fix alignBioPairwise for new biopython

[jamesmkrieger]

This fixes some of the issues around #2205. This doesn't fix all my problems but it does fix alignChains with match_func=sameChid.

With Biopython 1.79, we always used to get full alignments with enough gaps:

In [1]: import prody

In [2]: import Bio

In [3]: Bio.__version__
Out[3]: '1.79'

In [4]: prody_ref_model = prody.parsePDB("ref_model.pdb")
@> 2243 atoms and 1 coordinate set(s) were parsed in 0.02s.

In [5]: prody_model = prody.parsePDB("centered_model.pdb")
@> 2280 atoms and 1 coordinate set(s) were parsed in 0.01s.

In [6]: target = list(prody_model.getHierView())[3]

In [7]: chain = list(prody_ref_model.getHierView())[3]

In [8]: from prody.utilities import MATCH_SCORE, MISMATCH_SCORE, GAP_PENALTY, GAP_EXT_PENALTY, ALIGNMENT_METHOD, alignBioPairwise

In [9]:             alignments = alignBioPairwise(target.getSequence(),
   ...:                                           chain.getSequence()[3:],
   ...:                                           "local",
   ...:                                           MATCH_SCORE, MISMATCH_SCORE,
   ...:                                           GAP_PENALTY,  GAP_EXT_PENALTY,
   ...:                                           max_alignments=1)

In [10]: alignments
Out[10]: 
[('KKRFEVKKWNAVALWAWDIVNCAICRNHIMDLCIECQANQASATSEECTVAWGVCNHAFHFHCISRWLKTRQVCPLDNREWE',
  '---FEVKKWNAVALWAWDIVV-------------------------------------------------------------',
  17.0,
  3,
  19)]

With Biopython 1.80 and onwards, this didn't happen anymore and that's what broke alignChains.

In [1]: from prody.utilities import MATCH_SCORE, MISMATCH_SCORE, GAP_PENALTY, GAP_EXT_PENALTY, ALIGNMENT_METHOD, alignBioPairwise

In [2]: import prody

In [3]: prody_model = prody.parsePDB("centered_model.pdb")
@> 2280 atoms and 1 coordinate set(s) were parsed in 0.02s.

In [4]: prody_ref_model = prody.parsePDB("ref_model.pdb")
@> 2243 atoms and 1 coordinate set(s) were parsed in 0.02s.

In [5]: target = list(prody_model.getHierView())[3]

In [6]: chain = list(prody_ref_model.getHierView())[3]

In [7]:             alignments = alignBioPairwise(target.getSequence(),
   ...:                                           chain.getSequence()[3:],
   ...:                                           "local",
   ...:                                           MATCH_SCORE, MISMATCH_SCORE,
   ...:                                           GAP_PENALTY,  GAP_EXT_PENALTY,
   ...:                                           max_alignments=1)

In [8]: alignments
Out[8]: [('FEVKKWNAVALWAWDIV', 'FEVKKWNAVALWAWDIV', 17.0, '3', '20')]

With the fix, this is restored.

In [1]: import prody

In [2]: prody_model = prody.parsePDB("centered_model.pdb")
@> 2280 atoms and 1 coordinate set(s) were parsed in 0.02s.

In [3]: prody_ref_model = prody.parsePDB("ref_model.pdb")
@> 2243 atoms and 1 coordinate set(s) were parsed in 0.02s.

In [4]: from prody.utilities import MATCH_SCORE, MISMATCH_SCORE, GAP_PENALTY, GAP_EXT_PENALTY, ALIGNMENT_METHOD, alignBioPairwise

In [5]: target = list(prody_model.getHierView())[3]

In [6]: chain = list(prody_ref_model.getHierView())[3]

In [7]:             alignments = alignBioPairwise(target.getSequence(),
   ...:                                           chain.getSequence()[3:],
   ...:                                           "local",
   ...:                                           MATCH_SCORE, MISMATCH_SCORE,
   ...:                                           GAP_PENALTY,  GAP_EXT_PENALTY,
   ...:                                           max_alignments=1)

In [8]: alignments
Out[8]: 
[('KKRFEVKKWNAVALWAWDIVNCAICRNHIMDLCIECQANQASATSEECTVAWGVCNHAFHFHCISRWLKTRQVCPLDNREWE',
  '---FEVKKWNAVALWAWDIV--------------------------------------------------------------',
  17.0,
  3,
  20)]

In [4]: prody_ref_amap = prody.alignChains(prody_ref_model, prody_model, overlap=15, match_func=prody.sameChid)
@> Trying to map atoms based on residue numbers and identities:
@>   Comparing Chain A from ref_model (len=1132) with Chain A from centered_model:
@>      Mapped: 1132 residues match with 100% sequence identity and 99% overlap.
@> Trying to map atoms based on residue numbers and identities:
@>   Comparing Chain B from ref_model (len=381) with Chain B from centered_model:
@>      Mapped: 346 residues match with 100% sequence identity and 99% overlap.
@> Trying to map atoms based on residue numbers and identities:
@>   Comparing Chain E from ref_model (len=709) with Chain E from centered_model:
@>      Mapped: 709 residues match with 100% sequence identity and 100% overlap.
@> Trying to map atoms based on residue numbers and identities:
@>   Comparing Chain F from ref_model (len=21) with Chain F from centered_model:
@> Trying to map atoms based on local sequence alignment:
@>   Comparing Chain F from ref_model (len=21) with Chain F from centered_model:
@>      Mapped: 21 residues match with 95% sequence identity and 26% overlap.
@> Finding the atommaps based on their coverages...
@> Identified that there exists 1 atommap(s) potentially.

In [5]: prody_ref_amap
Out[5]: [<AtomMap: (Chain F from ref_model -> Chain F from centered_model) + (Chain E from ref_model -> Chain E from centered_model) + (Chain B from ref_model -> Chain B from centered_model) + (Chain A from ref_model -> Chain A from centered_model) from ref_model (2280 atoms, 2208 mapped, 72 dummy)>]

[jamesmkrieger]

This isn't right. It only handles the case where the target is longer