Four ways to get the secondary structure of a protein

In this example, we will obtain the secondary structure of the transketolase crystal structure (PDB: 1QGD) in four different ways and visualize it using a customized feature map.

At first, we will write draw functions for visualization of helices and sheets in feature maps.

# Code source: Patrick Kunzmann
# License: BSD 3 clause

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib.patches import Rectangle
import biotite
import biotite.structure as struc
import as mmtf
import biotite.sequence as seq
import as graphics
import as gb
import biotite.database.rcsb as rcsb
import biotite.database.entrez as entrez
import biotite.application.dssp as dssp

# Create 'FeaturePlotter' subclasses
# for drawing the scondary structure features

class HelixPlotter(graphics.FeaturePlotter):

    def __init__(self):

    # Check whether this class is applicable for drawing a feature
    def matches(self, feature):
        if feature.key == "SecStr":
            if "sec_str_type" in feature.qual:
                if feature.qual["sec_str_type"] == "helix":
                    return True
        return False

    # The drawing function itself
    def draw(self, axes, feature, bbox, loc, style_param):
        # Approx. 1 turn per 3.6 residues to resemble natural helix
        n_turns = np.ceil((loc.last - loc.first + 1) / 3.6)
        x_val = np.linspace(0, n_turns * 2*np.pi, 100)
        # Curve ranges from 0.3 to 0.7
        y_val = (-0.4*np.sin(x_val) + 1) / 2

        # Transform values for correct location in feature map
        x_val *= bbox.width / (n_turns * 2*np.pi)
        x_val += bbox.x0
        y_val *= bbox.height
        y_val += bbox.y0

        # Draw white background to overlay the guiding line
        background = Rectangle(
            bbox.p0, bbox.width, bbox.height, color="white", linewidth=0
            x_val, y_val, linewidth=2, color=biotite.colors["dimgreen"]

class SheetPlotter(graphics.FeaturePlotter):

    def __init__(self, head_width=0.8, tail_width=0.5):
        self._head_width = head_width
        self._tail_width = tail_width

    def matches(self, feature):
        if feature.key == "SecStr":
            if "sec_str_type" in feature.qual:
                if feature.qual["sec_str_type"] == "sheet":
                    return True
        return False

    def draw(self, axes, feature, bbox, loc, style_param):
        x = bbox.x0
        y = bbox.y0 + bbox.height/2
        dx = bbox.width
        dy = 0

        if  loc.defect & seq.Location.Defect.MISS_RIGHT:
            # If the feature extends into the prevoius or next line
            # do not draw an arrow head
            draw_head = False
            draw_head = True

            x, y, dx, dy,
            self._tail_width*bbox.height, self._head_width*bbox.height,
            # Create head with 90 degrees tip
            # -> head width/length ratio = 1/2
            head_ratio=0.5, draw_head=draw_head,
            color=biotite.colors["orange"], linewidth=0

# Test our drawing functions with example annotation
annotation = seq.Annotation([
    seq.Feature("SecStr", [seq.Location(10, 40)], {"sec_str_type" : "helix"}),
    seq.Feature("SecStr", [seq.Location(60, 90)], {"sec_str_type" : "sheet"}),

fig = plt.figure(figsize=(8.0, 0.8))
ax = fig.add_subplot(111)
    ax, annotation, multi_line=False, loc_range=(1,100),
    # Register our drawing functions
    feature_plotters=[HelixPlotter(), SheetPlotter()]

Now let us do some serious application. We want to visualize the secondary structure of one monomer of the homodimeric transketolase (PDB: 1QGD). The simplest way to do that, is to fetch the corresponding GenBank file, extract an Annotation object from the file and draw the annotation.

# Fetch GenBank files of the TK's first chain and extract annotatation
file_name = entrez.fetch("1QGD_A", biotite.temp_dir(), "gb", "protein", "gb")
gb_file = gb.GenBankFile()
annotation = gb_file.get_annotation(include_only=["SecStr"])
# Length of the sequence
length = int(gb_file.get_locus()["length"])

fig = plt.figure(figsize=(8.0, 3.0))
ax = fig.add_subplot(111)
    ax, annotation, symbols_per_line=150,
    show_numbers=True, show_line_position=True,
    # 'loc_range' takes exclusive stop -> length+1 is required
    feature_plotters=[HelixPlotter(), SheetPlotter()]

Another (more complicated) approach is the creation of an Annotation containing the secondary structure from a structure file. All file formats distributed by the RCSB PDB contain this information, but it is most easily extracted from the 'secStructList' field in MMTF files. Since the two sources use different means of secondary structure calculation, the results will differ from each other.

# Dictionary to convert 'secStructList' codes to DSSP values
sec_struct_codes = {0 : "I",
                    1 : "S",
                    2 : "H",
                    3 : "E",
                    4 : "G",
                    5 : "B",
                    6 : "T",
                    7 : "C"}
# Converter for the DSSP secondary structure elements
# to the classical ones
dssp_to_abc = {"I" : "c",
               "S" : "c",
               "H" : "a",
               "E" : "b",
               "G" : "c",
               "B" : "b",
               "T" : "c",
               "C" : "c"}

# Fetch and load structure
file_name = rcsb.fetch("1QGD", "mmtf", biotite.temp_dir())
mmtf_file = mmtf.MMTFFile()
array = mmtf.get_structure(mmtf_file, model=1)
# Transketolase homodimer
tk_dimer = array[struc.filter_amino_acids(array)]
# Transketolase monomer
tk_mono = tk_dimer[tk_dimer.chain_id == "A"]

# The chain ID corresponding to each residue
chain_id_per_res = array.chain_id[struc.get_residue_starts(tk_dimer)]
sse = mmtf_file["secStructList"]
sse = sse[sse != -1]
sse = sse[chain_id_per_res == "A"]
sse = np.array([sec_struct_codes[code] for code in sse if code != -1],
sse = np.array([dssp_to_abc[e] for e in sse], dtype="U1")

# Helper function to convert secondary structure array to annotation
# and visualize it
def visualize_secondary_structure(sse, first_id):

    def _add_sec_str(annotation, first, last, str_type):
        if str_type == "a":
            str_type = "helix"
        elif str_type == "b":
            str_type = "sheet"
            # coil
        feature = seq.Feature(
            "SecStr", [seq.Location(first, last)], {"sec_str_type" : str_type}

    # Find the intervals for each secondary structure element
    # and add to annotation
    annotation = seq.Annotation()
    curr_sse = None
    curr_start = None
    for i in range(len(sse)):
        if curr_start is None:
            curr_start = i
            curr_sse = sse[i]
            if sse[i] != sse[i-1]:
                    annotation, curr_start+first_id, i-1+first_id, curr_sse
                curr_start = i
                curr_sse = sse[i]
    # Add last secondary structure element to annotation
    _add_sec_str(annotation, curr_start+first_id, i-1+first_id, curr_sse)

    fig = plt.figure(figsize=(8.0, 3.0))
    ax = fig.add_subplot(111)
        ax, annotation, symbols_per_line=150, loc_range=(1,length+1),
        show_numbers=True, show_line_position=True,
        feature_plotters=[HelixPlotter(), SheetPlotter()]

# Visualize seconday structure array
# Sine the residues may not start at 1,
# provide the actual first residue ID
visualize_secondary_structure(sse, tk_mono.res_id[0])

Almost the same result can be achieved, when we calculate the secondary structure ourselves using the DSSP software, as the content in 'secStructList' is also calculated by the RCSB.

sse = dssp.DsspApp.annotate_sse(tk_mono)
sse = np.array([dssp_to_abc[e] for e in sse], dtype="U1")
visualize_secondary_structure(sse, tk_mono.res_id[0])
# sphinx_gallery_thumbnail_number = 4

The one and only difference is that the second helix is slightly shorter. This is probably caused by different versions of DSSP.

Last but not least we calculate the secondary structure using Biotite’s built-in method, based on the P-SEA algorithm.

sse = struc.annotate_sse(array, chain_id="A")
visualize_secondary_structure(sse, tk_mono.res_id[0])

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