def changeLoop(filename, loopname):
posted=request.get_json(force=True)
if posted["action"]=="change" and posted["method"]=="random":
sm=get_sm(filename)
sm.load_sampled_elems()
if loopname not in sm.bg.coords:
abort(404)
original_cg=copy.deepcopy(sm.bg)
new_filename=get_new_filename()
smCache.renameSM(filename, new_filename)
change_elem(sm, loopname)
cg=sm.bg
centroid0 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(original_cg))
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(original_cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
filename=get_new_filename()
cg.to_cg_file("user_files/"+filename)
return jsonify({"url": url_for("structure_main", filename=filename)})
else:
abort(403)
def changeLoop(filename, loopname):
posted = request.get_json(force=True)
if posted["action"] == "change" and posted["method"] == "random":
sm = get_sm(filename)
sm.load_sampled_elems()
if loopname not in sm.bg.coords:
abort(404)
original_cg = copy.deepcopy(sm.bg)
new_filename = get_new_filename()
smCache.renameSM(filename, new_filename)
change_elem(sm, loopname)
cg = sm.bg
centroid0 = ftuv.get_vector_centroid(
ftug.bg_virtual_residues(original_cg))
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(original_cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
filename = get_new_filename()
cg.to_cg_file("user_files/" + filename)
return jsonify({"url": url_for("structure_main", filename=filename)})
else:
abort(403)
def align_rnas(rnas):
crds0 = rnas[0].get_ordered_virtual_residue_poss()
centroid0 = ftuv.get_vector_centroid(crds0)
print(centroid0)
rnas[0].rotate_translate(centroid0, ftuv.identity_matrix)
crds0 -= centroid0
assert ftuv.magnitude(
ftuv.get_vector_centroid(crds0)) < 10**-5, ftuv.magnitude(
ftuv.get_vector_centroid(crds0))
assert ftuv.magnitude(
ftuv.get_vector_centroid(rnas[0].get_ordered_virtual_residue_poss())
) < 10**-5, ftuv.get_vector_centroid(
rnas[0].get_ordered_virtual_residue_poss())
for rna in rnas[1:]:
crds1 = rna.get_ordered_virtual_residue_poss()
centroid1 = ftuv.get_vector_centroid(crds1)
crds1 -= centroid1
rot_mat = ftms.optimal_superposition(crds0, crds1)
rna.rotate_translate(centroid1, rot_mat)
assert ftuv.magnitude(
ftuv.get_vector_centroid(crds1)) < 10**-5, ftuv.magnitude(
ftuv.get_vector_centroid(crds1))
assert ftuv.magnitude(
ftuv.get_vector_centroid(rna.get_ordered_virtual_residue_poss())
) < 10**-5, ftuv.magnitude(
ftuv.get_vector_centroid(rna.get_ordered_virtual_residue_poss()))
def replace_base(res_dir, res_ref):
'''
Orient res_ref so that it points in the same direction
as res_dir.
@param res_dir: The residue indicating the direction
@param res_ref: The reference residue to be rotated
@return res: A residue with the atoms of res_ref pointing in the direction of res_dir
'''
#av = { 'U': ['N1', 'C6', 'C2'], 'C': ['N1', 'C6', 'C2'], 'A': ['N9', 'C4', 'C8'], 'G': ['N9', 'C4', 'C8'] }
av = { 'U': ['N1', "C1'", "C2'"], 'C': ['N1', "C1'", "C2'"], 'A': ['N9', "C1'", "C2'"], 'G': ['N9', "C1'", "C2'"], 'rU': ['N1', "C1'", "C2'"], 'rC': ['N1', "C1'", "C2'"], 'rA': ['N9', "C1'", "C2'"], 'rG': ['N9', "C1'", "C2'"] }
dv = av[res_dir.resname.strip()]
rv = av[res_ref.resname.strip()]
dir_points = np.array([res_dir[v].get_vector().get_array() for v in dv])
ref_points = np.array([res_ref[v].get_vector().get_array() for v in rv])
dir_centroid = cuv.get_vector_centroid(dir_points)
ref_centroid = cuv.get_vector_centroid(ref_points)
#sup = brmsd.optimal_superposition(dir_points - dir_centroid, ref_points - ref_centroid)
sup = brmsd.optimal_superposition(ref_points - ref_centroid, dir_points - dir_centroid)
new_res = res_ref.copy()
for atom in new_res:
atom.transform(np.eye(3,3), -ref_centroid)
atom.transform(sup, dir_centroid)
return new_res
def align_cgs(cgs):
'''
Align each coarse grain RNA to the first one.
The points representing each coarse grain RNA molecule
will be the virtual residues.
@param cgs: A list of CoarseGrainRNA structures.
@return: Nothing, the cgs are modified in place
'''
centroid0 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cgs[0]))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cgs[0]))
for cg in cgs:
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
def align_starts(chain_stems, chain_loop, handles, end=0, reverse=False):
'''
Align the sugar rings of one part of the stem structure to one part
of the loop structure.
@param chain_stems: The chain containing the stems
@param chain_loop: The chain containing the sampled loop
@param handles: The indexes into the stem and loop for the overlapping residues.
'''
v1 = []
v2 = []
for handle in handles:
if end == 0:
v1 += get_alignment_vectors(chain_stems, handle[0], handle[1])
v2 += get_alignment_vectors(chain_loop, handle[2], handle[3])
elif end == 2:
if reverse:
# used for aligning the 5' region, the back of which needs
# to be aligned to the beginning of the stem
v1 = (chain_stems[handle[1]]["C4'"].get_vector().get_array(),
chain_stems[handle[1]]["C3'"].get_vector().get_array(),
chain_stems[handle[1]]["O3'"].get_vector().get_array())
v2 = (chain_loop[handle[3]]["C4'"].get_vector().get_array(),
chain_loop[handle[3]]["C3'"].get_vector().get_array(),
chain_loop[handle[3]]["O3'"].get_vector().get_array())
else:
v1 = (chain_stems[handle[0]]["C4'"].get_vector().get_array(),
chain_stems[handle[0]]["C3'"].get_vector().get_array(),
chain_stems[handle[0]]["O3'"].get_vector().get_array())
v2 = (chain_loop[handle[2]]["C4'"].get_vector().get_array(),
chain_loop[handle[2]]["C3'"].get_vector().get_array(),
chain_loop[handle[2]]["O3'"].get_vector().get_array())
else:
v1 += get_measurement_vectors(chain_stems, handle[0], handle[1])
v2 += get_measurement_vectors(chain_loop, handle[2], handle[3])
#v1_m = get_measurement_vectors_rosetta(chain_stems, handle[0], handle[1])
#v2_m = get_measurement_vectors_barnacle(chain_loop, handle[2], handle[3])
v1_centroid = cuv.get_vector_centroid(v1)
v2_centroid = cuv.get_vector_centroid(v2)
v1_t = v1 - v1_centroid
v2_t = v2 - v2_centroid
sup = brmsd.optimal_superposition(v2_t, v1_t)
#v2_mt = v2_m - v2_centroid
#v2_rmt = np.dot(sup.transpose(), v2_mt.transpose()).transpose()
#v1_rmt = v1_m - v1_centroid
#rmsd = cuv.vector_set_rmsd(v1_rmt, v2_rmt)
for atom in bpdb.Selection.unfold_entities(chain_loop, 'A'):
atom.transform(np.eye(3,3), -v2_centroid)
atom.transform(sup, v1_centroid)
def test_center_on_centroid(self):
coords = [[0., 1., 1.], [1, 1, 1], [-1, 2, 3], [3, 0, 0], [-3, 1, 0]]
nptest.assert_almost_equal(
ftuv.center_on_centroid(np.array(coords)),
[[0, 0., 0], [1, 0, 0], [-1, 1, 2], [3, -1, -1], [-3, 0, -1]])
nptest.assert_equal(
ftuv.get_vector_centroid(ftuv.center_on_centroid(coords)),
[0, 0., 0])
def align_residues(res_dir, res_ref, on=None):
'''
Orient res_ref so that it points in the same direction
as res_dir.
:param res_dir: The residue indicating the direction
:param res_ref: The reference residue to be rotated
:return res: A residue with the atoms of res_ref pointing in the direction of res_dir
'''
#TODO: BT: In the future we might align based on ALL non-sidechain atoms
# using optimal_superposition.
# If we stick to 3 reference atoms, we could use
# ftuv.get_double_alignment_matrix instead.
if on is None:
av = {
'U': ['N1', "C1'", "C2'"],
'C': ['N1', "C1'", "C2'"],
'A': ['N9', "C1'", "C2'"],
'G': ['N9', "C1'", "C2'"],
'rU': ['N1', "C1'", "C2'"],
'rC': ['N1', "C1'", "C2'"],
'rA': ['N9', "C1'", "C2'"],
'rG': ['N9', "C1'", "C2'"]
}
else:
av = defaultdict(lambda: on)
dv = av[res_dir.resname.strip()]
rv = av[res_ref.resname.strip()]
dir_points = np.array([res_dir[v].coord for v in dv])
ref_points = np.array([res_ref[v].coord for v in rv])
dir_centroid = cuv.get_vector_centroid(dir_points)
ref_centroid = cuv.get_vector_centroid(ref_points)
sup = brmsd.optimal_superposition(ref_points - ref_centroid,
dir_points - dir_centroid)
new_res = res_ref.copy()
for atom in new_res:
atom.transform(np.eye(3, 3), -ref_centroid)
atom.transform(sup, dir_centroid)
return new_res
def align_source_to_target_fragment(target_chain, source_chain, sm, angle_def, ld):
'''
Align a PDB chain to the position where it is supposed to
bridge the gap between two stems.
@param target_chain: The chain the fragment is to be inserted into
@param source_chain: The chain from which the fragment comes
@param sm: The SpatialModel being reconstructed
@param angle_def: The define containing the residue numbers in source_chain
@param ld: The name of the fragment.
'''
connections = sm.bg.connections(ld)
(s1b, s1e) = sm.bg.get_sides(connections[0], ld)
#(s2b, s2e) = sm.bg.get_sides(connections[1], ld)
(sd, bd) = sm.bg.get_sides_plus(connections[0], ld)
t_v = (target_chain[sm.bg.defines[connections[0]][sd]]["C3'"].get_vector().get_array(),
target_chain[sm.bg.defines[connections[0]][sd]]["C4'"].get_vector().get_array(),
target_chain[sm.bg.defines[connections[0]][sd]]["O4'"].get_vector().get_array())
s_v = (source_chain[angle_def.define[bd]]["C3'"].get_vector().get_array(),
source_chain[angle_def.define[bd]]["C4'"].get_vector().get_array(),
source_chain[angle_def.define[bd]]["O4'"].get_vector().get_array())
t_centroid = cuv.get_vector_centroid(t_v)
s_centroid = cuv.get_vector_centroid(s_v)
t_v1 = t_v - t_centroid
s_v1 = s_v - s_centroid
sup = brmsd.optimal_superposition(s_v1, t_v1)
for atom in bpdb.Selection.unfold_entities(source_chain, 'A'):
atom.transform(np.eye(3,3), -s_centroid)
atom.transform(sup, t_centroid)
pass
def align_rnas(rnas):
crds0 = rnas[0].get_ordered_virtual_residue_poss()
centroid0 = ftuv.get_vector_centroid(crds0)
print(centroid0)
rnas[0].rotate_translate(centroid0, ftuv.identity_matrix)
crds0-=centroid0
assert ftuv.magnitude(ftuv.get_vector_centroid(crds0))<10**-5, ftuv.magnitude(ftuv.get_vector_centroid(crds0))
assert ftuv.magnitude(ftuv.get_vector_centroid(rnas[0].get_ordered_virtual_residue_poss()))<10**-5, ftuv.get_vector_centroid(rnas[0].get_ordered_virtual_residue_poss())
for rna in rnas[1:]:
crds1 = rna.get_ordered_virtual_residue_poss()
centroid1 = ftuv.get_vector_centroid(crds1)
crds1-=centroid1
rot_mat = ftms.optimal_superposition(crds0, crds1)
rna.rotate_translate(centroid1, rot_mat)
assert ftuv.magnitude(ftuv.get_vector_centroid(crds1))<10**-5, ftuv.magnitude(ftuv.get_vector_centroid(crds1))
assert ftuv.magnitude(ftuv.get_vector_centroid(rna.get_ordered_virtual_residue_poss()))<10**-5, ftuv.magnitude(ftuv.get_vector_centroid(rna.get_ordered_virtual_residue_poss()))
#! /usr/bin/python
import forgi.threedee.model.coarse_grain as ftmc
import fess.builder.models as fbm
import forgi.threedee.utilities.vector as ftuv
import forgi.threedee.utilities.graph_pdb as ftug
import sys
if __name__=="__main__":
filename=sys.argv[1]
print ("BUILDSTRUCTURE: Filename is ", filename)
cg=ftmc.CoarseGrainRNA(filename)
print ("BUILDSTRUCTURE: cg is ", cg)
sm=fbm.SpatialModel(cg)
print ("BUILDSTRUCTURE: sampling ")
sm.sample_stats()
print ("BUILDSTRUCTURE: traverse and build ")
sm.traverse_and_build()
print("BUILDSTRUCTURE: Writing File")
centroid0 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(sm.bg))
for k in cg.coords.keys():
cg.coords[k] = ((cg.coords[k][0] - centroid0),
(cg.coords[k][1] - centroid0))
sm.bg.to_cg_file(filename)
print ("BUILDSTRUCTURE: DONE")
def test_center_on_centroid(self):
coords = [[0., 1., 1.], [1, 1, 1], [-1, 2, 3], [3, 0, 0], [-3, 1, 0]]
nptest.assert_almost_equal(ftuv.center_on_centroid(np.array(coords)),
[[0, 0., 0], [1, 0, 0], [-1, 1, 2], [3, -1, -1], [-3, 0, -1]])
nptest.assert_equal(ftuv.get_vector_centroid(
ftuv.center_on_centroid(coords)), [0, 0., 0])