Select the model

Prediction of drug solubility in supercritical CO2

The model predicts the solubility of drugs in supercritical carbon dioxide by employing the CatBoost method with CDK descriptors and the drug’s melting point as input variables. Users need to input the drug’s representation in the SMILES format, in addition to the supercritical state’s temperature and pressure conditions.

Prediction of absorption maximum and IC50 of Pt-BODIPY

These models are capable of predicting the absorption maximum (CatBoost/ECFP) and IC50 (kNN/text vectorization) values  for BODIPY-appended platinum complexes. Additionally, the models facilitate the search for similar structures by calculating the Euclidean distance between the Morgan Fingerprint vectors of the input structure and the structures in the training database.

Prediction of absorption maximum of substituted porphyrins and metalloporphyrins

This model is based on the CatBoost method using the Morgan fragment descriptors. The complete experimental dataset consisted of 10,849 records, which were used to evaluate the absorption maximum wavelength of porphyrins and metalloporphyrins. The dataset included both free porphyrins and chlorins, as well as their complexes with various metal ions such as zinc(II), nickel(II), copper(II), cobalt(II), gold(III), indium(III), palladium(II), platinum(II), silver(II), cadmium(II), magnesium(II), and aluminum(III).

Prediction of absorption maximum and molar absorption coefficient of various dyes

This model can predict the absorption maximum and molar absorption coefficient (CatBoost/ECFP) for various classes of dyes, such as xanthenes, acridines, diarylmethanes, anthraquinones, and dipyrromethenes.

Prediction of 11B NMR chemical shift of BODIPY

This model based on an RFR machine learning method using the ISIDA fragment descriptors for predicting the 11B NMR chemical shift of BODIPY.

Prediction of sensor ability based on chemical formula

This model can be used to find a sensor structure similar to your molecule. The database contains information about various classes of chemosensors, such as dipyrromethenes, BODIPY, Schiff bases, hydrazones, fluorescein, rhodamine, phenanthroline, coumarin, naphthalimide derivatives, and others.