chemaxon.calculations.admet_predictors

class HergClassificationType(enum.IntEnum):

Enumeration for hERG inhibition classification types used in the hERG classification predictor.

@dataclass(frozen=True)
class HergClassResult:

hERG inhibition prediction result object

HergClassResult( classification: HergClassificationType, error: list[HergClassificationType], probabilities: dict[HergClassificationType, int])
classification: HergClassificationType

Classification result.

error: list[HergClassificationType]
probabilities: dict[HergClassificationType, int]

Probabilities for each classification type.

@dataclass(frozen=True)
class HergActivityResult:

hERG inhibition activity prediction result object

HergActivityResult(value: float, error: float)
value: float

Predicted hERG inhibition activity.

error: float

Error of the predicted hERG inhibition activity.

class BbbFunction(enum.IntEnum):

Enumeration for blood-brain barrier penetration properties used in the BBB predictor.

ARO_R = <BbbFunction.ARO_R: 0>

Number of aromatic rings.

HA = <BbbFunction.HA: 1>

Number of heavy atoms.

MWHBN = <BbbFunction.MWHBN: 2>

MW^(-0.5) * (HBN), where HBN = HBA + HBD.

TPSA = <BbbFunction.TPSA: 3>

Topological polar surface area.

PKA = <BbbFunction.PKA: 4>

PKa calculation for bbb score.

@dataclass(frozen=True)
class BbbProperty:

Blood-brain barrier penetration prediction property object

BbbProperty(value: float, multiplied_score: float, score: float)
value: float

Predicted value for the property.

multiplied_score: float

Predicted score for the property, calculated by multiplying the predicted value with the corresponding coefficient for the property.

score: float

Predicted score for the property.

@dataclass(frozen=True)
class BbbResult:

Blood-brain barrier penetration prediction result object

BbbResult( score: float, properties: dict[BbbFunction, BbbProperty])
score: float

Multiplied predicted blood-brain barrier penetration score of the property scores.

properties: dict[BbbFunction, BbbProperty]

Predicted blood-brain barrier penetration scores for each property used in the prediction, as well as the predicted value for each property.

class CnsMpoFunction(enum.IntEnum):

Enumeration for CNS MPO score prediction properties used in the CNS MPO predictor.

HBD = <CnsMpoFunction.HBD: 0>

Number of hydrogen bond donors.

LOGD = <CnsMpoFunction.LOGD: 1>

Calculated distribution coefficient az pH 7.4.

LOGP = <CnsMpoFunction.LOGP: 2>

Lipophilicity, calculated partition coefficient.

MW = <CnsMpoFunction.MW: 3>

Molecular weight.

PKA = <CnsMpoFunction.PKA: 4>

Most basic center (pKa).

TPSA = <CnsMpoFunction.TPSA: 5>

Topological polar surface area.

@dataclass(frozen=True)
class CnsMpoProperty:

CNS MPO score prediction property

CnsMpoProperty(value: float, score: float)
value: float

Predicted value for the property.

score: float

Predicted score for the property.

@dataclass(frozen=True)
class CnsMpoResult:

CNS MPO score prediction result object

CnsMpoResult( score: float, properties: dict[CnsMpoFunction, CnsMpoProperty])
score: float

Predicted CNS MPO score calculated by summing the predicted scores of the properties.

properties: dict[CnsMpoFunction, CnsMpoProperty]

Predicted CNS MPO scores for each property used in the prediction, as well as the predicted value for each property.

def herg_classification( mol: chemaxon.molecule.Molecule) -> HergClassResult:

Predict hERG class inhibition.

For more information: https://docs.chemaxon.com/latest/calculators_herg.html?h=herg#the-herg-classification-model

Example usage:

from chemaxon import import_mol
from chemaxon import herg_classification

mol = import_mol("CCN(CC)CCOC(=O)c1ccccc1C(=O)O")
result = herg_classification(mol)
print(f'Classification: {result.classification}')
print(f'Probabilities: {result.probabilities}')
Parameters
  • mol: Molecule - Input molecule
Returns

HergClassResult - Result object containing classification

def herg_activity( mol: chemaxon.molecule.Molecule) -> HergActivityResult:

Predict hERG inhibition activity.

For more information: https://docs.chemaxon.com/latest/calculators_herg.html?h=herg#the-herg-activity-model

Example usage:

from chemaxon import import_mol
from chemaxon import herg_activity

mol = import_mol("CCN(CC)CCOC(=O)c1ccccc1C(=O)O")
result = herg_activity(mol)
print(f'value: {result.value}')
print(f'error: {result.error}')
Parameters
  • mol: Molecule - Input molecule
Returns

int - Predicted hERG inhibition activity

def bbb( mol: chemaxon.molecule.Molecule) -> BbbResult:

Predict blood-brain barrier penetration.

For more information: https://docs.chemaxon.com/latest/calculators_bbb-score.html?h=bbb+score#blood-brain-barrier-bbb-score-predictor

Example usage:

from chemaxon import import_mol
from chemaxon.calculations import bbb

mol = import_mol("CCN(CC)CCOC(=O)c1ccccc1C(=O)O")
result = bbb(mol)
print(f'value: {result.score}')
print(f'error: {result.properties}')
Parameters
  • mol: Molecule - Input molecule
Returns

BbbResult - Predicted blood-brain barrier scores by properties and the overall (multiplied) score

def cns_mpo( mol: chemaxon.molecule.Molecule) -> CnsMpoResult:

Predict CNS MPO score.

For more information: https://docs.chemaxon.com/latest/calculators_cns-mpo-score.html

Example usage:

from chemaxon import import_mol
from chemaxon.calculations import cns_mpo

mol = import_mol("CCN(CC)CCOC(=O)c1ccccc1C(=O)O")
result = cns_mpo(mol)
print(f'value: {result.score}')
print(f'error: {result.properties}')
Parameters
  • mol: Molecule - Input molecule
Returns

CnsMpoResult - Predicted CNS MPO score and scores by properties