# iqspr v2.3

0

0th

Percentile

## Inverse Molecular Design

Autonomous generation of novel organic compounds with target physicochemical properties initially constrained by the user. This package has the ambition to become an unavoidable tool in the innovation of novel materials and/or drugs with specific target properties.

## Functions in iqspr

 Name Description QSPRpred-class QSPRpred class SmcChem-class SMILES generator get_descriptors get a list of the available descriptors types get_linearBayes get the computation of parameters issued from the training of a Bayesian linear regression ENgram-class Extended N-gram model for learning SMILES strings Esmi-class Extend smi class use_linearBayes get the prediction from a Bayesian linear regression viewstr view 2D structures from SMILES string vector get_Model construct a given regression model thanks to a training set get_Model_params get a list of default parameters for a given regression algorithm get_Models get a list of the implemented regression algorithms get_descriptor get a descriptor (fingerprints and/or CDK physical descriptors) from SMILES strings dpred Table of 372 SMILES with predicted internal energy E and HOMO-LUMO gap engram_5k n-grams model learned from 5,000 SMILES from PubChem predinit Table of predicted internal energy E and HOMO-LUMO gap for the phenol genENgram generate SMILES strings from extended N-gram model gensmis Table of 372 SMILES with associated QSPRScore get_targetzone get a targeted zone predictions List of predictions associated to the internal energy E and HOMO-LUMO gap of 500 SMILES trainedSMI List of 5,000 SMILES used for training the n-grams model use_Model get the prediction from a given model qspr.data Table of 16,674 SMILES with associated internal energy E and HOMO-LUMO gap No Results!