fingerprint | index /home/orient/pydpi/src/pydpi/drug/fingerprint.py

`##############################################################################
This module is to compute the various fingerprints based on the provided
fingerprint system. If you have any question please contact me via email.
My email adress is : orientalcds@gmail.com
2012.09.25
@author: Dongsheng Cao
##############################################################################`

Modules
`` |  |
rdkit.Chem.AllChem rdkit.Chem | rdkit.DataStructs rdkit.Chem.Fingerprints.FingerprintMols | rdkit.Chem.MACCSkeys rdkit.Chem.AtomPairs.Pairs | rdkit.Chem.AtomPairs.Torsions

Functions
`` |  | CalculateAtomPairsFingerprint(mol) `################################################################# Calculate atom pairs fingerprints Usage: result=CalculateAtomPairsFingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateDaylightFingerprint(mol) `################################################################# Calculate Daylight-like fingerprint or topological fingerprint (2048 bits). Usage: result=CalculateDaylightFingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateEstateFingerprint(mol) `################################################################# Calculate E-state fingerprints (79 bits). Usage: result=CalculateEstateFingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateFP4Fingerprint(mol) `################################################################# Calculate FP4 fingerprints (307 bits). Usage: result=CalculateFP4Fingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateMACCSFingerprint(mol) `################################################################# Calculate MACCS keys (166 bits). Usage: result=CalculateMACCSFingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateMorganFingerprint(mol, radius=2) `################################################################# Calculate Morgan Usage: result=CalculateMorganFingerprint(mol) Input: mol is a molecule object. radius is a radius. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################` CalculateSimilarity(fp1, fp2, similarity='Tanimoto') `################################################################# Calculate similarity between two molecules. Usage: result=CalculateSimilarity(fp1,fp2) Input: fp1 and fp2 are two DataStructs. Output: result is a similarity value. #################################################################` CalculateTopologicalTorsionFingerprint(mol) `################################################################# Calculate Topological Torsion Fingerprints Usage: result=CalculateTopologicalTorsionFingerprint(mol) Input: mol is a molecule object. Output: result is a tuple form. The first is the number of fingerprints. The second is a dict form whose keys are the position which this molecule has some substructure. The third is the DataStructs which is used for calculating the similarity. #################################################################`

Data
`` |  | Version = 1.0 similaritymeasure = ['Tanimoto', 'Dice', 'Cosine', 'Sokal', 'Russel', 'Kulczynski', 'McConnaughey', 'Asymmetric', 'BraunBlanquet']