admet

KERMT is a pretrained graph neural network model for molecular property prediction.

Accurate ADMET Prediction with XGBoost

Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference

Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems

Auditable generation and multi-objective triage of structurally diverse, drug-like molecules with RDKit.

A script using RDKit to reproduce the BBB score reported by Gupta.

Multi-objective Pareto analysis of drug-like molecules. Paste SMILES, get instant Pareto analysis. 100% client-side.

Claude Plugin for CompChem , Drug Discovery & Organic Chemistry reasoning

Reproducible predictors for time-dependent CYP3A4 and CYP2D6 inhibition and CYP3A4-ligand structures (OpenADMET CYP Inhibition Blind Challenge): nested cross-validation without selection bias, pre-registered gates, a ledger of negative results and an audited rebuild.

Agent skill for choosing small-molecule design tools for molecular generation, synthesis planning, docking, and property prediction.

The open computational chemistry engine for drug discovery and materials science; MCP + REST + Workbench + Next.js dashboard, wrapping RDKit, GROMACS, AutoDock, OpenFold, Chai, Boltz, Gnina.

Reproducible R pipeline for network pharmacology analysis of plant extracts — from GC-MS data to pre-docking candidate prioritization

This repository contains code and documentation for participating in the OpenADMET + ExpansionRx Blind Challenge. The goal of this challenge is to develop machine learning models to predict various ADMET properties of small molecules using the provided dataset.

Here I provide some code that enables users to calculate CNS MPO score for their molecules, based on the SMILES and known pKa values.

ADMET calculations from different research paper and a goal to make it memory efficent with ML implementations.

Template for running a blind ML prediction challenge: scoring backend, OpenTofu AWS infrastructure, and a Hugging Face frontend.

This project presents a web-based AI-driven platform designed to predict key ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) properties of drug-like molecules.

Hackathon ADMET 2024 - evaluating the danger of the molecules for humans using ML.

🤖 Use GitHub Actions and admetMesh to predict admet automatically per 30 minutes.

AI campaign orchestrator for drug discovery that plans with OpenClaw and executes Refua MCP tools, including autonomous loops and portfolio ranking.