deepchem

GNN, GCN, Molecular Solubility, RDKit, Cheminformatics

Agent Skills for small-molecule and protein therapeutics: cheminformatics, molecular ML, docking and dynamics, protein design platforms, and target-discovery knowledge graphs.

Chempleter is a lightweight generative model to predict syntactically valid extensions of molecular structures.

XGBoost and GNN training and models for prediction of Hansen solubility parameters

With the rise of deep learning models and the successful result showing in different domains (such as Computer vision and Natural language processing)researchers and laboratories of chem-informatics try to apply these techniques in drug design and discovery. recently,the application of Deep Learning in this area of research has made a good progr…

A computational tutorial for predicting drug formulation properties using DeepChem

Using DeepChem with TensorFlow 2.x and Keras

HIV molecules inhibitor classification using GNN with attention

Molecule water solubility prediction using DeepChem.

---------BBM420 -------- UNDERGRADUATE PROJECT FINAL REPORT

Docker for reproducing solubility model

This is an introductory deep learning model which uses the Deepchem package. Lots of credit has to be given to the authors(Ramsundar B., Eastman P., Walters P., Pande V.) of the book "Deep Learning for the Life Sciences". This book has been a gold mine in terms of my exploration and journey in DeepLearning in the field of biochemistry.

some scripts using deepchem

A Graph Neural Network to classify human HIV inhibitor molecules using DeepChem feature extractor

This is a research project as part of the course CSE-700 : Independent Study, that I had taken up for Spring 2020 at the University at Buffalo.

practical notebooks for learning and applying machine learning in chemistry and cheminformatics.

Scaffold-split benchmark suite for ADMET property prediction (hERG, solubility, CYP3A4, Caco-2, clearance) with Morgan FP+RF and MPNN baselines, plus ECE/calibration metrics for uncertainty-aware evaluation. PyTorch · RDKit · DeepChem · scikit-learn.

End-to-end ML pipeline for drug toxicity and solubility prediction from SMILES. RDKit · DeepChem · XGBoost · Scaffold CV

Optimizing Mistral-7B for BACE-1 inhibitor prediction using Low-Rank Adaptation (r=8) to capture peak generalization on scaffold-split molecular data. Achieved 0.8034 ROC-AUC. Built for DeepChem GSoC '26.

Molecular property prediction on BBBP using Mistral-7B. Features Nitrogen valence sanitization and property-aware prompting (MW/TPSA). Achieved 0.75+ ROC-AUC on scaffold splits for DeepChem GSoC '26.