def exclude_h_on_SS(model):
rm = model.get_restraints_manager()
bond_proxies_simple, asu = rm.geometry.get_all_bond_proxies(
sites_cart=model.get_sites_cart())
els = model.get_hierarchy().atoms().extract_element()
ss_i_seqs = []
all_proxies = [p for p in bond_proxies_simple]
for proxy in asu:
all_proxies.append(proxy)
for proxy in all_proxies:
if (isinstance(proxy, ext.bond_simple_proxy)): i, j = proxy.i_seqs
elif (isinstance(proxy, ext.bond_asu_proxy)):
i, j = proxy.i_seq, proxy.j_seq
else:
assert 0 # never goes here
if ([els[i], els[j]
].count("S") == 2): # XXX may be coordinated if metal edits used
ss_i_seqs.extend([i, j])
sel_remove = flex.size_t()
for proxy in all_proxies:
if (isinstance(proxy, ext.bond_simple_proxy)): i, j = proxy.i_seqs
elif (isinstance(proxy, ext.bond_asu_proxy)):
i, j = proxy.i_seq, proxy.j_seq
else:
assert 0 # never goes here
if (els[i] in ["H", "D"] and j in ss_i_seqs): sel_remove.append(i)
if (els[j] in ["H", "D"] and i in ss_i_seqs): sel_remove.append(j)
return model.select(~flex.bool(model.size(), sel_remove))
def exclude_h_on_coordinated_S(model): # XXX if edits used it should be like in exclude_h_on_SS
rm = model.get_restraints_manager().geometry
els = model.get_hierarchy().atoms().extract_element()
# Find possibly coordinated S
exclusion_list = ["H","D","T","S","O","P","N","C","SE"]
sel_s = []
for proxy in rm.pair_proxies().nonbonded_proxies.simple:
i,j = proxy.i_seqs
if(els[i] == "S" and not els[j] in exclusion_list): sel_s.append(i)
if(els[j] == "S" and not els[i] in exclusion_list): sel_s.append(j)
# Find H attached to possibly coordinated S
bond_proxies_simple, asu = rm.get_all_bond_proxies(
sites_cart = model.get_sites_cart())
sel_remove = flex.size_t()
for proxy in bond_proxies_simple:
i,j = proxy.i_seqs
if(els[i] in ["H","D"] and j in sel_s): sel_remove.append(i)
if(els[j] in ["H","D"] and i in sel_s): sel_remove.append(j)
return model.select(~flex.bool(model.size(), sel_remove))
def stats(model, prefix, no_ticks=True):
# Get rid of H, multi-model, no-protein and single-atom residue models
if (model.percent_of_single_atom_residues() > 20):
return None
sel = model.selection(string="protein")
if (sel.count(True) == 0):
return None
ssr = "protein and not (element H or element D or resname UNX or resname UNK or resname UNL)"
sel = model.selection(string=ssr)
model = model.select(sel)
if (len(model.get_hierarchy().models()) > 1):
return None
# Add H; this looses CRYST1 !
rr = run_reduce_with_timeout(
stdin_lines=model.get_hierarchy().as_pdb_string().splitlines(),
file_name=None,
parameters="-oh -his -flip -keep -allalt -pen9999 -",
override_auto_timeout_with=None)
# Create model; this is a single-model pure protein with new H added
pdb_inp = iotbx.pdb.input(source_info=None, lines=rr.stdout_lines)
model = mmtbx.model.manager(model_input=None,
build_grm=True,
pdb_hierarchy=pdb_inp.construct_hierarchy(),
process_input=True,
log=null_out())
box = uctbx.non_crystallographic_unit_cell_with_the_sites_in_its_center(
sites_cart=model.get_sites_cart(), buffer_layer=5)
model.set_sites_cart(box.sites_cart)
model._crystal_symmetry = box.crystal_symmetry()
#
N = 10
SS = get_ss_selections(hierarchy=model.get_hierarchy())
HB_all = find(
model=model.select(flex.bool(model.size(), True)),
a_DHA_cutoff=90).get_params_as_arrays(replace_with_empty_threshold=N)
HB_alpha = find(
model=model.select(SS.both.h_sel),
a_DHA_cutoff=90).get_params_as_arrays(replace_with_empty_threshold=N)
HB_beta = find(
model=model.select(SS.both.s_sel),
a_DHA_cutoff=90).get_params_as_arrays(replace_with_empty_threshold=N)
print(HB_all.d_HA.size())
result_dict = {}
result_dict["all"] = HB_all
result_dict["alpha"] = HB_alpha
result_dict["beta"] = HB_beta
# result_dict["loop"] = get_selected(sel=loop_sel)
# Load histograms for reference high-resolution d_HA and a_DHA
pkl_fn = libtbx.env.find_in_repositories(
relative_path="mmtbx") + "/nci/d_HA_and_a_DHA_high_res.pkl"
assert os.path.isfile(pkl_fn)
ref = easy_pickle.load(pkl_fn)
#
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(10, 10))
kwargs = dict(histtype='bar', bins=20, range=[1.6, 3.0], alpha=.8)
for j, it in enumerate([["alpha", 1], ["beta", 3], ["all", 5]]):
key, i = it
ax = plt.subplot(int("32%d" % i))
if (no_ticks):
#ax.set_xticks([])
ax.set_yticks([])
if (j in [0, 1]):
ax.tick_params(bottom=False)
ax.set_xticklabels([])
ax.tick_params(axis="x", labelsize=12)
ax.tick_params(axis="y", labelsize=12, left=False, pad=-2)
ax.text(0.98,
0.92,
key,
size=12,
horizontalalignment='right',
transform=ax.transAxes)
HB = result_dict[key]
if HB is None: continue
w1 = np.ones_like(HB.d_HA) / HB.d_HA.size()
ax.hist(HB.d_HA, color="orangered", weights=w1, rwidth=0.3, **kwargs)
#
start, end1, end2 = 0, max(ref.distances[key].vals), \
round(max(ref.distances[key].vals),2)
if (not no_ticks):
plt.yticks([0.01, end1], ["0", end2],
visible=True,
rotation="horizontal")
if (key == "alpha"): plt.ylim(0, end2 + 0.02)
elif (key == "beta"): plt.ylim(0, end2 + 0.02)
elif (key == "all"): plt.ylim(0, end2 + 0.02)
else: assert 0
#
if (j == 0): ax.set_title("Distance", size=15)
bins = list(flex.double(ref.distances[key].bins))
ax.bar(bins, ref.distances[key].vals, alpha=.3, width=0.07)
#
kwargs = dict(histtype='bar', bins=20, range=[90, 180], alpha=.8)
for j, it in enumerate([["alpha", 2], ["beta", 4], ["all", 6]]):
key, i = it
ax = plt.subplot(int("32%d" % i))
if (j in [0, 1]):
ax.tick_params(bottom=False)
ax.set_xticklabels([])
if (no_ticks):
#ax.set_xticks([])
ax.set_yticks([])
ax.tick_params(axis="x", labelsize=12)
ax.tick_params(axis="y", labelsize=12, left=False, pad=-2)
ax.text(0.98,
0.92,
key,
size=12,
horizontalalignment='right',
transform=ax.transAxes)
ax.text(0.98,
0.92,
key,
size=12,
horizontalalignment='right',
transform=ax.transAxes)
#if(j in [0,1]): ax.plot_params(bottom=False)
HB = result_dict[key]
if HB is None: continue
w1 = np.ones_like(HB.a_DHA) / HB.a_DHA.size()
ax.hist(HB.a_DHA, color="orangered", weights=w1, rwidth=0.3, **kwargs)
#
start, end1, end2 = 0, max(ref.angles[key].vals), \
round(max(ref.angles[key].vals),2)
if (not no_ticks):
plt.yticks([0.01, end1], ["0", end2],
visible=True,
rotation="horizontal")
if (key == "alpha"): plt.ylim(0, end2 + 0.02)
elif (key == "beta"): plt.ylim(0, end2 + 0.02)
elif (key == "all"): plt.ylim(0, end2 + 0.02)
else: assert 0
#
if (j == 0): ax.set_title("Angle", size=15)
ax.bar(ref.angles[key].bins, ref.angles[key].vals, width=4.5, alpha=.3)
plt.subplots_adjust(wspace=0.12, hspace=0.025)
if (no_ticks):
plt.subplots_adjust(wspace=0.025, hspace=0.025)
#fig.savefig("%s.png"%prefix, dpi=1000)
fig.savefig("%s.pdf" % prefix)
