Import the latticeproteins package.
In [1]:
import latticeproteins as lp
The LatticeThermodyanmics class creates objects that can calculate lattice protein thermodynamics for any sequences of a specified length. In the example below, we initialize this object for sequences of length 10. Note that to avoid repeating expensive conformation enumerations, the LatticeThermodynamics object creates a directory in your current location called database. Inside this directory, it stores python pickle files that include a database of all conformations on a 2d grid.
In [2]:
seq_length = 10
temperature = 1.0
lattice = lp.LatticeThermodynamics.from_length(seq_length, 1.0)
Now, we'll create a random sequence with the given length and start evaluating thermodynamic values.
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seq = lp.random_sequence(seq_length)
print(seq)
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print("Energy of native conformation: %f" % lattice.nativeE(seq))
print("stability of native conformation: %f" % lattice.stability(seq))
print("fraction folded: %f" % lattice.fracfolded(seq))
The lattice protein package comes with a drawing module that creates SVG drawing of the lattice conformations.
In [5]:
conf = lattice.native_conf(seq)
lp.draw.in_notebook(seq, conf)
Out[5]:
The LatticeThermodynamics object can also do the above calculations while using a specified target native state.
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# Find the 5 lowest energy conformations.
alt_conf = lattice.confs.k_lowest_confs(seq, 1.0, 5)
# Choose the 5th lowest as the target fold.
target = alt_conf[-1]
lp.draw.in_notebook(seq, target)
Out[6]:
In [7]:
print("Energy of native conformation: %f" % lattice.nativeE(seq, target=target))
print("stability of native conformation: %f" % lattice.stability(seq, target=target))
print("fraction folded: %f" % lattice.fracfolded(seq, target=target))