I have made the function called sup to superimpose 2 protein-like PDB superimpose class :

from NumPy import *
from NumPy.linalg import svd, det


# Test data
# Coordinate vectors along with columns 

a=matrix([[ 18.92238689,  9.18841188,  8.70764463,  9.38130981, 8.53057997],
         [ 1.12391951,  0.8707568 ,  1.01214183,  0.59383894, 0.65155349],
         [ 0.46106398,  0.62858099, -0.02625641,  0.35264203, 0.53670857]], 'f')

b=matrix([[ 1.68739355,  1.38774297,  2.1959675 , 1.51248281,  1.70793414],
         [ 8.99726755,  8.73213223,  8.86804272, 8.31722197,  8.9924607 ],
         [ 1.1668153 ,  1.1135669 ,  1.02279055, 1.06534992,  0.54881902]], 'f')

# Code

def center(m):
   # Returns centered m
   # Calculate center of mass of x
   center_of_mass_m=m.sum(1)/m.shape[1]
   # Center m
   centered_m=m-center_of_mass_m
   return centered_m


def sup(x, y):
    # Nr of atoms
    N=x.shape[1]

    ########################

    # Center x and y
    x=center(x)
    y=center(y)

    # correlation matrix
    r=y*x.T

    # SVD of correlation matrix
    v, s, wt=svd(r)

    w=wt.T
    vt=v.T

    # Rotation matrix
    u=w*vt

    # Check for roto-reflection
    if det(u)<0:
        z=diag((1,1,-1))
        u=w*z*vt
        s[2]=-s[2]

    # Calculate RMSD
    e0=sum(x.A*x.A+y.A*y.A)
    print("E0 ", e0)
    rmsd=sqrt((e0-2*sum(s))/N)

    print('RMSD (svd) ', rmsd)

    print("u estimated ")
    print(u)

    # Calculate RMSD from the coordinates 
    d=x-u*y
    d=d.A*d.A
    rmsd=sqrt(sum(d)/N)
    print('RMSD (real) ', rmsd)

if __name__=="__main__":

    # Run some stuff

    # 1. Test data
    sup(a,b)

    # 2. Protein

    # Parse PDB file
    from Bio.PDB import *
    p=PDBParser()
    s=p.get_structure("XXX", "2NIC.pdb")

    # Chain A in model 0
    chain1=s[0]["A"]
    # Chain A in model 1
    chain2=s[0]["A"]

    def get_coordinates(chain):
        # Get the CA coordinates of a cahin and return 3xn matrix
        coords=[]
        for res in chain:
            try:
                # Extract CA coordinate
                a=res["CA"]
                c=a.get_coord()
                coords.append(c)
            except:
                # No CA atom - skip
                pass
        # Turn coordinate list in 3xn numpy matrix
        coords=matrix(coords) # nx3
        coords=coords.T       # 3xn
        return coords

    # Get the 3xn coordinate matrices for the chains
    a=get_coordinates(chain1)
    b=get_coordinates(chain2)

    # Superimpose and done
    sup(a,b)

Now I need to make another by utilizing this sup function to download 2 PDB files from the PDB database and then superimposes the 2nd to the first one based on the backbone atoms(N, C alpha, C,0) of the amino acids specified the list of residue numbers. The function should save the rotated and translated structure in a separate PDB file

I am trying this script :

import numpy as np
import Bio
from Bio.PDB import * 

# Select what residues numbers you wish to align # and put them in a list
start_id = 1
end_id   = 70
atoms_to_be_aligned = range(start_id, end_id + 1)

def superimpose():
    pdb_code_1= "1d3z"
    pdb_filename_1 = "%s.pdb" % pdb_code_1
    pdb_out_filename = "%s_aligned.pdb" % pdb_code_1
    pdb_code_2= "1ubq"
    pdb_filename_2 = "%s.pdb" % pdb_code_2
    # Start the parser
    pdb_parser = Bio.PDB.PDBParser(QUIET = True)
    # Get the structures
    ref_structure = pdb_parser.get_structure("reference", pdb_filename_1)
    sample_structure = pdb_parser.get_structure("sample", pdb_filename_2)
    # Use the first model in the pdb-files for alignment
    # Change the number 0 if you want to align to another structure
    ref_model    = ref_structure[0]
    sample_model = sample_structure[0]
    # Make a list of the atoms (in the structures) you wish to align.
    # In this case we use CA atoms whose index is in the specified range
    list_res_1 = []
    list_res_2 = []
    ref_atoms = []  
    sample_atoms = []
    # Iterate of all chains in the model in order to find all residues
    for ref_chain in ref_model:
        # Iterate of all residues in each model in order to find proper atoms
        for ref_res in ref_chain:
            # Check if residue number ( .get_id() ) is in the list
            if ref_res.get_id()[1] in atoms_to_be_aligned:
                # Append CA atom to list
                ref_atoms.append(ref_res['O'])
                # Do the same for the sample structure
                for sample_chain in sample_model:
                    for sample_res in sample_chain:
                        if sample_res.get_id()[1] in atoms_to_be_aligned:
                            sample_atoms.append(sample_res['O'])
                            # Now we initiate the superimposer:
                            #super_imposer = Bio.PDB.Superimposer()
                            sup(ref_atoms, sample_atoms)
                            sup(sample_model.get_atoms())
                            # Print RMSD:
                            print (list_res_1,list_res2)

superimpose()

But it is giving me an error :

AttributeError                            Traceback (most recent call last)
<ipython-input-30-58f50b4768f7> in <module>()
     49                             print (list_res_1,list_res2)
     50 
---> 51 superimpose()

<ipython-input-30-58f50b4768f7> in superimpose()
     44                             # Now we initiate the superimposer:
     45                             #super_imposer = Bio.PDB.Superimposer()
---> 46                             sup(ref_atoms, sample_atoms)
     47                             sup(sample_model.get_atoms())
     48                             # Print RMSD:

<ipython-input-11-e7d76316a1c0> in sup(x, y)
     27 def sup(x, y):
     28     # Nr of atoms
---> 29     N=x.shape[1]
     30 
     31     ########################

AttributeError: 'list' object has no attribute 'shape'

Can anyone help me plz?