def get_msms_df(model,
pdb_file,
outfile=None,
outdir=None,
outext='_msms.df',
force_rerun=False):
"""Run MSMS (using Biopython) on a Biopython Structure Model and the path to the actual PDB file.
Returns a dictionary of:
{chain_id: {resnum1_id: (res_depth, ca_depth)},
{resnum2_id: (res_depth, ca_depth)} }
Depths are in units Angstroms. 1A = 10^-10 m = 1nm
Args:
model: Biopython Structure Model
pdb_file: Path to PDB file
Returns:
Pandas DataFrame: ResidueDepth property_dict, reformatted
"""
# Create the output file name
outfile = ssbio.utils.outfile_maker(inname=pdb_file,
outname=outfile,
outdir=outdir,
outext=outext)
if ssbio.utils.force_rerun(flag=force_rerun, outfile=outfile):
# Run MSMS with Biopython
try:
rd = PDB.ResidueDepth(model, pdb_file)
except AssertionError:
log.error('{}: unable to run MSMS'.format(pdb_file))
return pd.DataFrame()
# Reorganize the results into a csv file
appender = []
for k in rd.property_keys:
x = rd.property_dict[k]
chain = k[0]
residue = k[1]
het = residue[0]
resnum = residue[1]
icode = residue[2]
resdepth = x[0]
cadepth = x[1]
appender.append((chain, resnum, icode, resdepth, cadepth))
df = pd.DataFrame.from_records(
appender,
columns=['chain', 'resnum', 'icode', 'res_depth', 'ca_depth'])
df.to_csv(outfile)
else:
log.debug(
'{}: already ran MSMS and force_rerun={}, loading results'.format(
outfile, force_rerun))
df = pd.read_csv(outfile, index_col=0)
return df
def get_msms_df(model, pdb_id, outfile=None, outdir=None, outext='_msms.df', force_rerun=False):
"""Run MSMS (using Biopython) on a Biopython Structure Model.
Depths are in units Angstroms. 1A = 10^-10 m = 1nm. Returns a dictionary of::
{
chain_id:{
resnum1_id: (res_depth, ca_depth),
resnum2_id: (res_depth, ca_depth)
}
}
Args:
model: Biopython Structure Model
Returns:
Pandas DataFrame: ResidueDepth property_dict, reformatted
"""
# XTODO: need to deal with temporary surface/vertex files in tmp directory when running on a large scale --
# XTODO: will run into inode limits! Also, some valuable information is in these MSMS output files that we should save.
# Create the output file name
outfile = ssbio.utils.outfile_maker(inname=pdb_id, outname=outfile, outdir=outdir, outext=outext)
if ssbio.utils.force_rerun(flag=force_rerun, outfile=outfile):
# Run MSMS with Biopython
try:
rd = PDB.ResidueDepth(model)
except AssertionError:
log.error('{}: unable to run MSMS'.format(pdb_id))
return pd.DataFrame()
# Reorganize the results into a csv file
appender = []
for k in rd.property_keys:
x = rd.property_dict[k]
chain = k[0]
residue = k[1]
het = residue[0]
resnum = residue[1]
icode = residue[2]
resdepth = x[0]
cadepth = x[1]
appender.append((chain, resnum, icode, resdepth, cadepth))
df = pd.DataFrame.from_records(appender, columns=['chain', 'resnum', 'icode', 'res_depth', 'ca_depth'])
df.to_csv(outfile)
else:
log.debug('{}: already ran MSMS and force_rerun={}, loading results'.format(outfile, force_rerun))
df = pd.read_csv(outfile, index_col=0)
return df
def cal_depth(s, aa_list_full):
depth = PDB.ResidueDepth(s) #氨基酸到蛋白质表面距离
dep_dict = depth.property_dict
dps = []
for a in aa_list_full:
try:
aa_id = (a.get_parent().get_id(), a.get_id())
if dep_dict.get(aa_id):
dps.append(dep_dict[aa_id])
else:
dps.append([None, None])
except:
dps.append([None, None])
dps = np.array(dps)
return dps
def cal(i):
print(pdbid[i],pdbchain[i])
pdb_name='pdb_/pdb'+pdbid[i].lower()+'.ent' #pdb name
try:
s = p.get_structure("1",pdb_name) #read pdb struture
s = s[0][pdbchain[i]] #choose chain
res_list = PDB.Selection.unfold_entities(s, 'R') #read aminoacid
except:
return 0
aa_list = []
for a in res_list:
if PDB.is_aa(a):
aa_list.append(a) #get acid
error=0
t=aa_list[0].get_id()[1]
aa_list_full=[]
for a in aa_list:
while 1:
if a.get_id()[1]<t:
error=1
break
if a.get_id()[1]==t:
aa_list_full.append(a)
t+=1
break
else:
aa_list_full.append(None)
t+=1
if error==1:
return 0
try:
depth=PDB.ResidueDepth(s) #氨基酸到蛋白质表面距离
except:
return 0
dep_dict=depth.property_dict
dep_keys=depth.property_keys
dep_list=depth.property_list
dps=[]
for a in aa_list_full:
try:
aa_id=(a.get_parent().get_id(),a.get_id())
if dep_dict.get(aa_id):
dps.append(dep_dict[aa_id])
else:
dps.append([None,None])
except:
dps.append([None,None])
dps=np.array(dps)
try:
HSEA=PDB.HSExposureCA(s)
except:
return 0
HSEA_dict=HSEA.property_dict
HSEA_keys=HSEA.property_keys
HSEA_list=HSEA.property_list
hse_a=[]
for a in aa_list_full:
try:
aa_id=(a.get_parent().get_id(),a.get_id())
if HSEA_dict.get(aa_id):
hse_a.append(HSEA_dict[aa_id])
else:
hse_a.append([None,None,None])
except:
hse_a.append([None,None,None])
hse_a=np.array(hse_a)
try:
HSEB=PDB.HSExposureCB(s)
except:
return 0
HSEB_dict=HSEB.property_dict
HSEB_keys=HSEB.property_keys
HSEB_list=HSEB.property_list
hse_b=[]
for a in aa_list_full:
try:
aa_id=(a.get_parent().get_id(),a.get_id())
if HSEB_dict.get(aa_id):
hse_b.append(HSEB_dict[aa_id])
else:
hse_b.append([None,None,None])
except:
hse_b.append([None,None,None])
hse_b=np.array(hse_b)
seq_list=''
for a in aa_list_full:
try:
t=a.get_resname()
if t in t_dic:
seq_list+=t_dic[t]
else:
seq_list+='X'
except:
seq_list+='X'
ca_list=[]
for a in aa_list_full:
try:
t=a['CA']
ca_list.append(t)
except:
t=None
ca_list.append(t)
cb_list=[]
for a in aa_list_full:
try:
t=a['CB']
cb_list.append(t)
except:
t=None
cb_list.append(t)
n_list=[]
for a in aa_list_full:
try:
t=a['N']
n_list.append(t)
except:
t=None
n_list.append(t)
c_list=[]
for a in aa_list_full:
try:
t=a['C']
c_list.append(t)
except:
t=None
c_list.append(t)
angle=[] #三个角两个氨基酸相对位置
for j in range(len(ca_list)):
angle_t=[]
for k in range(len(ca_list)):
if ca_list[j]!=None and ca_list[k]!=None:
ca1=ca_list[j].get_vector()
ca2=ca_list[k].get_vector()
if cb_list[j]!=None:
cb=cb_list[j].get_vector()
t1=PDB.vectors.calc_angle(cb,ca1,ca2)
else:
if c_list[j]!=None and n_list[j]!=None and ca_list[j]!=None:
ca_v=ca_list[j].get_vector().get_array()
c_v=c_list[j].get_vector().get_array()
n_v=n_list[j].get_vector().get_array()
cb=calha1(n_v,c_v,ca_v)
cb=PDB.vectors.Vector(cb)
t1=PDB.vectors.calc_angle(cb,ca1,ca2)
else:
t1=None
if n_list[j]!=None:
n_=n_list[j].get_vector()
t2=PDB.vectors.calc_angle(n_,ca1,ca2)
else:
t2=None
if c_list[j]!=None:
c_=c_list[j].get_vector()
t3=PDB.vectors.calc_angle(c_,ca1,ca2)
else:
t3=None
angle_t.append([t1,t2,t3])
else:
angle_t.append([None,None,None])
angle.append(angle_t)
angle_d=[] #六个角
for j in range(len(angle)):
angle_dt=[]
for k in range(len(angle[j])):
angle_dt.append(angle[j][k]+angle[k][j])
angle_d.append(angle_dt)
angle_d=np.array(angle_d)
ca_num=len(ca_list)
ca_dist=[] #CA距离
for j in range(len(ca_list)):
for k in range(len(ca_list)):
if ca_list[j]!=None and ca_list[k]!=None:
ca_dist.append(ca_list[j]-ca_list[k])
else:
ca_dist.append(None)
ca_dist=np.array(ca_dist)
ca_dist=ca_dist.reshape(ca_num,ca_num)
mask=[] #是否有CA
for j in range(len(ca_list)):
if ca_list[j]!=None:
mask.append(1)
else:
mask.append(0)
ids=ca_dist==None
ca_dist[ids]=100 #算不出来距离的设置为100
ca_dist_cs=[]
angle_cs=[]
num_cs=[]
for j in range(len(ca_dist)):
t=ca_dist[j]
s=t.argsort()
ca_dist_cs.append(t[s[1:17]])
angle_cs.append(angle_d[j][s[1:17]])
num_cs.append(s[1:17])
dic_r={}
dic_r['dis']=ca_dist_cs
dic_r['angle']=angle_cs
dic_r['mask']=mask
dic_r['ids']=num_cs
dic_r['seq']=seq_list
dic_r['dps']=dps
dic_r['hsea']=hse_a
dic_r['hseb']=hse_b
out_name='pdb_other_cb/'+pdbid[i].lower()+pdbchain[i]+'_all.npy'
np.save(out_name,dic_r)
res_name = [res.get_resname() for res in aa_list]
HSEA = PDB.HSExposureCA(s)
HSEA_dict = HSEA.property_dict
HSEA_keys = HSEA.property_keys
HSEA_list = HSEA.property_list
HSEB = PDB.HSExposureCB(s)
HSEB_dict = HSEB.property_dict
HSEB_keys = HSEB.property_keys
HSEB_list = HSEB.property_list
depth = PDB.ResidueDepth(s)
dep_dict = depth.property_dict
dep_keys = depth.property_keys
dep_list = depth.property_list
dssp = PDB.DSSP(s, "3skpFH.pdb")
dssp_dict = dssp.property_dict
nb_dict = {}
nb = PDB.NeighborSearch(ca_list)
for a in ca_list:
t = nb.search(a.get_coord(), 8)
aa = a.get_parent()
aa_id = (aa.get_parent().get_id(), aa.get_id())
nb_dict[aa_id] = t
def get_dis(name):
p = PDBParser(PERMISSIVE=1)
pdb_name = name
try:
s = p.get_structure("X", pdb_name)
s = s[0]
except:
return None, None, None, None, None, None, None, None
res_list = PDB.Selection.unfold_entities(s, 'R')
aa_list = []
for a in res_list:
if PDB.is_aa(a):
aa_list.append(a)
t = aa_list[0].get_id()[1]
aa_list_full = []
error = 0
for a in aa_list:
while 1:
if a.get_id()[1] < t:
error = 1
break
if a.get_id()[1] == t:
aa_list_full.append(a)
t += 1
break
else:
aa_list_full.append(None)
t += 1
if error == 1:
return None, None, None, None, None, None, None, None
try:
depth = PDB.ResidueDepth(s)
except:
return None, None, None, None, None, None, None, None
dep_dict = depth.property_dict
dep_keys = depth.property_keys
dep_list = depth.property_list
dps = []
for a in aa_list_full:
try:
aa_id = (a.get_parent().get_id(), a.get_id())
if dep_dict.get(aa_id):
dps.append(dep_dict[aa_id])
else:
dps.append([None, None])
except:
dps.append([None, None])
dps = np.array(dps)
try:
HSEA = PDB.HSExposureCA(s)
except:
return None, None, None, None, None, None, None, None
HSEA_dict = HSEA.property_dict
HSEA_keys = HSEA.property_keys
HSEA_list = HSEA.property_list
hse_a = []
for a in aa_list_full:
try:
aa_id = (a.get_parent().get_id(), a.get_id())
if HSEA_dict.get(aa_id):
hse_a.append(HSEA_dict[aa_id])
else:
hse_a.append([None, None, None])
except:
hse_a.append([None, None, None])
hse_a = np.array(hse_a)
try:
HSEB = PDB.HSExposureCB(s)
except:
return None, None, None, None, None, None, None, None
HSEB_dict = HSEB.property_dict
HSEB_keys = HSEB.property_keys
HSEB_list = HSEB.property_list
hse_b = []
for a in aa_list_full:
try:
aa_id = (a.get_parent().get_id(), a.get_id())
if HSEB_dict.get(aa_id):
hse_b.append(HSEB_dict[aa_id])
else:
hse_b.append([None, None, None])
except:
hse_b.append([None, None, None])
hse_b = np.array(hse_b)
seq_list = ''
for a in aa_list_full:
try:
t = a.get_resname()
if t in t_dic:
seq_list += t_dic[t]
else:
seq_list += 'X'
except:
seq_list += 'X'
ca_list = []
for a in aa_list_full:
try:
t = a['CA']
ca_list.append(t)
except:
t = None
ca_list.append(t)
cb_list = []
for a in aa_list_full:
try:
t = a['CB']
cb_list.append(t)
except:
t = None
cb_list.append(t)
n_list = []
for a in aa_list_full:
try:
t = a['N']
n_list.append(t)
except:
t = None
n_list.append(t)
c_list = []
for a in aa_list_full:
try:
t = a['C']
c_list.append(t)
except:
t = None
c_list.append(t)
angle = []
for j in range(len(ca_list)):
angle_t = []
for k in range(len(ca_list)):
if ca_list[j] != None and ca_list[k] != None:
ca1 = ca_list[j].get_vector()
ca2 = ca_list[k].get_vector()
if cb_list[j] != None:
cb = cb_list[j].get_vector()
t1 = PDB.vectors.calc_angle(cb, ca1, ca2)
else:
if c_list[j] != None and n_list[j] != None and ca_list[
j] != None:
ca_v = ca_list[j].get_vector().get_array()
c_v = c_list[j].get_vector().get_array()
n_v = n_list[j].get_vector().get_array()
cb = calha1(n_v, c_v, ca_v)
cb = PDB.vectors.Vector(cb)
t1 = PDB.vectors.calc_angle(cb, ca1, ca2)
else:
t1 = None
if n_list[j] != None:
n_ = n_list[j].get_vector()
t2 = PDB.vectors.calc_angle(n_, ca1, ca2)
else:
t2 = None
if c_list[j] != None:
c_ = c_list[j].get_vector()
t3 = PDB.vectors.calc_angle(c_, ca1, ca2)
else:
t3 = None
angle_t.append([t1, t2, t3])
else:
angle_t.append([None, None, None])
angle.append(angle_t)
angle_d = []
for j in range(len(angle)):
angle_dt = []
for k in range(len(angle[j])):
angle_dt.append(angle[j][k] + angle[k][j])
angle_d.append(angle_dt)
angle_d = np.array(angle_d)
ca_num = len(ca_list)
ca_dist = []
for j in range(len(ca_list)):
for k in range(len(ca_list)):
if ca_list[j] != None and ca_list[k] != None:
ca_dist.append(ca_list[j] - ca_list[k])
else:
ca_dist.append(None)
ca_dist = np.array(ca_dist)
ca_dist = ca_dist.reshape(ca_num, ca_num)
mask = []
for j in range(len(ca_list)):
if ca_list[j] != None:
mask.append(1)
else:
mask.append(0)
ids = ca_dist == None
ca_dist[ids] = 100
ca_dist_cs = []
angle_cs = []
num_cs = []
for j in range(len(ca_dist)):
t = ca_dist[j]
s = t.argsort()
ca_dist_cs.append(t[s[1:17]])
angle_cs.append(angle_d[j][s[1:17]])
num_cs.append(s[1:17])
return seq_list, num_cs, mask, ca_dist_cs, angle_cs, dps, hse_a, hse_b
