_results = scipy.optimize.minimize(target_function, positions,
+ method='L-BFGS-B',
  options={'ftol': 0.001, 'maxiter': 100})
 
  # evaluate if optimization was successful

polyply/tests/test_data/library_tests/martini3/PROT/PNt.fasta

@@ -0,0 +1,2 @@
+> PNt PROTEIN
+DWNNQSIVKTGERQHGIHIQGSDPGGVRTASGTTIKVSGRQAQGILLENPAAELQFRNGSVTSSGQLSDDGIRRFLGTVTVKAGKLVADHATLANVGDTWDDDGIALYVAGEQAQASIADSTLQGAGGVQIERGANVTVQRSAIVDGGLHIGALQSLQPEDLPPSRVVLRDTNVTAVPASGAPAAVSVLGASELTLDGGHITGGRAAGVAAMQGAVVHLQRATIRRGDALAGGAVPGGAVPGGAVPGGFGPGGFGPVLDGWYGVDVSGSSVELAQSIVEAPELGAAIRVGRGARVTVPGGSLSAPHGNVIETGGARRFAPQAAPLSITLQAGAH