Skill UI

Cloud-native Rowan orchestrates medicinal chemistry and molecular modeling pipelines via a Python API, offering pKa prediction, docking, descriptors, dynamics, and AI-driven structure workflows for scalable batch screening without local HPC.

Query UCSF’s ZINC22 repository of 230M+ purchasable compounds via the web UI or CartBlanche APIs to fetch IDs/SMILES, run similarity, supplier, or random sampling, and assemble docking-ready libraries for virtual screening.

DiffDock is a state-of-the-art, diffusion-based deep learning tool for predicting 3D binding poses of drug-like ligands to protein targets. It supports both PDB files and amino acid sequences for proteins, and accepts diverse ligand formats (SMILES, SDF, MOL2). It is designed for structure-based drug discovery, lead optimization, and high-throughput virtual screening campaigns, providing predicted poses and confidence scores.

Rowan is a cloud-native workflow platform providing a unified Python API for complex molecular modeling and medicinal chemistry tasks. It handles property prediction (pKa, descriptors), conformational analysis, molecular docking, and molecular dynamics. Users can run scalable, multi-step drug discovery pipelines and batch screening campaigns without managing local high-performance computing infrastructure.

Tamarind Bio is a comprehensive cloud platform providing access to state-of-the-art open-source tools for structural biology and molecular design. It supports complex tasks including protein structure prediction (AlphaFold, ESMFold), molecular design (RFdiffusion, ProteinMPNN), protein-ligand docking, and binding affinity prediction. Users submit sequences or structures and receive predicted results without requiring local GPU hardware.