Loading homepage
ProteinMPNN — deep learning-based protein sequence design from backbone structures. Uses message passing neural networks to predict amino acid sequences that fold into a given 3D backbone. Supports fi
Use with AI
Install the MCP server or CLI to instantly fetch ProteinMPNN documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/proteinmpnn
Boltz-1 — open-source deep learning model for predicting biomolecular 3D structures and interactions, approaching AlphaFold3-level accuracy. Supports protein, DNA, RNA, and small-molecule ligand struc
2 shared topics • 3 shared operations
Gnina — deep learning molecular docking program built on AutoDock Vina. Uses convolutional neural networks (CNNs) to rescore protein-ligand poses for improved binding pose prediction and virtual scree
2 shared topics • 3 shared operations
RoseTTAFold — deep learning-based protein structure prediction using a three-track neural network architecture for simultaneous processing of 1D sequence, 2D distance maps, and 3D coordinates. Predict
2 shared topics • 3 shared operations
TorchDrug — PyTorch-based machine learning platform for drug discovery and graph representation learning. Supports molecule property prediction, molecular generation, retrosynthesis planning, knowledg
2 shared topics • 3 shared operations
Prosit — deep learning framework for predicting MS2 fragment ion spectra and indexed retention times (iRT) from peptide sequences. Enables in silico spectral library generation for any organism and pr
3 shared topics • 1 shared operation