def test_protein_folding_problem_2_second_bead_side_chain(self):
"""Tests if a protein folding problem is created and returns a correct qubit operator if
a second main bead has a side chain."""
lambda_back = 10
lambda_chiral = 10
lambda_1 = 10
penalty_terms = PenaltyParameters(lambda_chiral, lambda_back, lambda_1)
main_chain_residue_seq = "SAAS"
side_chain_residue_sequences = ["", "A", "A", ""]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
mj_interaction = MiyazawaJerniganInteraction()
protein_folding_problem = ProteinFoldingProblem(
peptide, mj_interaction, penalty_terms)
qubit_op = protein_folding_problem._qubit_op_full()
expected_path = self.get_resource_path(
"test_protein_folding_problem_2_second_bead_side_chain",
PATH,
)
expected = read_expected_file(expected_path)
self.assertEqual(qubit_op, expected)
def create_protein_folding_result(main_chain: str, side_chains: List[str],
turn_sequence: str) -> ProteinFoldingResult:
"""
Creates a protein_folding_problem, solves it and uses the result
to create a protein_folding_result instance.
Args:
main_chain: The desired main_chain for the molecules to be optimized
side_chains: The desired side_chains for the molecules to be optimized
turn_sequence: The best sequence found by ProteinFoldingResult pre-computed
Returns:
Protein Folding Result
"""
algorithm_globals.random_seed = 23
peptide = Peptide(main_chain, side_chains)
mj_interaction = MiyazawaJerniganInteraction()
penalty_back = 10
penalty_chiral = 10
penalty_1 = 10
penalty_terms = PenaltyParameters(penalty_chiral, penalty_back, penalty_1)
protein_folding_problem = ProteinFoldingProblem(peptide, mj_interaction,
penalty_terms)
protein_folding_problem.qubit_op()
return ProteinFoldingResult(
unused_qubits=protein_folding_problem.unused_qubits,
peptide=protein_folding_problem.peptide,
turn_sequence=turn_sequence,
)
def test_get_result_binary_vector_compressed(self):
"""Tests if a protein folding result returns a correct expanded best sequence."""
lambda_back = 10
lambda_chiral = 10
lambda_1 = 10
penalty_terms = PenaltyParameters(lambda_chiral, lambda_back, lambda_1)
main_chain_residue_seq = "SAASSASAA"
side_chain_residue_sequences = [
"", "", "A", "A", "A", "A", "A", "A", ""
]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
mj_interaction = MiyazawaJerniganInteraction()
protein_folding_problem = ProteinFoldingProblem(
peptide, mj_interaction, penalty_terms)
best_sequence = "101110010"
protein_folding_problem._unused_qubits = [0, 1, 2, 5, 7]
protein_folding_result = ProteinFoldingResult(protein_folding_problem,
best_sequence)
result = protein_folding_result.get_result_binary_vector()
expected_sequence = "101110*0*10***"
self.assertEqual(result, expected_sequence)
def test_check_turns(self):
"""
Tests that check turns operators are generate correctly.
"""
main_chain_residue_seq = "SAASSA"
side_chain_residue_sequences = ["", "", "A", "A", "A", ""]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
bead_2 = peptide.get_main_chain[2]
bead_3 = peptide.get_main_chain[3]
bead_4 = peptide.get_main_chain[4]
side_bead_2 = bead_2.side_chain[0]
side_bead_3 = bead_3.side_chain[0]
side_bead_4 = bead_4.side_chain[0]
lambda_back = 10
lambda_chiral = 10
lambda_1 = 10
penalty_params = PenaltyParameters(lambda_chiral, lambda_back, lambda_1)
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
t_23 = qubit_op_builder._create_turn_operators(bead_2, bead_3)
t_34 = qubit_op_builder._create_turn_operators(bead_3, bead_4)
t_2s3 = qubit_op_builder._create_turn_operators(side_bead_2, bead_3)
t_3s4s = qubit_op_builder._create_turn_operators(side_bead_3, side_bead_4)
expected_path_t23 = self.get_resource_path(
"test_check_turns_expected_t23",
PATH,
)
expected_t23 = read_expected_file(expected_path_t23)
expected_path_t34 = self.get_resource_path(
"test_check_turns_expected_t34",
PATH,
)
expected_t34 = read_expected_file(expected_path_t34)
expected_path_t2s3 = self.get_resource_path(
"test_check_turns_expected_t2s3",
PATH,
)
expected_t_2s3 = read_expected_file(expected_path_t2s3)
expected_path_t3s4s = self.get_resource_path(
"test_check_turns_expected_t3s4s",
PATH,
)
expected_t_3s4s = read_expected_file(expected_path_t3s4s)
self.assertEqual(t_23, expected_t23)
self.assertEqual(t_34, expected_t34)
self.assertEqual(t_2s3, expected_t_2s3)
self.assertEqual(t_3s4s, expected_t_3s4s)
def test_create_h_short(self):
"""
Tests that the Hamiltonian to back-overlaps is created correctly.
"""
main_chain_residue_seq = "APRLAAAA"
side_chain_residue_sequences = ["", "", "A", "A", "A", "A", "A", ""]
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_short = qubit_op_builder._create_h_short()
expected = PauliSumOp.from_list([("IIIIIIIIIIIIIIIIIIIIIIIIIIII", 0)])
self.assertEqual(h_short, expected)
def test_create_h_bbsc_and_h_scbb_3(self):
"""
Tests if H_BBBB Hamiltonian qubit operator is built correctly.
"""
main_chain_residue_seq = "SAACS"
side_chain_residue_sequences = ["", "", "A", "A", ""]
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_bbsc, h_scbb = qubit_op_builder._create_h_bbsc_and_h_scbb()
self.assertEqual(h_bbsc, 0)
self.assertEqual(h_scbb, 0)
def test_create_h_bbbb(self):
"""Tests if H_BBBB Hamiltonian qubit operator is built correctly."""
main_chain_residue_seq = "SAASSASA"
side_chain_residue_sequences = ["", "", "A", "", "", "A", "A", ""]
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_bbbb = qubit_op_builder._create_h_bbbb()
expected_path = self.get_resource_path(
"test_create_h_bbbb_expected",
PATH,
)
expected = read_expected_file(expected_path)
self.assertEqual(h_bbbb, expected)
def test_create_h_chiral_2(self):
"""
Tests that the Hamiltonian chirality constraints is created correctly.
"""
main_chain_residue_seq = "SAACS"
side_chain_residue_sequences = ["", "", "A", "A", ""]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_chiral = qubit_op_builder._create_h_chiral()
expected_path = self.get_resource_path(
"test_create_h_chiral_2_expected",
PATH,
)
expected = read_expected_file(expected_path)
self.assertEqual(h_chiral, expected)
def test_build_qubit_op(self):
"""Tests if a total Hamiltonian qubit operator is built correctly."""
lambda_back = 10
lambda_chiral = 10
lambda_1 = 10
main_chain_residue_seq = "SAASSASAA"
side_chain_residue_sequences = ["", "", "A", "A", "A", "A", "A", "A", ""]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
mj_interaction = MiyazawaJerniganInteraction()
penalty_params = PenaltyParameters(lambda_chiral, lambda_back, lambda_1)
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
qubit_op = qubit_op_builder._build_qubit_op()
expected_path = self.get_resource_path(
"test_build_qubit_op_expected",
PATH,
)
expected = read_expected_file(expected_path)
self.assertEqual(qubit_op, expected)
def test_create_h_back_side_chains(self):
"""
Tests that the Hamiltonian to back-overlaps is created correctly in the presence of side
chains which should not have any influence in this case.
"""
main_chain_residue_seq = "SAASS"
side_chain_residue_sequences = ["", "", "A", "A", ""]
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_back = qubit_op_builder._create_h_back()
expected_path = self.get_resource_path(
"test_create_h_back_side_chains_expected",
PATH,
)
expected = read_expected_file(expected_path)
self.assertEqual(h_back, expected)
def test_create_h_bbsc_and_h_scbb(self):
"""Tests if H_BBSC and H_SCBB Hamiltonians qubit operators are built correctly."""
main_chain_residue_seq = "APRLAAA"
side_chain_residue_sequences = ["", "", "A", "", "", "A", ""]
mj_interaction = MiyazawaJerniganInteraction()
pair_energies = mj_interaction.calculate_energy_matrix(main_chain_residue_seq)
peptide = Peptide(main_chain_residue_seq, side_chain_residue_sequences)
penalty_params = PenaltyParameters()
qubit_op_builder = QubitOpBuilder(peptide, pair_energies, penalty_params)
h_bbsc, h_scbb = qubit_op_builder._create_h_bbsc_and_h_scbb()
expected_path_h_bbsc = self.get_resource_path(
"test_create_h_bbsc_and_h_scbb_expected_h_bbsc",
PATH,
)
expected_path_h_scbb = self.get_resource_path(
"test_create_h_bbsc_and_h_scbb_expected_h_scbb",
PATH,
)
expected_h_bbsc = read_expected_file(expected_path_h_bbsc)
expected_h_scbb = read_expected_file(expected_path_h_scbb)
self.assertEqual(h_bbsc, expected_h_bbsc)
self.assertEqual(h_scbb, expected_h_scbb)