Introduction

DeepMol is a Python-based machine and deep learning framework for drug discovery. It offers a variety of functionalities that enable a smoother approach to many drug discovery and chemoinformatics problems. It uses Tensorflow, Keras, Scikit-learn and DeepChem to build custom ML and DL models or make use of pre-built ones. It uses the RDKit framework to perform operations on molecular data.

Here is an image with the overall pipeline of DeepMol and the packages it uses:

Google colabs to run AutoML

• Binary and multiclass classification

• Regression

• Multi-task/multi-label

Available models

In our publication, we present several case studies associated to Absorption, Distribution, Metabolism, Excretion, and Toxicity of molecules. We made them available to make predictions on new data in the following repository: https://github.com/BioSystemsUM/deepmol_case_studies. Moreover, other models from other publications are also made available. Check it out the link to know more.

Alternatively, if you want to use the models directly in a Google Colab, you can access it directly here.

Models available so far:

Model Name	How to Call	Prediction Type
BBB (Blood-Brain Barrier)	BBB	Penetrates BBB (1) or does not penetrate BBB (0)
AMES Mutagenicity	AMES	Mutagenic (1) or not mutagenic (0)
Human plasma protein binding rate (PPBR)	PPBR	Rate of PPBR expressed in percentage
Volume of Distribution (VD) at steady state	VDss	Volume of Distribution expressed in liters per kilogram (L/kg)
Caco-2 (Cell Effective Permeability)	Caco2	Cell Effective Permeability (cm/s)
HIA (Human Intestinal Absorption)	HIA	Absorbed (1) or not absorbed (0)
Bioavailability	Bioavailability	Bioavailable (1) or not bioavailable (0)
Lipophilicity	Lipophilicity	Lipophilicity log-ratio
Solubility	Solubility	Solubility (log mol/L)
CYP P450 2C9 Inhibition	CYP2C9Inhibition	Inhibit (1) or does not inhibit (0)
CYP P450 3A4 Inhibition	CYP3A4Inhibition	Inhibit (1) or does not inhibit (0)
CYP2C9 Substrate	CYP2C9Substrate	Metabolized (1) or does not metabolize (0)
CYP2D6 Substrate	CYP2D6Substrate	Metabolized (1) or does not metabolize (0)
CYP3A4 Substrate	CYP3A4Substrate	Metabolized (1) or does not metabolize (0)
Hepatocyte Clearance	HepatocyteClearance	Drug hepatocyte clearance (uL.min-1.(10^6 cells)-1)
NPClassifier	NPClassifier	Pathway, Superclass, Class
Plants secondary metabolite precursors predictor	PlantsSMPrecursorPredictor	Precursor 1; Precursor 2
Microsome Clearance	MicrosomeClearance	Drug microsome clearance (mL.min-1.g-1)
LD50	LD50	LD50 (log(1/(mol/kg)))
hERG Blockers	hERGBlockers	hERG blocker (1) or not blocker (0)