print("No grid file", pdb_id, site_id)
continue
elif os.path.isfile("%s/%s_ElectFeatures.txt"%(root_dir, pdb_id)) == False: #is there bluues electrostatics data?
print("No electro file", pdb_id, site_id)
continue
elif os.path.isfile("%s/%s.findgeo"%(root_dir, pdb_id)) == False: #is there findgeo/CMM data?
print("No geom file", pdb_id, site_id)
continue
else:
print(pdb_id, site_id)
chain = entry.chainID
if relax == True:
pdb_file = "%s_Relaxed.pdb"%pdb_id
else:
pdb_file = "%s.pdb"%pdb_id
residues, res_nums, header = pdbp.create_res("%s/%s"%(root_dir, pdb_file))
#print(res_nums)
this_protein = pdbp.Protein(residues, res_nums, header)
center_of_mass = np.mean(this_protein.Coords, axis = 0)
#print(center_of_mass)
metals = set([str(entry.seqNum1), str(entry.seqNum2), str(entry.seqNum3), str(entry.seqNum4)])
metal_res = []
for x in metals:
if x != "0": metal_res.append(str(round(float(x))) + chain )
metals = [entry.resName1, entry.resName2, entry.resName3, entry.resName4]
site_atom_count = 0
for x in metals:
if x != "0": site_atom_count += metal_size[x]
#general SITE info
if relaxed == "Relaxed":
pdb_id = pdb_id + "_Relaxed"
if os.path.isfile(
"/panfs/pfs.local/work/slusky/MSEAL/data/PDB_chains/%s/%s/%s/%s/%s.pdb"
% (pdb_id[0], pdb_id[1], pdb_id[0:6], relaxed,
pdb_id)) == False: #pdb_id[0], pdb_id[1],
#if os.path.isfile("SampleData/%s/UnRelaxed/%s.pdb"%(pdb_id, pdb_id) ) == False: #pdb_id[0], pdb_id[1],
continue
else:
print(pdb_id, metals)
chain = pdb_id[5]
metal_res = [str(x) + chain for x in metals]
#residues, res_nums, header = pdbp.create_res("SampleData/%s/UnRelaxed/%s.pdb"%(pdb_id, pdb_id)) #test on local
residues, res_nums, header = pdbp.create_res(
"/panfs/pfs.local/work/slusky/MSEAL/data/PDB_chains/%s/%s/%s/%s/%s.pdb"
% (pdb_id[0], pdb_id[1], pdb_id[0:6], relaxed,
pdb_id)) #for production run on CRC
#print(res_nums)
this_protein = pdbp.Protein(residues, res_nums, header)
SITE_center_pt = SITE_center(metal_res, this_protein)
index = entry.Index
site_list.loc[index, "X"] = SITE_center_pt[0]
site_list.loc[index, "Y"] = SITE_center_pt[1]
site_list.loc[index, "Z"] = SITE_center_pt[2]
site_list.loc[index,
"NearNeigh"] = nearest_neigh(SITE_center_pt,
metal_res, this_protein)
#print(site_list.loc[index,:])
site_list.to_csv("SITECenters_%s.txt" % relaxed, sep="\t", index=False)
