Source of the materials: Biopython cookbook (adapted) Status: Draft

Going 3D: The PDB module

Bio.PDB is a Biopython module that focuses on working with crystal structures of biological macromolecules. Among other things, Bio.PDB includes a PDBParser class that produces a Structure object, which can be used to access the atomic data in the file in a convenient manner. There is limited support for parsing the information contained in the PDB header.

Reading and writing crystal structure files

Reading a PDB file

First we create a PDBParser object:

In [1]:

from Bio.PDB.PDBParser import PDBParser
p = PDBParser(PERMISSIVE=1)

The PERMISSIVE flag indicates that a number of common problems (see [problem structures]) associated with PDB files will be ignored (but note that some atoms and/or residues will be missing). If the flag is not present a PDBConstructionException will be generated if any problems are detected during the parse operation.

The Structure object is then produced by letting the PDBParser object parse a PDB file (the PDB file in this case is called ’pdb1fat.ent’, ’1fat’ is a user defined name for the structure):

In [2]:

structure_id = "1fat"
filename = "data/pdb1fat.ent"
structure = p.get_structure(structure_id, filename)

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain A is discontinuous at line 8068.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain B is discontinuous at line 8084.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain C is discontinuous at line 8100.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain D is discontinuous at line 8116.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain A is discontinuous at line 8132.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain B is discontinuous at line 8136.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain C is discontinuous at line 8140.
  PDBConstructionWarning)
/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py:87: PDBConstructionWarning: WARNING: Chain D is discontinuous at line 8144.
  PDBConstructionWarning)

You can extract the header and trailer (simple lists of strings) of the PDB file from the PDBParser object with the get_header and get_trailer methods. Note however that many PDB files contain headers with incomplete or erroneous information. Many of the errors have been fixed in the equivalent mmCIF files. Hence, if you are interested in the header information, it is a good idea to extract information from mmCIF files using the MMCIF2Dict tool described below, instead of parsing the PDB header.

Now that is clarified, let’s return to parsing the PDB header. The structure object has an attribute called header which is a Python dictionary that maps header records to their values.

Example:

In [3]:

resolution = structure.header['resolution']
keywords = structure.header['keywords']

The available keys are name, head, deposition_date, release_date, structure_method, resolution, structure_reference (which maps to a list of references), journal_reference, author, and compound (which maps to a dictionary with various information about the crystallized compound).

The dictionary can also be created without creating a Structure object, ie. directly from the PDB file:

In [4]:

file = open(filename, 'r')
header_dict = parse_pdb_header(file)
file.close()

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-4-48b9e36dd9f4> in <module>()
      1 file = open(filename, 'r')
----> 2 header_dict = parse_pdb_header(file)
      3 file.close()

NameError: name 'parse_pdb_header' is not defined

Reading an mmCIF file

Similarly to the case the case of PDB files, first create an MMCIFParser object:

In [5]:

from Bio.PDB.MMCIFParser import MMCIFParser
parser = MMCIFParser()

Then use this parser to create a structure object from the mmCIF file:

In [6]:

structure = parser.get_structure('1fat', 'data/1fat.cif')

---------------------------------------------------------------------------
PDBConstructionException                  Traceback (most recent call last)
<ipython-input-6-218e52367060> in <module>()
----> 1 structure = parser.get_structure('1fat', 'data/1fat.cif')

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/MMCIFParser.py in get_structure(self, structure_id, filename)
     59                 warnings.filterwarnings("ignore", category=PDBConstructionWarning)
     60         self._mmcif_dict = MMCIF2Dict(filename)
---> 61         self._build_structure(structure_id)
     62         return self._structure_builder.get_structure()
     63

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/MMCIFParser.py in _build_structure(self, structure_id)
    177             element = element_list[i] if element_list else None
    178             structure_builder.init_atom(name, coord, tempfactor, occupancy, altloc,
--> 179                 name, element=element)
    180             if aniso_flag == 1:
    181                 u = (aniso_u11[i], aniso_u12[i], aniso_u13[i],

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/StructureBuilder.py in init_atom(self, name, coord, b_factor, occupancy, altloc, fullname, serial_number, element)
    239         else:
    240             # The atom is not disordered
--> 241             residue.add(self.atom)
    242
    243     def set_anisou(self, anisou_array):

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/Residue.py in add(self, atom)
     78         if self.has_id(atom_id):
     79             raise PDBConstructionException(
---> 80                 "Atom %s defined twice in residue %s" % (atom_id, self))
     81         Entity.add(self, atom)
     82

PDBConstructionException: Atom C1 defined twice in residue <Residue NAG het=H_NAG resseq=253 icode= >

To have some more low level access to an mmCIF file, you can use the MMCIF2Dict class to create a Python dictionary that maps all mmCIF tags in an mmCIF file to their values. If there are multiple values (like in the case of tag _atom_site.Cartn_y, which holds the \(y\) coordinates of all atoms), the tag is mapped to a list of values. The dictionary is created from the mmCIF file as follows:

In [7]:

from Bio.PDB.MMCIF2Dict import MMCIF2Dict
mmcif_dict = MMCIF2Dict('data/1fat.cif')

Example: get the solvent content from an mmCIF file:

In [8]:

sc = mmcif_dict['_exptl_crystal.density_percent_sol']

Example: get the list of the \(y\) coordinates of all atoms

In [9]:

y_list = mmcif_dict['_atom_site.Cartn_y']

Reading files in the PDB XML format

That’s not yet supported, but we are definitely planning to support that in the future (it’s not a lot of work). Contact the Biopython developers () if you need this).

Writing PDB files

Use the PDBIO class for this. It’s easy to write out specific parts of a structure too, of course.

Example: saving a structure

In [11]:

from Bio.PDB import PDBIO
io = PDBIO()
io.set_structure(s)
io.save('out.pdb')

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-11-bcca00d727d1> in <module>()
      1 from Bio.PDB import PDBIO
      2 io = PDBIO()
----> 3 io.set_structure(s)
      4 io.save('out.pdb')

NameError: name 's' is not defined

If you want to write out a part of the structure, make use of the Select class (also in PDBIO). Select has four methods:

  • accept_model(model)
  • accept_chain(chain)
  • accept_residue(residue)
  • accept_atom(atom)

By default, every method returns 1 (which means the model/chain/residue/atom is included in the output). By subclassing Select and returning 0 when appropriate you can exclude models, chains, etc. from the output. Cumbersome maybe, but very powerful. The following code only writes out glycine residues:

In [14]:

from Bio.PDB.PDBIO import Select
class GlySelect(Select):
    def accept_residue(self, residue):
        if residue.get_name() == 'GLY':
            return True
        else:
            return False

In [15]:

io = PDBIO()
io.set_structure(s)
io.save('gly_only.pdb', GlySelect())

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-15-10edd36b5ec5> in <module>()
      1 io = PDBIO()
----> 2 io.set_structure(s)
      3 io.save('gly_only.pdb', GlySelect())

NameError: name 's' is not defined

If this is all too complicated for you, the Dice module contains a handy extract function that writes out all residues in a chain between a start and end residue.

Structure representation

The overall layout of a Structure object follows the so-called SMCRA (Structure/Model/Chain/Residue/Atom) architecture:

  • A structure consists of models
  • A model consists of chains
  • A chain consists of residues
  • A residue consists of atoms

This is the way many structural biologists/bioinformaticians think about structure, and provides a simple but efficient way to deal with structure. Additional stuff is essentially added when needed. A UML diagram of the Structure object (forget about the Disordered classes for now) is shown in Fig. [fig:smcra]. Such a data structure is not necessarily best suited for the representation of the macromolecular content of a structure, but it is absolutely necessary for a good interpretation of the data present in a file that describes the structure (typically a PDB or MMCIF file). If this hierarchy cannot represent the contents of a structure file, it is fairly certain that the file contains an error or at least does not describe the structure unambiguously. If a SMCRA data structure cannot be generated, there is reason to suspect a problem. Parsing a PDB file can thus be used to detect likely problems. We will give several examples of this in section [problem structures].

Structure, Model, Chain and Residue are all subclasses of the Entity base class. The Atom class only (partly) implements the Entity interface (because an Atom does not have children).

For each Entity subclass, you can extract a child by using a unique id for that child as a key (e.g. you can extract an Atom object from a Residue object by using an atom name string as a key, you can extract a Chain object from a Model object by using its chain identifier as a key).

Disordered atoms and residues are represented by DisorderedAtom and DisorderedResidue classes, which are both subclasses of the DisorderedEntityWrapper base class. They hide the complexity associated with disorder and behave exactly as Atom and Residue objects.

In general, a child Entity object (i.e. Atom, Residue, Chain, Model) can be extracted from its parent (i.e. Residue, Chain, Model, Structure, respectively) by using an id as a key.

In [16]:

child_entity = parent_entity[child_id]

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-16-4f5136545867> in <module>()
----> 1 child_entity = parent_entity[child_id]

NameError: name 'parent_entity' is not defined

You can also get a list of all child Entities of a parent Entity object. Note that this list is sorted in a specific way (e.g. according to chain identifier for Chain objects in a Model object).

In [ ]:

child_list = parent_entity.get_list()

You can also get the parent from a child:

In [17]:

parent_entity = child_entity.get_parent()

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-17-9871f6bbb145> in <module>()
----> 1 parent_entity = child_entity.get_parent()

NameError: name 'child_entity' is not defined

At all levels of the SMCRA hierarchy, you can also extract a full id. The full id is a tuple containing all id’s starting from the top object (Structure) down to the current object. A full id for a Residue object e.g. is something like:

In [18]:

full_id = residue.get_full_id()
print(full_id)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-18-985fe60adf7d> in <module>()
----> 1 full_id = residue.get_full_id()
      2 print(full_id)

NameError: name 'residue' is not defined

This corresponds to:

  • The Structure with id `”1abc`”
  • The Model with id 0
  • The Chain with id `”A`”
  • The Residue with id (`” `”, 10, `”A`”).

The Residue id indicates that the residue is not a hetero-residue (nor a water) because it has a blank hetero field, that its sequence identifier is 10 and that its insertion code is `”A`”.

To get the entity’s id, use the get_id method:

In [19]:

entity.get_id()

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-19-f97a391c9568> in <module>()
----> 1 entity.get_id()

NameError: name 'entity' is not defined

You can check if the entity has a child with a given id by using the has_id method:

In [ ]:

entity.has_id(entity_id)

The length of an entity is equal to its number of children:

In [ ]:

nr_children = len(entity)

It is possible to delete, rename, add, etc. child entities from a parent entity, but this does not include any sanity checks (e.g. it is possible to add two residues with the same id to one chain). This really should be done via a nice Decorator class that includes integrity checking, but you can take a look at the code (Entity.py) if you want to use the raw interface.

Structure

The Structure object is at the top of the hierarchy. Its id is a user given string. The Structure contains a number of Model children. Most crystal structures (but not all) contain a single model, while NMR structures typically consist of several models. Disorder in crystal structures of large parts of molecules can also result in several models.

Model

The id of the Model object is an integer, which is derived from the position of the model in the parsed file (they are automatically numbered starting from 0). Crystal structures generally have only one model (with id 0), while NMR files usually have several models. Whereas many PDB parsers assume that there is only one model, the Structure class in Bio.PDB is designed such that it can easily handle PDB files with more than one model.

As an example, to get the first model from a Structure object, use

In [20]:

first_model = structure[0]

The Model object stores a list of Chain children.

Chain

The id of a Chain object is derived from the chain identifier in the PDB/mmCIF file, and is a single character (typically a letter). Each Chain in a Model object has a unique id. As an example, to get the Chain object with identifier “A” from a Model object, use

In [21]:

chain_A = model["A"]

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-21-45b288421d99> in <module>()
----> 1 chain_A = model["A"]

NameError: name 'model' is not defined

The Chain object stores a list of Residue children.

Residue

A residue id is a tuple with three elements:

  • The hetero-field (hetfield): this is

    • 'W' in the case of a water molecule;
    • 'H_' followed by the residue name for other hetero residues (e.g. 'H_GLC' in the case of a glucose molecule);
    • blank for standard amino and nucleic acids.

    This scheme is adopted for reasons described in section [hetero problems].

  • The sequence identifier (resseq), an integer describing the position of the residue in the chain (e.g., 100);

  • The insertion code (icode); a string, e.g. ’A’. The insertion code is sometimes used to preserve a certain desirable residue numbering scheme. A Ser 80 insertion mutant (inserted e.g. between a Thr 80 and an Asn 81 residue) could e.g. have sequence identifiers and insertion codes as follows: Thr 80 A, Ser 80 B, Asn 81. In this way the residue numbering scheme stays in tune with that of the wild type structure.

The id of the above glucose residue would thus be (’H_GLC’, 100, ’A’). If the hetero-flag and insertion code are blank, the sequence identifier alone can be used:

In [22]:

# Full id
residue = chain[(' ', 100, ' ')]

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-22-c937bc6cdff3> in <module>()
      1 # Full id
----> 2 residue = chain[(' ', 100, ' ')]

NameError: name 'chain' is not defined

In [23]:

residue = chain[100]

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-23-6ca58ca97644> in <module>()
----> 1 residue = chain[100]

NameError: name 'chain' is not defined

The reason for the hetero-flag is that many, many PDB files use the same sequence identifier for an amino acid and a hetero-residue or a water, which would create obvious problems if the hetero-flag was not used.

Unsurprisingly, a Residue object stores a set of Atom children. It also contains a string that specifies the residue name (e.g. “ASN”) and the segment identifier of the residue (well known to X-PLOR users, but not used in the construction of the SMCRA data structure).

Let’s look at some examples. Asn 10 with a blank insertion code would have residue id (’ ’, 10, ’ ’). Water 10 would have residue id (’W’, 10, ’ ’). A glucose molecule (a hetero residue with residue name GLC) with sequence identifier 10 would have residue id (’H_GLC’, 10, ’ ’). In this way, the three residues (with the same insertion code and sequence identifier) can be part of the same chain because their residue id’s are distinct.

In most cases, the hetflag and insertion code fields will be blank, e.g. (’ ’, 10, ’ ’). In these cases, the sequence identifier can be used as a shortcut for the full id:

In [ ]:

# use full id
res10 = chain[(' ', 10, ' ')]

In [ ]:

res10 = chain[10]

Each Residue object in a Chain object should have a unique id. However, disordered residues are dealt with in a special way, as described in section [point mutations].

A Residue object has a number of additional methods:

In [24]:

residue.get_resname()       # returns the residue name, e.g. "ASN"
residue.is_disordered()     # returns 1 if the residue has disordered atoms
residue.get_segid()         # returns the SEGID, e.g. "CHN1"
residue.has_id(name)        # test if a residue has a certain atom

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-24-a34e77e319d2> in <module>()
----> 1 residue.get_resname()       # returns the residue name, e.g. "ASN"
      2 residue.is_disordered()     # returns 1 if the residue has disordered atoms
      3 residue.get_segid()         # returns the SEGID, e.g. "CHN1"
      4 residue.has_id(name)        # test if a residue has a certain atom

NameError: name 'residue' is not defined

You can use is_aa(residue) to test if a Residue object is an amino acid.

Atom

The Atom object stores the data associated with an atom, and has no children. The id of an atom is its atom name (e.g. “OG” for the side chain oxygen of a Ser residue). An Atom id needs to be unique in a Residue. Again, an exception is made for disordered atoms, as described in section [disordered atoms].

The atom id is simply the atom name (eg. ’CA’). In practice, the atom name is created by stripping all spaces from the atom name in the PDB file.

However, in PDB files, a space can be part of an atom name. Often, calcium atoms are called ’CA..’ in order to distinguish them from C\(\alpha\) atoms (which are called ’.CA.’). In cases were stripping the spaces would create problems (ie. two atoms called ’CA’ in the same residue) the spaces are kept.

In a PDB file, an atom name consists of 4 chars, typically with leading and trailing spaces. Often these spaces can be removed for ease of use (e.g. an amino acid C$ :raw-latex:`alpha `$ atom is labeled “.CA.” in a PDB file, where the dots represent spaces). To generate an atom name (and thus an atom id) the spaces are removed, unless this would result in a name collision in a Residue (i.e. two Atom objects with the same atom name and id). In the latter case, the atom name including spaces is tried. This situation can e.g. happen when one residue contains atoms with names “.CA.” and “CA..”, although this is not very likely.

The atomic data stored includes the atom name, the atomic coordinates (including standard deviation if present), the B factor (including anisotropic B factors and standard deviation if present), the altloc specifier and the full atom name including spaces. Less used items like the atom element number or the atomic charge sometimes specified in a PDB file are not stored.

To manipulate the atomic coordinates, use the transform method of the Atom object. Use the set_coord method to specify the atomic coordinates directly.

An Atom object has the following additional methods:

In [25]:

a.get_name()       # atom name (spaces stripped, e.g. "CA")
a.get_id()         # id (equals atom name)
a.get_coord()      # atomic coordinates
a.get_vector()     # atomic coordinates as Vector object
a.get_bfactor()    # isotropic B factor
a.get_occupancy()  # occupancy
a.get_altloc()     # alternative location specifier
a.get_sigatm()     # standard deviation of atomic parameters
a.get_siguij()     # standard deviation of anisotropic B factor
a.get_anisou()     # anisotropic B factor
a.get_fullname()   # atom name (with spaces, e.g. ".CA.")

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-25-2b9bddc52a80> in <module>()
----> 1 a.get_name()       # atom name (spaces stripped, e.g. "CA")
      2 a.get_id()         # id (equals atom name)
      3 a.get_coord()      # atomic coordinates
      4 a.get_vector()     # atomic coordinates as Vector object
      5 a.get_bfactor()    # isotropic B factor

NameError: name 'a' is not defined

To represent the atom coordinates, siguij, anisotropic B factor and sigatm Numpy arrays are used.

The get_vector method returns a Vector object representation of the coordinates of the Atom object, allowing you to do vector operations on atomic coordinates. Vector implements the full set of 3D vector operations, matrix multiplication (left and right) and some advanced rotation-related operations as well.

As an example of the capabilities of Bio.PDB’s Vector module, suppose that you would like to find the position of a Gly residue’s C\(\beta\) atom, if it had one. Rotating the N atom of the Gly residue along the C\(\alpha\)-C bond over -120 degrees roughly puts it in the position of a virtual C\(\beta\) atom. Here’s how to do it, making use of the rotaxis method (which can be used to construct a rotation around a certain axis) of the Vector module:

In [26]:

# get atom coordinates as vectors
n = residue['N'].get_vector()
c = residue['C'].get_vector()
ca = residue['CA'].get_vector()

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-26-e0172a5c1106> in <module>()
      1 # get atom coordinates as vectors
----> 2 n = residue['N'].get_vector()
      3 c = residue['C'].get_vector()
      4 ca = residue['CA'].get_vector()

NameError: name 'residue' is not defined

In [27]:

n = n - ca
c = c - ca

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-27-c8c7b51cbaf3> in <module>()
----> 1 n = n - ca
      2 c = c - ca

NameError: name 'n' is not defined

In [28]:

rot = rotaxis(-pi * 120.0/180.0, c)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-28-6b8da02d67ce> in <module>()
----> 1 rot = rotaxis(-pi * 120.0/180.0, c)

NameError: name 'rotaxis' is not defined

In [29]:

cb_at_origin = n.left_multiply(rot)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-29-b23ae22bff68> in <module>()
----> 1 cb_at_origin = n.left_multiply(rot)

NameError: name 'n' is not defined

In [30]:

cb = cb_at_origin + ca

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-30-790f34c5734f> in <module>()
----> 1 cb = cb_at_origin + ca

NameError: name 'cb_at_origin' is not defined

This example shows that it’s possible to do some quite nontrivial vector operations on atomic data, which can be quite useful. In addition to all the usual vector operations (cross (use **), and dot (use *) product, angle, norm, etc.) and the above mentioned rotaxis function, the Vector module also has methods to rotate (rotmat) or reflect (refmat) one vector on top of another.

Extracting a specific Atom/Residue/Chain/Model from a Structure

These are some examples:

In [31]:

model = structure[0]
chain = model['A']
residue = chain[100]
atom = residue['CA']

Note that you can use a shortcut:

In [32]:

atom = structure[0]['A'][100]['CA']

Disorder

Bio.PDB can handle both disordered atoms and point mutations (i.e. a Gly and an Ala residue in the same position).

General approach[disorder problems]

Disorder should be dealt with from two points of view: the atom and the residue points of view. In general, we have tried to encapsulate all the complexity that arises from disorder. If you just want to loop over all C\(\alpha\) atoms, you do not care that some residues have a disordered side chain. On the other hand it should also be possible to represent disorder completely in the data structure. Therefore, disordered atoms or residues are stored in special objects that behave as if there is no disorder. This is done by only representing a subset of the disordered atoms or residues. Which subset is picked (e.g. which of the two disordered OG side chain atom positions of a Ser residue is used) can be specified by the user.

Disordered atoms[disordered atoms]

Disordered atoms are represented by ordinary Atom objects, but all Atom objects that represent the same physical atom are stored in a DisorderedAtom object (see Fig. [fig:smcra]). Each Atom object in a DisorderedAtom object can be uniquely indexed using its altloc specifier. The DisorderedAtom object forwards all uncaught method calls to the selected Atom object, by default the one that represents the atom with the highest occupancy. The user can of course change the selected Atom object, making use of its altloc specifier. In this way atom disorder is represented correctly without much additional complexity. In other words, if you are not interested in atom disorder, you will not be bothered by it.

Each disordered atom has a characteristic altloc identifier. You can specify that a DisorderedAtom object should behave like the Atom object associated with a specific altloc identifier:

In [33]:

atom.disordered_select('A') # select altloc A atom
print(atom.get_altloc())

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-33-b874ea06f929> in <module>()
----> 1 atom.disordered_select('A') # select altloc A atom
      2 print(atom.get_altloc())

AttributeError: 'Atom' object has no attribute 'disordered_select'

In [34]:

atom.disordered_select('B') # select altloc B atom
print(atom.get_altloc())

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-34-f32dfd0feabf> in <module>()
----> 1 atom.disordered_select('B') # select altloc B atom
      2 print(atom.get_altloc())

AttributeError: 'Atom' object has no attribute 'disordered_select'

Disordered residues

Common case

The most common case is a residue that contains one or more disordered atoms. This is evidently solved by using DisorderedAtom objects to represent the disordered atoms, and storing the DisorderedAtom object in a Residue object just like ordinary Atom objects. The DisorderedAtom will behave exactly like an ordinary atom (in fact the atom with the highest occupancy) by forwarding all uncaught method calls to one of the Atom objects (the selected Atom object) it contains.

Point mutations[point mutations]

A special case arises when disorder is due to a point mutation, i.e. when two or more point mutants of a polypeptide are present in the crystal. An example of this can be found in PDB structure 1EN2.

Since these residues belong to a different residue type (e.g. let’s say Ser 60 and Cys 60) they should not be stored in a single Residue object as in the common case. In this case, each residue is represented by one Residue object, and both Residue objects are stored in a single DisorderedResidue object (see Fig. [fig:smcra]).

The DisorderedResidue object forwards all uncaught methods to the selected Residue object (by default the last Residue object added), and thus behaves like an ordinary residue. Each Residue object in a DisorderedResidue object can be uniquely identified by its residue name. In the above example, residue Ser 60 would have id “SER” in the DisorderedResidue object, while residue Cys 60 would have id “CYS”. The user can select the active Residue object in a DisorderedResidue object via this id.

Example: suppose that a chain has a point mutation at position 10, consisting of a Ser and a Cys residue. Make sure that residue 10 of this chain behaves as the Cys residue.

In [35]:

residue = chain[10]
residue.disordered_select('CYS')

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-35-c375d43705d3> in <module>()
      1 residue = chain[10]
----> 2 residue.disordered_select('CYS')

AttributeError: 'Residue' object has no attribute 'disordered_select'

In addition, you can get a list of all Atom objects (ie. all DisorderedAtom objects are ’unpacked’ to their individual Atom objects) using the get_unpacked_list method of a (Disordered)Residue object.

Hetero residues

Associated problems[hetero problems]

A common problem with hetero residues is that several hetero and non-hetero residues present in the same chain share the same sequence identifier (and insertion code). Therefore, to generate a unique id for each hetero residue, waters and other hetero residues are treated in a different way.

Remember that Residue object have the tuple (hetfield, resseq, icode) as id. The hetfield is blank (“ ”) for amino and nucleic acids, and a string for waters and other hetero residues. The content of the hetfield is explained below.

Water residues

The hetfield string of a water residue consists of the letter “W”. So a typical residue id for a water is (“W”, 1, “ ”).

Other hetero residues

The hetfield string for other hetero residues starts with “H_” followed by the residue name. A glucose molecule e.g. with residue name “GLC” would have hetfield “H_GLC”. Its residue id could e.g. be (“H_GLC”, 1, “ ”).

Analyzing structures

Measuring distances

The minus operator for atoms has been overloaded to return the distance between two atoms.

In [57]:

# Get some atoms
ca1 = residue1['CA']
ca2 = residue2['CA']

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-57-2f7f3dc9b562> in <module>()
      1 # Get some atoms
----> 2 ca1 = residue1['CA']
      3 ca2 = residue2['CA']

NameError: name 'residue1' is not defined

In [ ]:

distance = ca1-ca2

Measuring angles

Use the vector representation of the atomic coordinates, and the calc_angle function from the Vector module:

In [58]:

vector1 = atom1.get_vector()
vector2 = atom2.get_vector()
vector3 = atom3.get_vector()
angle = calc_angle(vector1, vector2, vector3)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-58-c61cceff7731> in <module>()
----> 1 vector1 = atom1.get_vector()
      2 vector2 = atom2.get_vector()
      3 vector3 = atom3.get_vector()
      4 angle = calc_angle(vector1, vector2, vector3)

NameError: name 'atom1' is not defined

Measuring torsion angles

Use the vector representation of the atomic coordinates, and the calc_dihedral function from the Vector module:

In [59]:

vector1 = atom1.get_vector()
vector2 = atom2.get_vector()
vector3 = atom3.get_vector()
vector4 = atom4.get_vector()
angle = calc_dihedral(vector1, vector2, vector3, vector4)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-59-03917accffd8> in <module>()
----> 1 vector1 = atom1.get_vector()
      2 vector2 = atom2.get_vector()
      3 vector3 = atom3.get_vector()
      4 vector4 = atom4.get_vector()
      5 angle = calc_dihedral(vector1, vector2, vector3, vector4)

NameError: name 'atom1' is not defined

Determining atom-atom contacts

Use NeighborSearch to perform neighbor lookup. The neighbor lookup is done using a KD tree module written in C (see Bio.KDTree), making it very fast. It also includes a fast method to find all point pairs within a certain distance of each other.

Superimposing two structures

Use a Superimposer object to superimpose two coordinate sets. This object calculates the rotation and translation matrix that rotates two lists of atoms on top of each other in such a way that their RMSD is minimized. Of course, the two lists need to contain the same number of atoms. The Superimposer object can also apply the rotation/translation to a list of atoms. The rotation and translation are stored as a tuple in the rotran attribute of the Superimposer object (note that the rotation is right multiplying!). The RMSD is stored in the rmsd attribute.

The algorithm used by Superimposer comes from @golub1989 [Golub & Van Loan] and makes use of singular value decomposition (this is implemented in the general Bio.SVDSuperimposer module).

Example:

In [61]:

from Bio.PDB import Superimposer
sup = Superimposer()

In [62]:

sup.set_atoms(fixed, moving)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-62-90d683778703> in <module>()
----> 1 sup.set_atoms(fixed, moving)

NameError: name 'fixed' is not defined

In [63]:

print(sup.rotran)
print(sup.rms)

None
None

In [64]:

sup.apply(moving)

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-64-c5ac66567782> in <module>()
----> 1 sup.apply(moving)

NameError: name 'moving' is not defined

To superimpose two structures based on their active sites, use the active site atoms to calculate the rotation/translation matrices (as above), and apply these to the whole molecule.

Calculating the Half Sphere Exposure

Half Sphere Exposure (HSE) is a new, 2D measure of solvent exposure @hamelryck2005. Basically, it counts the number of C\(\alpha\) atoms around a residue in the direction of its side chain, and in the opposite direction (within a radius of \(13 \AA\)). Despite its simplicity, it outperforms many other measures of solvent exposure.

HSE comes in two flavors: HSE\(\alpha\) and HSE\(\beta\). The former only uses the C\(\alpha\) atom positions, while the latter uses the C\(\alpha\) and C\(\beta\) atom positions. The HSE measure is calculated by the HSExposure class, which can also calculate the contact number. The latter class has methods which return dictionaries that map a Residue object to its corresponding HSE\(\alpha\), HSE\(\beta\) and contact number values.

Example:

In [66]:

from Bio.PDB import HSExposure
model = structure[0]
hse = HSExposure()

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-66-b00b7a96aff9> in <module>()
      1 from Bio.PDB import HSExposure
      2 model = structure[0]
----> 3 hse = HSExposure()

TypeError: 'module' object is not callable

In [67]:

exp_ca = hse.calc_hs_exposure(model, option='CA3')

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-67-72378e1b79de> in <module>()
----> 1 exp_ca = hse.calc_hs_exposure(model, option='CA3')

NameError: name 'hse' is not defined

In [ ]:

exp_cb=hse.calc_hs_exposure(model, option='CB')

In [ ]:

exp_fs = hse.calc_fs_exposure(model)

In [ ]:

print(exp_ca[some_residue])

Determining the secondary structure

For this functionality, you need to install DSSP (and obtain a license for it — free for academic use, see http://www.cmbi.kun.nl/gv/dssp/). Then use the DSSP class, which maps Residue objects to their secondary structure (and accessible surface area). The DSSP codes are listed in Table [cap:DSSP-codes]. Note that DSSP (the program, and thus by consequence the class) cannot handle multiple models!

Code Secondary structure
H \(\alpha\)-helix
B Isolated \(\beta\)-bridge residue
E Strand
G 3-10 helix
I \(\Pi\)-helix
T Turn
S Bend
Other

Table: [cap:DSSP-codes]DSSP codes in Bio.PDB.

The DSSP class can also be used to calculate the accessible surface area of a residue. But see also section [subsec:residue_depth].

Calculating the residue depth[subsec:residue_depth]

Residue depth is the average distance of a residue’s atoms from the solvent accessible surface. It’s a fairly new and very powerful parameterization of solvent accessibility. For this functionality, you need to install Michel Sanner’s MSMS program (http://www.scripps.edu/pub/olson-web/people/sanner/html/msms_home.html). Then use the ResidueDepth class. This class behaves as a dictionary which maps Residue objects to corresponding (residue depth, C\(\alpha\) depth) tuples. The C\(\alpha\) depth is the distance of a residue’s C\(\alpha\) atom to the solvent accessible surface.

Example:

In [69]:

from Bio.PDB import ResidueDepth
model = structure[0]
rd = ResidueDepth(model, pdb_file)
residue_depth, ca_depth=rd[some_residue]

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-69-1139411bd4aa> in <module>()
      1 from Bio.PDB import ResidueDepth
      2 model = structure[0]
----> 3 rd = ResidueDepth(model, pdb_file)
      4 residue_depth, ca_depth=rd[some_residue]

NameError: name 'pdb_file' is not defined

You can also get access to the molecular surface itself (via the get_surface function), in the form of a Numeric Python array with the surface points.

Common problems in PDB files

It is well known that many PDB files contain semantic errors (not the structures themselves, but their representation in PDB files). Bio.PDB tries to handle this in two ways. The PDBParser object can behave in two ways: a restrictive way and a permissive way, which is the default.

Example:

In [70]:

# Permissive parser
parser = PDBParser(PERMISSIVE=1)
parser = PDBParser() # The same (default)

In [71]:

strict_parser = PDBParser(PERMISSIVE=0)

In the permissive state (DEFAULT), PDB files that obviously contain errors are “corrected” (i.e. some residues or atoms are left out). These errors include:

  • Multiple residues with the same identifier
  • Multiple atoms with the same identifier (taking into account the altloc identifier)

These errors indicate real problems in the PDB file (for details see @hamelryck2003a [Hamelryck and Manderick, 2003]). In the restrictive state, PDB files with errors cause an exception to occur. This is useful to find errors in PDB files.

Some errors however are automatically corrected. Normally each disordered atom should have a non-blank altloc identifier. However, there are many structures that do not follow this convention, and have a blank and a non-blank identifier for two disordered positions of the same atom. This is automatically interpreted in the right way.

Sometimes a structure contains a list of residues belonging to chain A, followed by residues belonging to chain B, and again followed by residues belonging to chain A, i.e. the chains are ’broken’. This is also correctly interpreted.

Examples[problem structures]

The PDBParser/Structure class was tested on about 800 structures (each belonging to a unique SCOP superfamily). This takes about 20 minutes, or on average 1.5 seconds per structure. Parsing the structure of the large ribosomal subunit (1FKK), which contains about 64000 atoms, takes 10 seconds on a 1000 MHz PC.

Three exceptions were generated in cases where an unambiguous data structure could not be built. In all three cases, the likely cause is an error in the PDB file that should be corrected. Generating an exception in these cases is much better than running the chance of incorrectly describing the structure in a data structure.

Duplicate residues

One structure contains two amino acid residues in one chain with the same sequence identifier (resseq 3) and icode. Upon inspection it was found that this chain contains the residues Thr A3, …, Gly A202, Leu A3, Glu A204. Clearly, Leu A3 should be Leu A203. A couple of similar situations exist for structure 1FFK (which e.g. contains Gly B64, Met B65, Glu B65, Thr B67, i.e. residue Glu B65 should be Glu B66).

Duplicate atoms

Structure 1EJG contains a Ser/Pro point mutation in chain A at position 22. In turn, Ser 22 contains some disordered atoms. As expected, all atoms belonging to Ser 22 have a non-blank altloc specifier (B or C). All atoms of Pro 22 have altloc A, except the N atom which has a blank altloc. This generates an exception, because all atoms belonging to two residues at a point mutation should have non-blank altloc. It turns out that this atom is probably shared by Ser and Pro 22, as Ser 22 misses the N atom. Again, this points to a problem in the file: the N atom should be present in both the Ser and the Pro residue, in both cases associated with a suitable altloc identifier.

Automatic correction

Some errors are quite common and can be easily corrected without much risk of making a wrong interpretation. These cases are listed below.

A blank altloc for a disordered atom

Normally each disordered atom should have a non-blank altloc identifier. However, there are many structures that do not follow this convention, and have a blank and a non-blank identifier for two disordered positions of the same atom. This is automatically interpreted in the right way.

Broken chains

Sometimes a structure contains a list of residues belonging to chain A, followed by residues belonging to chain B, and again followed by residues belonging to chain A, i.e. the chains are “broken”. This is correctly interpreted.

Fatal errors

Sometimes a PDB file cannot be unambiguously interpreted. Rather than guessing and risking a mistake, an exception is generated, and the user is expected to correct the PDB file. These cases are listed below.

Duplicate residues

All residues in a chain should have a unique id. This id is generated based on:

  • The sequence identifier (resseq).
  • The insertion code (icode).
  • The hetfield string (“W” for waters and “H_” followed by the residue name for other hetero residues)
  • The residue names of the residues in the case of point mutations (to store the Residue objects in a DisorderedResidue object).

If this does not lead to a unique id something is quite likely wrong, and an exception is generated.

Duplicate atoms

All atoms in a residue should have a unique id. This id is generated based on:

  • The atom name (without spaces, or with spaces if a problem arises).
  • The altloc specifier.

If this does not lead to a unique id something is quite likely wrong, and an exception is generated.

Accessing the Protein Data Bank

Downloading structures from the Protein Data Bank

Structures can be downloaded from the PDB (Protein Data Bank) by using the retrieve_pdb_file method on a PDBList object. The argument for this method is the PDB identifier of the structure.

In [73]:

from Bio.PDB import PDBList
pdbl = PDBList()
pdbl.retrieve_pdb_file('1FAT')

Downloading PDB structure '1FAT'...

Out[73]:

'/home/tiago_antao/biopython-notebook/notebooks/fa/pdb1fat.ent'

The PDBList class can also be used as a command-line tool:

python PDBList.py 1fat

The downloaded file will be called pdb1fat.ent and stored in the current working directory. Note that the retrieve_pdb_file method also has an optional argument pdir that specifies a specific directory in which to store the downloaded PDB files.

The retrieve_pdb_file method also has some options to specify the compression format used for the download, and the program used for local decompression (default .Z format and gunzip). In addition, the PDB ftp site can be specified upon creation of the PDBList object. By default, the server of the Worldwide Protein Data Bank (ftp://ftp.wwpdb.org/pub/pdb/data/structures/divided/pdb/) is used. See the API documentation for more details. Thanks again to Kristian Rother for donating this module.

Downloading the entire PDB

The following commands will store all PDB files in the /data/pdb directory:

python PDBList.py all /data/pdb

python PDBList.py all /data/pdb -d

The API method for this is called download_entire_pdb. Adding the -d option will store all files in the same directory. Otherwise, they are sorted into PDB-style subdirectories according to their PDB ID’s. Depending on the traffic, a complete download will take 2-4 days.

Keeping a local copy of the PDB up to date

This can also be done using the PDBList object. One simply creates a PDBList object (specifying the directory where the local copy of the PDB is present) and calls the update_pdb method:

In [75]:

pl = PDBList(pdb='/tmp/data/pdb')
pl.update_pdb()

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-75-726659b0f2c5> in <module>()
      1 pl = PDBList(pdb='/tmp/data/pdb')
----> 2 pl.update_pdb()

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/PDBList.py in update_pdb(self)
    236         assert os.path.isdir(self.obsolete_pdb)
    237
--> 238         new, modified, obsolete = self.get_recent_changes()
    239
    240         for pdb_code in new + modified:

/home/tiago_antao/miniconda/lib/python3.5/site-packages/Bio/PDB/PDBList.py in get_recent_changes(self)
    114             recent = filter(str.isdigit,
    115                             (x.split()[-1] for x in handle.readlines())
--> 116                             )[-1]
    117
    118         path = self.pdb_server + '/pub/pdb/data/status/%s/' % (recent)

TypeError: 'filter' object is not subscriptable