Skill for protein structure prediction and analysis with AlphaFold. Use this skill whenever a user wants to predict or fetch a protein 3D structure, download structures from the AlphaFold Database (AFDB), run ColabFold for novel proteins, parse pLDDT confidence scores or PAE (predicted aligned error) from AlphaFold…
Skill for structure prediction with AlphaFold 3 (AF3) from Google DeepMind. Use this skill when a user wants to predict the structure of a protein complex with ligands, DNA, or RNA; predict protein-ligand binding poses; model protein-nucleic acid interactions; use SMILES or CCD codes to specify small molecules; parse…
Skill for biomolecular structure and binding affinity prediction with Boltz-2. Use this skill when a user wants to predict protein-ligand complex structures, estimate binding affinities (IC50/ΔG), screen compound libraries, optimize lead compounds, model protein-DNA or protein-RNA interactions, specify binding pockets…
Skill for biomolecular structure prediction with Chai-1 from Chai Discovery. Use this skill when a user wants to predict protein structures, protein-ligand complexes, protein-nucleic acid complexes, or multi-chain biomolecular assemblies. Also trigger when the user mentions Chai-1, chai-lab, or wants an…
Skill for protein-ligand docking with DiffDock, a diffusion model that generates 3D binding poses from protein structure and ligand SMILES. Use this skill when a user wants to dock a small molecule to a protein, predict binding poses, run blind docking (no pocket specification required), or process batches of…
Skill for working with ESM2 protein language models from Meta FAIR. Use this skill whenever the user wants to generate protein embeddings or representations, score variant effects or predict mutation fitness, run contact prediction, or use ESMFold for structure prediction. Also trigger when the user mentions ESM2…
Skill for generative protein design with ESM3 from EvolutionaryScale. Use this skill whenever a user wants to design or generate novel protein sequences, complete masked or partial sequences, predict 3D structure from sequence, perform inverse folding (design a sequence for a target structure), do function-conditioned…
Skill for efficient protein embeddings using ESM-C (ESM Cambrian) from EvolutionaryScale. Use this skill whenever a user wants to generate protein embeddings or representations, compute sequence similarities, run protein classification or regression from embeddings, cluster proteins, build a sequence similarity index…
Skill for genomic sequence modeling and design with Evo2 from Arc Institute. Use this skill when a user wants to model or generate DNA sequences, score variant effects at single-nucleotide resolution, extract genomic embeddings, analyze mutations in non-coding or coding regions, design synthetic genomic elements…
Skill for protein sequence-structure translation using ProstT5 from Rostlab. Use this skill when a user wants to predict protein structure as a 3Di structural alphabet string (Foldseek tokens) from an amino acid sequence, do inverse folding (recover an amino acid sequence from a 3Di structure), embed both amino acid…
Skill for inverse folding — designing amino acid sequences for a given protein backbone structure. Use this skill when a user wants to design sequences for a PDB structure, score sequences against a structure, design symmetric oligomers with tied positions, fix specific residues while redesigning others, or use…
Skill for protein embeddings using ProtTrans models (ProtT5, ProtBERT) from Rostlab. Use this skill whenever a user wants protein embeddings or representations for downstream ML tasks, protein classification (subcellular localization, membrane prediction, secondary structure annotation), similarity search, or…
Skill for de novo protein backbone generation with RFdiffusion from the Baker Lab (Institute for Protein Design). Use this skill when a user wants to design a new protein backbone from scratch, scaffold a functional motif into a new protein, design a protein binder against a target, generate symmetric oligomers…
Skill for RNA sequence analysis with RNA-FM, a foundation model trained on 23 million non-coding RNA sequences. Use this skill when a user wants to embed RNA sequences, predict RNA secondary structure, classify RNA families, or analyze mRNA with mRNA-FM. Also trigger when the user mentions RNA-FM, RNA foundation…
Skill for single-cell biology with scGPT, a foundation model trained on 33 million human single cells. Use this skill when a user wants to annotate cell types, predict perturbation responses, integrate multi-batch scRNA-seq data, extract cell embeddings, perform reference mapping, infer gene regulatory networks, or…