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Found 11 Skills
Run ProteinMPNN inverse folding via NVIDIA NIM to design protein sequences for a target backbone. Use for ProteinMPNN, inverse folding, sequence design, backbone redesign, fixed chains/residues, omit_AAs, sampling temperature, soluble model, hosted NVIDIA API, local Docker, PDB input, and multi-FASTA output.
Orchestrate an end-to-end de novo protein binder design campaign against a protein target by composing BioNeMo NIM skills. Use for binder design, minibinder design, de novo binders, RFdiffusion + ProteinMPNN + Boltz2/OpenFold3 pipelines, epitope/hotspot-targeted design, in-silico binder validation, and ranking designs by interface confidence.
Design protein sequences using ProteinMPNN inverse folding. Use this skill when: (1) Designing sequences for RFdiffusion backbones, (2) Redesigning existing protein sequences, (3) Fixing specific residues while designing others, (4) Optimizing sequences for expression or stability, (5) Multi-state or negative design. For backbone generation, use rfdiffusion or bindcraft. For ligand-aware design, use ligandmpnn. For solubility optimization, use solublempnn.
Design novel protein therapeutics (binders, enzymes, scaffolds) using AI-guided de novo design. Uses RFdiffusion for backbone generation, ProteinMPNN for sequence design, ESMFold/AlphaFold2 for validation. Use when asked to design protein binders, therapeutic proteins, or engineer protein function.
Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation. For standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.
Run RFDiffusion protein backbone design via NVIDIA NIM. Use for de novo protein backbones, motif scaffolding, binder design, hotspot residues, contigs syntax, diffusion steps, hosted NVIDIA API calls, local Docker deployment, and PDB backbone outputs for ProteinMPNN sequence design.
Ligand-aware protein sequence design using LigandMPNN. Use this skill when: (1) Designing sequences around small molecules, (2) Enzyme active site design, (3) Ligand binding pocket optimization, (4) Metal coordination site design, (5) Cofactor binding proteins. For standard protein design, use proteinmpnn. For solubility optimization, use solublempnn.
Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.
OpenBio API for biological data access and computational biology tools. Use when: (1) Querying biological databases (PDB, UniProt, ChEMBL, etc.), (2) Searching scientific literature (PubMed, bioRxiv, arXiv), (3) Running structure prediction (Boltz, Chai, ProteinMPNN), (4) Performing pathway/enrichment analysis, (5) Designing molecular biology experiments (primers, cloning), (6) Analyzing variants and clinical data.
All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For backbone-only generation, use rfdiffusion. For sequence-only design, use proteinmpnn. For structure validation, use boltz.
End-to-end guidance for protein design pipelines. Use this skill when: (1) Starting a new protein design project, (2) Need step-by-step workflow guidance, (3) Understanding the full design pipeline, (4) Planning compute resources and timelines, (5) Integrating multiple design tools. For tool selection, use binder-design. For QC thresholds, use protein-qc.