Source code for MDAnalysis.analysis.align

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# doi: 10.25080/majora-629e541a-00e
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# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787

"""Coordinate fitting and alignment --- :mod:`MDAnalysis.analysis.align`

:Author: Oliver Beckstein, Joshua Adelman
:Year: 2010--2013
:Copyright: GNU Public License v3

The module contains functions to fit a target structure to a reference
structure. They use the fast QCP algorithm to calculate the root mean
square distance (RMSD) between two coordinate sets [Theobald2005]_ and
the rotation matrix *R* that minimizes the RMSD [Liu2010]_. (Please
cite these references when using this module.).

Typically, one selects a group of atoms (such as the C-alphas),
calculates the RMSD and transformation matrix, and applys the
transformation to the current frame of a trajectory to obtain the
rotated structure. The :func:`alignto` and :class:`AlignTraj`
functions can be used to do this for individual frames and
trajectories respectively.

The :ref:`RMS-fitting-tutorial` shows how to do the individual steps
manually and explains the intermediate steps.

See Also
     contains functions to compute RMSD (when structural alignment is not
     implements the fast RMSD algorithm.

.. _RMS-fitting-tutorial:

RMS-fitting tutorial

The example uses files provided as part of the MDAnalysis test suite
(in the variables :data:`~MDAnalysis.tests.datafiles.PSF`,
:data:`~MDAnalysis.tests.datafiles.DCD`, and
:data:`~MDAnalysis.tests.datafiles.PDB_small`). For all further
examples execute first ::

   >>> import MDAnalysis as mda
   >>> from MDAnalysis.analysis import align
   >>> from MDAnalysis.analysis.rms import rmsd
   >>> from MDAnalysis.tests.datafiles import PSF, DCD, PDB_small

In the simplest case, we can simply calculate the C-alpha RMSD between
two structures, using :func:`rmsd`::

   >>> ref = mda.Universe(PDB_small)
   >>> mobile = mda.Universe(PSF,DCD)
   >>> rmsd(mobile.select_atoms('name CA').positions, ref.select_atoms('name CA').positions)

Note that in this example translations have not been removed. In order
to look at the pure rotation one needs to superimpose the centres of
mass (or geometry) first:

   >>> rmsd(mobile.select_atoms('name CA').positions, ref.select_atoms('name CA').positions, center=True)

This has only done a translational superposition. If you want to also do a
rotational superposition use the superposition keyword. This will calculate a
minimized RMSD between the reference and mobile structure.

   >>> rmsd(mobile.select_atoms('name CA').positions, ref.select_atoms('name CA').positions,
   >>>      superposition=True)

The rotation matrix that superimposes *mobile* on *ref* while
minimizing the CA-RMSD is obtained with the :func:`rotation_matrix`
function ::

   >>> mobile0 = mobile.select_atoms('name CA').positions - mobile.atoms.center_of_mass()
   >>> ref0 = ref.select_atoms('name CA').positions - ref.atoms.center_of_mass()
   >>> R, rmsd = align.rotation_matrix(mobile0, ref0)
   >>> print rmsd
   >>> print R
   [[ 0.14514539 -0.27259113  0.95111876]
    [ 0.88652593  0.46267112 -0.00268642]
    [-0.43932289  0.84358136  0.30881368]]

Putting all this together one can superimpose all of *mobile* onto *ref*::

   >>> mobile.atoms.translate(-mobile.select_atoms('name CA').center_of_mass())
   >>> mobile.atoms.rotate(R)
   >>> mobile.atoms.translate(ref.select_atoms('name CA').center_of_mass())
   >>> mobile.atoms.write("mobile_on_ref.pdb")

Common usage

To **fit a single structure** with :func:`alignto`::

   >>> ref = mda.Universe(PSF, PDB_small)
   >>> mobile = mda.Universe(PSF, DCD)     # we use the first frame
   >>> align.alignto(mobile, ref, select="protein and name CA", weights="mass")

This will change *all* coordinates in *mobile* so that the protein
C-alpha atoms are optimally superimposed (translation and rotation).

To **fit a whole trajectory** to a reference structure with the
:class:`AlignTraj` class::

   >>> ref = mda.Universe(PSF, PDB_small)   # reference structure 1AKE
   >>> trj = mda.Universe(PSF, DCD)         # trajectory of change 1AKE->4AKE
   >>> alignment = align.AlignTraj(trj, ref, filename='rmsfit.dcd')

It is also possible to align two arbitrary structures by providing a
mapping between atoms based on a sequence alignment. This allows
fitting of structural homologs or wild type and mutant.

If a alignment was provided as "sequences.aln" one would first produce
the appropriate MDAnalysis selections with the :func:`fasta2select`
function and then feed the resulting dictionary to :class:`AlignTraj`::

   >>> seldict = align.fasta2select('sequences.aln')
   >>> alignment = align.AlignTraj(trj, ref, filename='rmsfit.dcd', select=seldict)

(See the documentation of the functions for this advanced usage.)

Functions and Classes

.. versionchanged:: 0.10.0
   Function :func:`~MDAnalysis.analysis.rms.rmsd` was removed from
   this module and is now exclusively accessible as

.. versionchanged:: 0.16.0
   Function :func:`~MDAnalysis.analysis.align.rms_fit_trj` deprecated
   in favor of :class:`AlignTraj` class.

.. versionchanged:: 0.17.0
   removed deprecated :func:`~MDAnalysis.analysis.align.rms_fit_trj`

.. autofunction:: alignto
.. autoclass:: AlignTraj
.. autofunction:: rotation_matrix

Helper functions

The following functions are used by the other functions in this
module. They are probably of more interest to developers than to
normal users.

.. autofunction:: _fit_to
.. autofunction:: fasta2select
.. autofunction:: sequence_alignment
.. autofunction:: get_matching_atoms

from __future__ import division, absolute_import

import os.path
import warnings
import logging

from six.moves import range, zip, zip_longest
from six import string_types

import numpy as np

import Bio.SeqIO
import Bio.AlignIO
import Bio.Align.Applications
import Bio.Alphabet
import Bio.pairwise2

import MDAnalysis as mda
import MDAnalysis.lib.qcprot as qcp
from MDAnalysis.exceptions import SelectionError, SelectionWarning
import MDAnalysis.analysis.rms as rms
from MDAnalysis.coordinates.memory import MemoryReader
from MDAnalysis.lib.util import get_weights, deprecate

from .base import AnalysisBase

logger = logging.getLogger('MDAnalysis.analysis.align')

[docs]def rotation_matrix(a, b, weights=None): r"""Returns the 3x3 rotation matrix `R` for RMSD fitting coordinate sets `a` and `b`. The rotation matrix `R` transforms vector `a` to overlap with vector `b` (i.e., `b` is the reference structure): .. math:: \mathbf{b} = \mathsf{R} \cdot \mathbf{a} Parameters ---------- a : array_like coordinates that are to be rotated ("mobile set"); array of N atoms of shape N*3 as generated by, e.g., :attr:`MDAnalysis.core.groups.AtomGroup.positions`. b : array_like reference coordinates; array of N atoms of shape N*3 as generated by, e.g., :attr:`MDAnalysis.core.groups.AtomGroup.positions`. weights : array_like (optional) array of floats of size N for doing weighted RMSD fitting (e.g. the masses of the atoms) Returns ------- R : ndarray rotation matrix rmsd : float RMSD between `a` and `b` before rotation ``(R, rmsd)`` rmsd and rotation matrix *R* Example ------- `R` can be used as an argument for :meth:`MDAnalysis.core.groups.AtomGroup.rotate` to generate a rotated selection, e.g. :: >>> R = rotation_matrix(A.select_atoms('backbone').positions, >>> B.select_atoms('backbone').positions)[0] >>> A.atoms.rotate(R) >>> A.atoms.write("rotated.pdb") Notes ----- The function does *not* shift the centers of mass or geometry; this needs to be done by the user. See Also -------- MDAnalysis.analysis.rms.rmsd: Calculates the RMSD between *a* and *b*. alignto: A complete fit of two structures. AlignTraj: Fit a whole trajectory. """ a = np.asarray(a, dtype=np.float64) b = np.asarray(b, dtype=np.float64) if a.shape != b.shape: raise ValueError("'a' and 'b' must have same shape") N = b.shape[0] if weights is not None: # qcp does NOT divide weights relative to the mean weights = np.asarray(weights, dtype=np.float64) / np.mean(weights) rot = np.zeros(9, dtype=np.float64) # Need to transpose coordinates such that the coordinate array is # 3xN instead of Nx3. Also qcp requires that the dtype be float64 # (I think we swapped the position of ref and traj in CalcRMSDRotationalMatrix # so that R acts **to the left** and can be broadcasted; we're saving # one transpose. [orbeckst]) rmsd = qcp.CalcRMSDRotationalMatrix(a, b, N, rot, weights) return rot.reshape(3, 3), rmsd
[docs]def _fit_to(mobile_coordinates, ref_coordinates, mobile_atoms, mobile_com, ref_com, weights=None): r"""Perform an rmsd-fitting to determine rotation matrix and align atoms Parameters ---------- mobile_coordinates : ndarray Coordinates of atoms to be aligned ref_coordinates : ndarray Coordinates of atoms to be fit against mobile_atoms : AtomGroup Atoms to be translated mobile_com: ndarray array of xyz coordinate of mobile center of mass ref_com: ndarray array of xyz coordinate of reference center of mass weights : array_like (optional) choose weights. With ``None`` weigh each atom equally. If a float array of the same length as `mobile_coordinates` is provided, use each element of the `array_like` as a weight for the corresponding atom in `mobile_coordinates`. Returns ------- mobile_atoms : AtomGroup AtomGroup of translated and rotated atoms min_rmsd : float Minimum rmsd of coordinates Notes ----- This function assumes that `mobile_coordinates` and `ref_coordinates` have already been shifted so that their centers of geometry (or centers of mass, depending on `weights`) coincide at the origin. `mobile_com` and `ref_com` are the centers *before* this shift. 1. The rotation matrix :math:`\mathsf{R}` is determined with :func:`rotation_matrix` directly from `mobile_coordinates` and `ref_coordinates`. 2. `mobile_atoms` :math:`X` is rotated according to the rotation matrix and the centers according to .. math:: X' = \mathsf{R}(X - \bar{X}) + \bar{X}_{\text{ref}} where :math:`\bar{X}` is the center. """ R, min_rmsd = rotation_matrix(mobile_coordinates, ref_coordinates, weights=weights) mobile_atoms.translate(-mobile_com) mobile_atoms.rotate(R) mobile_atoms.translate(ref_com) return mobile_atoms, min_rmsd
[docs]def alignto(mobile, reference, select="all", weights=None, subselection=None, tol_mass=0.1, strict=False): """Perform a spatial superposition by minimizing the RMSD. Spatially align the group of atoms `mobile` to `reference` by doing a RMSD fit on `select` atoms. The superposition is done in the following way: 1. A rotation matrix is computed that minimizes the RMSD between the coordinates of `mobile.select_atoms(sel1)` and `reference.select_atoms(sel2)`; before the rotation, `mobile` is translated so that its center of geometry (or center of mass) coincides with the one of `reference`. (See below for explanation of how *sel1* and *sel2* are derived from `select`.) 2. All atoms in :class:`~MDAnalysis.core.universe.Universe` that contain `mobile` are shifted and rotated. (See below for how to change this behavior through the `subselection` keyword.) The `mobile` and `reference` atom groups can be constructed so that they already match atom by atom. In this case, `select` should be set to "all" (or ``None``) so that no further selections are applied to `mobile` and `reference`, therefore preserving the exact atom ordering (see :ref:`ordered-selections-label`). .. Warning:: The atom order for `mobile` and `reference` is *only* preserved when `select` is either "all" or ``None``. In any other case, a new selection will be made that will sort the resulting AtomGroup by index and therefore destroy the correspondence between the two groups. **It is safest not to mix ordered AtomGroups with selection strings.** Parameters ---------- mobile : Universe or AtomGroup structure to be aligned, a :class:`~MDAnalysis.core.groups.AtomGroup` or a whole :class:`~MDAnalysis.core.universe.Universe` reference : Universe or AtomGroup reference structure, a :class:`~MDAnalysis.core.groups.AtomGroup` or a whole :class:`~MDAnalysis.core.universe.Universe` select : str or dict or tuple (optional) The selection to operate on; can be one of: 1. any valid selection string for :meth:`~MDAnalysis.core.groups.AtomGroup.select_atoms` that produces identical selections in `mobile` and `reference`; or 2. a dictionary ``{'mobile': sel1, 'reference': sel2}`` where *sel1* and *sel2* are valid selection strings that are applied to `mobile` and `reference` respectively (the :func:`MDAnalysis.analysis.align.fasta2select` function returns such a dictionary based on a ClustalW_ or STAMP_ sequence alignment); or 3. a tuple ``(sel1, sel2)`` When using 2. or 3. with *sel1* and *sel2* then these selection strings are applied to `atomgroup` and `reference` respectively and should generate *groups of equivalent atoms*. *sel1* and *sel2* can each also be a *list of selection strings* to generate a :class:`~MDAnalysis.core.groups.AtomGroup` with defined atom order as described under :ref:`ordered-selections-label`). weights : {"mass", ``None``} or array_like (optional) choose weights. With ``"mass"`` uses masses as weights; with ``None`` weigh each atom equally. If a float array of the same length as `mobile` is provided, use each element of the `array_like` as a weight for the corresponding atom in `mobile`. tol_mass: float (optional) Reject match if the atomic masses for matched atoms differ by more than `tol_mass`, default [0.1] strict: bool (optional) ``True`` Will raise :exc:`SelectionError` if a single atom does not match between the two selections. ``False`` [default] Will try to prepare a matching selection by dropping residues with non-matching atoms. See :func:`get_matching_atoms` for details. subselection : str or AtomGroup or None (optional) Apply the transformation only to this selection. ``None`` [default] Apply to ``mobile.universe.atoms`` (i.e., all atoms in the context of the selection from `mobile` such as the rest of a protein, ligands and the surrounding water) *selection-string* Apply to ``mobile.select_atoms(selection-string)`` :class:`~MDAnalysis.core.groups.AtomGroup` Apply to the arbitrary group of atoms Returns ------- old_rmsd : float RMSD before spatial alignment new_rmsd : float RMSD after spatial alignment See Also -------- AlignTraj: More efficient method for RMSD-fitting trajectories. .. _ClustalW: .. _STAMP: .. versionchanged:: 0.8 Added check that the two groups describe the same atoms including the new *tol_mass* keyword. .. versionchanged:: 0.10.0 Uses :func:`get_matching_atoms` to work with incomplete selections and new `strict` keyword. The new default is to be lenient whereas the old behavior was the equivalent of ``strict = True``. .. versionchanged:: 0.16.0 new general 'weights' kwarg replace `mass_weighted`, deprecated `mass_weighted` .. deprecated:: 0.16.0 Instead of ``mass_weighted=True`` use new ``weights='mass'`` .. versionchanged:: 0.17.0 Deprecated keyword `mass_weighted` was removed. """ if select in ('all', None): # keep the EXACT order in the input AtomGroups; select_atoms('all') # orders them by index, which can lead to wrong results if the user # has crafted mobile and reference to match atom by atom mobile_atoms = mobile.atoms ref_atoms = reference.atoms else: select = rms.process_selection(select) mobile_atoms = mobile.select_atoms(*select['mobile']) ref_atoms = reference.select_atoms(*select['reference']) ref_atoms, mobile_atoms = get_matching_atoms(ref_atoms, mobile_atoms, tol_mass=tol_mass, strict=strict) weights = get_weights(ref_atoms, weights) mobile_com = ref_com = ref_coordinates = ref_atoms.positions - ref_com mobile_coordinates = mobile_atoms.positions - mobile_com old_rmsd = rms.rmsd(mobile_coordinates, ref_coordinates, weights) if subselection is None: # mobile_atoms is Universe mobile_atoms = mobile.universe.atoms elif isinstance(subselection, string_types): # select mobile_atoms from string mobile_atoms = mobile.select_atoms(subselection) else: try: # treat subselection as AtomGroup mobile_atoms = subselection.atoms except AttributeError: raise TypeError("subselection must be a selection string, an" " AtomGroup or Universe or None") # _fit_to DOES subtract center of mass, will provide proper min_rmsd mobile_atoms, new_rmsd = _fit_to(mobile_coordinates, ref_coordinates, mobile_atoms, mobile_com, ref_com, weights=weights) return old_rmsd, new_rmsd
[docs]class AlignTraj(AnalysisBase): """RMS-align trajectory to a reference structure using a selection. Both the reference `reference` and the trajectory `mobile` must be :class:`MDAnalysis.Universe` instances. If they contain a trajectory then it is used. The output file format is determined by the file extension of `filename`. One can also use the same universe if one wants to fit to the current frame. """ def __init__(self, mobile, reference, select='all', filename=None, prefix='rmsfit_', weights=None, tol_mass=0.1, strict=False, force=True, in_memory=False, **kwargs): """Parameters ---------- mobile : Universe Universe containing trajectory to be fitted to reference reference : Universe Universe containing trajectory frame to be used as reference select : str (optional) Set as default to all, is used for Universe.select_atoms to choose subdomain to be fitted against filename : str (optional) Provide a filename for results to be written to prefix : str (optional) Provide a string to prepend to filename for results to be written to weights : {"mass", ``None``} or array_like (optional) choose weights. With ``"mass"`` uses masses of `reference` as weights; with ``None`` weigh each atom equally. If a float array of the same length as the selection is provided, use each element of the `array_like` as a weight for the corresponding atom in the selection. tol_mass : float (optional) Tolerance given to `get_matching_atoms` to find appropriate atoms strict : bool (optional) Force `get_matching_atoms` to fail if atoms can't be found using exact methods force : bool (optional) Force overwrite of filename for rmsd-fitting start : int (optional) First frame of trajectory to analyse, Default: 0 stop : int (optional) Last frame of trajectory to analyse, Default: -1 step : int (optional) Step between frames to analyse, Default: 1 in_memory : bool (optional) *Permanently* switch `mobile` to an in-memory trajectory so that alignment can be done in-place, which can improve performance substantially in some cases. In this case, no file is written out (`filename` and `prefix` are ignored) and only the coordinates of `mobile` are *changed in memory*. verbose : bool (optional) Set logger to show more information and show detailed progress of the calculation if set to ``True``; the default is ``False``. Attributes ---------- reference_atoms : AtomGroup Atoms of the reference structure to be aligned against mobile_atoms : AtomGroup Atoms inside each trajectory frame to be rmsd_aligned rmsd : Array Array of the rmsd values of the least rmsd between the mobile_atoms and reference_atoms after superposition and minimimization of rmsd filename : str String reflecting the filename of the file where mobile_atoms positions will be written to upon running RMSD alignment Notes ----- - If set to ``verbose=False``, it is recommended to wrap the statement in a ``try ... finally`` to guarantee restoring of the log level in the case of an exception. - The ``in_memory`` option changes the `mobile` universe to an in-memory representation (see :mod:`MDAnalysis.coordinates.memory`) for the remainder of the Python session. If ``mobile.trajectory`` is already a :class:`MemoryReader` then it is *always* treated as if ``in_memory`` had been set to ``True``. .. deprecated:: 0.19.1 Default ``filename`` directory will change in 1.0 to the current directory. .. versionchanged:: 0.16.0 new general ``weights`` kwarg replace ``mass_weights`` .. deprecated:: 0.16.0 Instead of ``mass_weighted=True`` use new ``weights='mass'`` .. versionchanged:: 0.17.0 removed deprecated `mass_weighted` keyword """ select = rms.process_selection(select) self.ref_atoms = reference.select_atoms(*select['reference']) self.mobile_atoms = mobile.select_atoms(*select['mobile']) if in_memory or isinstance(mobile.trajectory, MemoryReader): mobile.transfer_to_memory() filename = None"Moved mobile trajectory to in-memory representation") else: if filename is None: # DEPRECATED in 0.19.1 # Change in 1.0 # # fn = os.path.split(mobile.trajectory.filename)[1] # filename = prefix + fn path, fn = os.path.split(mobile.trajectory.filename) filename = os.path.join(path, prefix + fn)'filename of rms_align with no filename given' ': {0}'.format(filename)) if os.path.exists(filename) and not force: raise IOError( 'Filename already exists in path and force is not set' ' to True') # do this after setting the memory reader to have a reference to the # right reader. super(AlignTraj, self).__init__(mobile.trajectory, **kwargs) if not self._verbose: logging.disable(logging.WARN) # store reference to mobile atoms = mobile.atoms self.filename = filename natoms = self.ref_atoms, self.mobile_atoms = get_matching_atoms( self.ref_atoms, self.mobile_atoms, tol_mass=tol_mass, strict=strict) # with self.filename == None (in_memory), the NullWriter is chosen # (which just ignores input) and so only the in_memory trajectory is # retained self._writer = mda.Writer(self.filename, natoms) self._weights = get_weights(self.ref_atoms, weights)"RMS-fitting on {0:d} atoms.".format(len(self.ref_atoms))) def _prepare(self): # reference centre of mass system self._ref_com = self._ref_coordinates = self.ref_atoms.positions - self._ref_com # allocate the array for selection atom coords self.rmsd = np.zeros((self.n_frames,)) def _single_frame(self): index = self._frame_index mobile_com = mobile_coordinates = self.mobile_atoms.positions - mobile_com mobile_atoms, self.rmsd[index] = _fit_to(mobile_coordinates, self._ref_coordinates,, mobile_com, self._ref_com, self._weights) # write whole aligned input trajectory system self._writer.write(mobile_atoms) def _conclude(self): self._writer.close() if not self._verbose: logging.disable(logging.NOTSET) @deprecate(release="0.19.0", remove="1.0") def save(self, rmsdfile): """save rmsd as a numpy array """ # these are the values of the new rmsd between the aligned trajectory # and reference structure np.savetxt(rmsdfile, self.rmsd)"Wrote RMSD timeseries to file %r", rmsdfile)
[docs]def sequence_alignment(mobile, reference, match_score=2, mismatch_penalty=-1, gap_penalty=-2, gapextension_penalty=-0.1): """Generate a global sequence alignment between two residue groups. The residues in `reference` and `mobile` will be globally aligned. The global alignment uses the Needleman-Wunsch algorithm as implemented in :mod:`Bio.pairwise2`. The parameters of the dynamic programming algorithm can be tuned with the keywords. The defaults should be suitable for two similar sequences. For sequences with low sequence identity, more specialized tools such as clustalw, muscle, tcoffee, or similar should be used. Parameters ---------- mobile : AtomGroup Atom group to be aligned reference : AtomGroup Atom group to be aligned against match_score : float (optional), default 2 score for matching residues, default 2 mismatch_penalty : float (optional), default -1 penalty for residues that do not match , default : -1 gap_penalty : float (optional), default -2 penalty for opening a gap; the high default value creates compact alignments for highly identical sequences but might not be suitable for sequences with low identity, default : -2 gapextension_penalty : float (optional), default -0.1 penalty for extending a gap, default: -0.1 Returns ------- alignment : tuple Tuple of top sequence matching output `('Sequence A', 'Sequence B', score, begin, end)` See Also -------- BioPython documentation for `pairwise2`_. Alternatively, use :func:`fasta2select` with :program:`clustalw2` and the option ``is_aligned=False``. .. _`pairwise2`: .. versionadded:: 0.10.0 """ aln = Bio.pairwise2.align.globalms( reference.residues.sequence(format="string"), mobile.residues.sequence(format="string"), match_score, mismatch_penalty, gap_penalty, gapextension_penalty) # choose top alignment return aln[0]
[docs]def fasta2select(fastafilename, is_aligned=False, ref_resids=None, target_resids=None, ref_offset=0, target_offset=0, verbosity=3, alnfilename=None, treefilename=None, clustalw="clustalw2"): """Return selection strings that will select equivalent residues. The function aligns two sequences provided in a FASTA file and constructs MDAnalysis selection strings of the common atoms. When these two strings are applied to the two different proteins they will generate AtomGroups of the aligned residues. `fastafilename` contains the two un-aligned sequences in FASTA format. The reference is assumed to be the first sequence, the target the second. ClustalW_ produces a pairwise alignment (which is written to a file with suffix ``.aln``). The output contains atom selection strings that select the same atoms in the two structures. Unless `ref_offset` and/or `target_offset` are specified, the resids in the structure are assumed to correspond to the positions in the un-aligned sequence, namely the first residue has resid == 1. In more complicated cases (e.g., when the resid numbering in the input structure has gaps due to missing parts), simply provide the sequence of resids as they appear in the topology in `ref_resids` or `target_resids`, e.g. :: target_resids = [a.resid for a in trj.select_atoms('name CA')] (This translation table *is* combined with any value for `ref_offset` or `target_offset`!) Parameters ---------- fastafilename : str, path to filename FASTA file with first sequence as reference and second the one to be aligned (ORDER IS IMPORTANT!) is_aligned : bool (optional) ``False`` (default) run clustalw for sequence alignment; ``True`` use the alignment in the file (e.g. from STAMP) [``False``] ref_offset : int (optional) add this number to the column number in the FASTA file to get the original residue number, default: 0 target_offset : int (optional) add this number to the column number in the FASTA file to get the original residue number, default: 0 ref_resids : str (optional) sequence of resids as they appear in the reference structure target_resids : str (optional) sequence of resids as they appear in the target alnfilename : str (optional) filename of ClustalW alignment (clustal format) that is produced by *clustalw* when *is_aligned* = ``False``. default ``None`` uses the name and path of *fastafilename* and subsititutes the suffix with '.aln'. treefilename: str (optional) filename of ClustalW guide tree (Newick format); if default ``None`` the the filename is generated from *alnfilename* with the suffix '.dnd' instead of '.aln' clustalw : str (optional) path to the ClustalW (or ClustalW2) binary; only needed for `is_aligned` = ``False``, default: "ClustalW2" Returns ------- select_dict : dict dictionary with 'reference' and 'mobile' selection string that can be used immediately in :class:`AlignTraj` as ``select=select_dict``. See Also -------- :func:`sequence_alignment`, which does not require external programs. .. _ClustalW: .. _STAMP: """ protein_gapped = Bio.Alphabet.Gapped(Bio.Alphabet.IUPAC.protein) if is_aligned:"Using provided alignment {}".format(fastafilename)) with open(fastafilename) as fasta: alignment = fasta, "fasta", alphabet=protein_gapped) else: if alnfilename is None: filepath, ext = os.path.splitext(fastafilename) alnfilename = filepath + '.aln' if treefilename is None: filepath, ext = os.path.splitext(alnfilename) treefilename = filepath + '.dnd' run_clustalw = Bio.Align.Applications.ClustalwCommandline( clustalw, infile=fastafilename, type="protein", align=True, outfile=alnfilename, newtree=treefilename) logger.debug( "Aligning sequences in %(fastafilename)r with %(clustalw)r.", vars()) logger.debug("ClustalW commandline: %r", str(run_clustalw)) try: stdout, stderr = run_clustalw() except: logger.exception("ClustalW %(clustalw)r failed", vars()) "(You can get clustalw2 from") raise with open(alnfilename) as aln: alignment = aln, "clustal", alphabet=protein_gapped) "Using clustalw sequence alignment {0!r}".format(alnfilename)) "ClustalW Newick guide tree was also produced: {0!r}".format(treefilename)) nseq = len(alignment) if nseq != 2: raise ValueError( "Only two sequences in the alignment can be processed.") # implict assertion that we only have two sequences in the alignment orig_resids = [ref_resids, target_resids] offsets = [ref_offset, target_offset] for iseq, a in enumerate(alignment): # need iseq index to change orig_resids if orig_resids[iseq] is None: # build default: assume consecutive numbering of all # residues in the alignment GAP = a.seq.alphabet.gap_char length = len(a.seq) - a.seq.count(GAP) orig_resids[iseq] = np.arange(1, length + 1) else: orig_resids[iseq] = np.asarray(orig_resids[iseq]) # add offsets to the sequence <--> resid translation table seq2resids = [resids + offset for resids, offset in zip( orig_resids, offsets)] del orig_resids del offsets def resid_factory(alignment, seq2resids): """Return a function that gives the resid for a position ipos in the nseq'th alignment. resid = resid_factory(alignment,seq2resids) r = resid(nseq,ipos) It is based on a look up table that translates position in the alignment to the residue number in the original sequence/structure. The first index of resid() is the alignmment number, the second the position in the alignment. seq2resids translates the residues in the sequence to resid numbers in the psf. In the simplest case this is a linear map but if whole parts such as loops are ommitted from the protein the seq2resids may have big gaps. Format: a tuple of two numpy arrays; the first array is for the reference, the second for the target, The index in each array gives the consecutive number of the amino acid in the sequence, the value the resid in the structure/psf. Note: assumes that alignments have same length and are padded if necessary. """ # could maybe use Bio.PDB.StructureAlignment instead? nseq = len(alignment) t = np.zeros((nseq, alignment.get_alignment_length()), dtype=int) for iseq, a in enumerate(alignment): GAP = a.seq.alphabet.gap_char t[iseq, :] = seq2resids[iseq][np.cumsum(np.where( np.array(list(a.seq)) == GAP, 0, 1)) - 1] # -1 because seq2resid is index-1 based (resids start at 1) def resid(nseq, ipos, t=t): return t[nseq, ipos] return resid resid = resid_factory(alignment, seq2resids) res_list = [] # collect individual selection string # could collect just resid and type (with/without CB) and # then post-process and use ranges for continuous stretches, eg # ( resid 1:35 and ( backbone or name CB ) ) or ( resid 36 and backbone ) # should be the same for both seqs GAP = alignment[0].seq.alphabet.gap_char if GAP != alignment[1].seq.alphabet.gap_char: raise ValueError( "Different gap characters in sequence 'target' and 'mobile'.") for ipos in range(alignment.get_alignment_length()): aligned = list(alignment[:, ipos]) if GAP in aligned: continue # skip residue template = "resid %i" if 'G' not in aligned: # can use CB template += " and ( backbone or name CB )" else: template += " and backbone" template = "( " + template + " )" res_list.append([template % resid(iseq, ipos) for iseq in range(nseq)]) sel = np.array(res_list).transpose() ref_selection = " or ".join(sel[0]) target_selection = " or ".join(sel[1]) return {'reference': ref_selection, 'mobile': target_selection}
[docs]def get_matching_atoms(ag1, ag2, tol_mass=0.1, strict=False): """Return two atom groups with one-to-one matched atoms. The function takes two :class:`~MDAnalysis.core.groups.AtomGroup` instances `ag1` and `ag2` and returns two atom groups `g1` and `g2` that consist of atoms so that the mass of atom ``g1[0]`` is the same as the mass of atom ``g2[0]``, ``g1[1]`` and ``g2[1]`` etc. The current implementation is very simplistic and works on a per-residue basis: 1. The two groups must contain the same number of residues. 2. Any residues in each group that have differing number of atoms are discarded. 3. The masses of corresponding atoms are compared. and if any masses differ by more than `tol_mass` the test is considered failed and a :exc:`SelectionError` is raised. The log file (see :func:`MDAnalysis.start_logging`) will contain detailed information about mismatches. Parameters ---------- ag1 : AtomGroup First :class:`~MDAnalysis.core.groups.AtomGroup` instance that is compared ag2 : AtomGroup Second :class:`~MDAnalysis.core.groups.AtomGroup` instance that is compared tol_mass : float (optional) Reject if the atomic masses for matched atoms differ by more than `tol_mass` [0.1] strict : bool (optional) ``True`` Will raise :exc:`SelectionError` if a single atom does not match between the two selections. ``False`` [default] Will try to prepare a matching selection by dropping residues with non-matching atoms. See :func:`get_matching_atoms` for details. Returns ------- (g1, g2) : tuple Tuple with :class:`~MDAnalysis.core.groups.AtomGroup` instances that match, atom by atom. The groups are either the original groups if all matched or slices of the original groups. Raises ------ :exc:`SelectionError` Error raised if the number of residues does not match or if in the final matching masses differ by more than *tol*. Notes ----- The algorithm could be improved by using e.g. the Needleman-Wunsch algorithm in :mod:`Bio.profile2` to align atoms in each residue (doing a global alignment is too expensive). .. versionadded:: 0.8 .. versionchanged:: 0.10.0 Renamed from :func:`check_same_atoms` to :func:`get_matching_atoms` and now returns matching atomgroups (possibly with residues removed) """ if ag1.n_atoms != ag2.n_atoms: if ag1.n_residues != ag2.n_residues: errmsg = ("Reference and trajectory atom selections do not contain " "the same number of atoms: \n" "atoms: N_ref={0}, N_traj={1}\n" "and also not the same number of residues:\n" "residues: N_ref={2}, N_traj={3}").format( ag1.n_atoms, ag2.n_atoms, ag1.n_residues, ag2.n_residues) logger.error(errmsg) raise SelectionError(errmsg) else: msg = ("Reference and trajectory atom selections do not contain " "the same number of atoms: \n" "atoms: N_ref={0}, N_traj={1}").format( ag1.n_atoms, ag2.n_atoms) if strict: logger.error(msg) raise SelectionError(msg) # continue with trying to create a valid selection msg += ("\nbut we attempt to create a valid selection " + "(use strict=True to disable this heuristic).") warnings.warn(msg, category=SelectionWarning) # continue with trying to salvage the selection: # - number of atoms is different # - number of residues is the same # We will remove residues with mismatching number of atoms (e.g. not resolved # in an X-ray structure) assert ag1.n_residues == ag2.n_residues # Alternatively, we could align all atoms but Needleman-Wunsch # pairwise2 consumes too much memory for thousands of characters in # each sequence. Perhaps a solution would be pairwise alignment per residue. # # aln_elem = Bio.pairwise2.align.globalms("".join([MDAnalysis.topology. # core.guess_atom_element(n) for n in gref.atoms.names]), # "".join([MDAnalysis.topology.core.guess_atom_element(n) # for n in models[0].atoms.names]), # 2, -1, -1, -0.1, # one_alignment_only=True) # For now, just remove the residues that don't have matching numbers # NOTE: This can create empty selections, e.g., when comparing a structure # with hydrogens to a PDB structure without hydrogens. rsize1 = np.array([r.atoms.n_atoms for r in ag1.residues]) rsize2 = np.array([r.atoms.n_atoms for r in ag2.residues]) rsize_mismatches = np.absolute(rsize1 - rsize2) mismatch_mask = (rsize_mismatches > 0) if np.any(mismatch_mask): if strict: # diagnostics mismatch_resindex = np.arange(ag1.n_residues)[mismatch_mask] def log_mismatch( number, ag, rsize, mismatch_resindex=mismatch_resindex): logger.error("Offending residues: group {0}: {1}".format( number, ", ".join(["{0[0]}{0[1]} ({0[2]})".format(r) for r in zip(ag.resnames[mismatch_resindex], ag.resids[mismatch_resindex], rsize[mismatch_resindex] )]))) logger.error("Found {0} residues with non-matching numbers of atoms (#)".format( mismatch_mask.sum())) log_mismatch(1, ag1, rsize1) log_mismatch(2, ag2, rsize2) errmsg = ("Different number of atoms in some residues. " "(Use strict=False to attempt using matching atoms only.)") logger.error(errmsg) raise SelectionError(errmsg) def get_atoms_byres(g, match_mask=np.logical_not(mismatch_mask)): # not pretty... but need to do things on a per-atom basis in # order to preserve original selection ag = g.atoms good = ag.residues.resids[match_mask] # resid for each residue resids = ag.resids # resid for each atom # boolean array for all matching atoms ix_good = np.in1d(resids, good) return ag[ix_good] _ag1 = get_atoms_byres(ag1) _ag2 = get_atoms_byres(ag2) assert _ag1.atoms.n_atoms == _ag2.atoms.n_atoms # diagnostics # (ugly workaround for missing boolean indexing of AtomGroup) # note: ag[arange(len(ag))[boolean]] is ~2x faster than # ag[where[boolean]] mismatch_resindex = np.arange(ag1.n_residues)[mismatch_mask] logger.warning("Removed {0} residues with non-matching numbers of atoms" .format(mismatch_mask.sum())) logger.debug("Removed residue ids: group 1: {0}" .format(ag1.residues.resids[mismatch_resindex])) logger.debug("Removed residue ids: group 2: {0}" .format(ag2.residues.resids[mismatch_resindex])) # replace after logging (still need old ag1 and ag2 for # diagnostics) ag1 = _ag1 ag2 = _ag2 del _ag1, _ag2 # stop if we created empty selections (by removing ALL residues...) if ag1.n_atoms == 0 or ag2.n_atoms == 0: errmsg = ("Failed to automatically find matching atoms: created empty selections. " + "Try to improve your selections for mobile and reference.") logger.error(errmsg) raise SelectionError(errmsg) # check again because the residue matching heuristic is not very # good and can easily be misled (e.g., when one of the selections # had fewer atoms but the residues in mobile and reference have # each the same number) try: mass_mismatches = (np.absolute(ag1.masses - ag2.masses) > tol_mass) except ValueError: errmsg = ("Failed to find matching atoms: len(reference) = {}, len(mobile) = {} " + "Try to improve your selections for mobile and reference.").format( ag1.n_atoms, ag2.n_atoms) logger.error(errmsg) raise SelectionError(errmsg) if np.any(mass_mismatches): # Test 2 failed. # diagnostic output: logger.error("Atoms: reference | trajectory") for ar, at in zip(ag1[mass_mismatches], ag2[mass_mismatches]): logger.error( "{0!s:>4} {1:3d} {2!s:>3} {3!s:>3} {4:6.3f} | {5!s:>4} {6:3d} {7!s:>3} {8!s:>3} {9:6.3f}".format( ar.segid, ar.resid, ar.resname,, ar.mass, at.segid, at.resid, at.resname,, at.mass)) errmsg = ("Inconsistent selections, masses differ by more than {0}; " "mis-matching atoms are shown above.").format(tol_mass) logger.error(errmsg) raise SelectionError(errmsg) return ag1, ag2