smiles

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactions" (https://advances.sciencemag.org/content/7/15/eabe4166).

Molecode presents molecules as code and enables LLMs to operate and reason on chemistry directly.

A lightweight python-only library for reading and writing SMILES strings

SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS

DeepSMILES - A variant of SMILES for use in machine-learning

The repository contains the network and the related scripts for encoder-decoder based Chemical Image Recognition

Draw molecules with plotly!

⚗️ An all-in-one solution for chemical property retrieval from PubChem.

PyTorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

MCP server that draws structures, reactions, mechanisms, peptides and proteins for Claude. Structures are drawn locally with RDKit; names, data sheets and proteins are looked up online.

pytoda - PaccMann PyTorch Dataset Classes. Read the docs: https://paccmann.github.io/paccmann_datasets/

Implementation of the paper "Neuraldecipher - Reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures" by Tuan Le, Robin Winter, Frank Noé and Djork-Arné Clevert

3D diverse conformers generation using rdkit

Reproducible cleaning and standardization of SMILES-based chemical datasets

Deterministic structure-to-IUPAC-name generator. Names are checked by an OPSIN round trip, the engine declines rather than guess, and --provenance says how each name was checked.

Updated fast, rule-free atom mapping for chemical reactions with a full pipeline to train, select, and evaluate your own RXNMapper/ALBERT model.

Automated BigSMILES conversion workflow and dataset for homopolymeric macromolecules

Peptide <-> SMILES utilities for monomer peptides with non-canonical residues, terminal modifications, and selected cyclizations.

Extract Molecular SMILES embeddings from language models pre-trained with various objectives architectures.