Did you know that you can do a Löwdin orthogonalization by a singular value decomposition? Usually, when I hear Löwdin orthogonalization, I think of some weird S1/2 matrix, which scares me and I tend to stay away from it... But this pdf from the University of Oregon claims that you can do it in a different way. And it seems to work.
Say you have a matrix A and you want an orthogonal matrix that resembles it as closely as possible. What do you do? First you do a singular value decomposition of A:
Selecting full residues within a certain distance of another residue or atom in PyMOL - Note to self: To select all atoms in a residue (plus any HETATMs) that is within 3 Å of any atom in residue 63 type: select br. all within 3 of resi 63 ...
11 hours ago