De la autor
De novo antibody and nanobody (VHH) design with Germinal. Use this skill when: (1) Designing epitope-targeted nanobodies or scFvs, (2) Needing CDR design on a fixed framework, (3) Working on antibody-format binders rather than miniproteins. For miniprotein binders, use binder-design (BoltzGen, BindCraft, RFdiffusion, Mosaic). For structure validation, use boltz or chai.
Instalare
npx skills add adaptyvbio/protein-design-skills --skill germinal -a claude-code
Se instalează în .claude/skills/germinal/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
Vrei ca agentul să-ți propună skill-uri în timp ce scrii? Vezi cum folosești skill-urile din IDE.
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 80
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- protein-binder-designK-Dense-AI/drug-discovery-agent-skillsDesign new proteins that bind a chosen surface, using BindCraft's AlphaFold2-guided hallucination or the RFdiffusion backbone plus ProteinMPNN sequence pipeline. Use this skill to specify a target epitope by hotspot residue, trim a receptor to the region worth designing against, set up a design campaign, and filter the output on the in-silico metrics that predict experimental success — interface predicted TM-score, predicted aligned error at the interface, buried surface area, and shape complementarity. Also trigger on BindCraft, RFdiffusion, ProteinMPNN, minibinder, hallucination, inverse folding, hotspot residue, epitope targeting, ipTM, or de novo binder.Design★ 51
- antibody-engineeringK-Dense-AI/drug-discovery-agent-skillsNumber antibody variable domains, annotate CDRs, and assess developability from sequence. Use this skill to apply IMGT, Kabat, Chothia, Martin, or AHo numbering with ANARCI, delimit CDRs and framework regions, scan for chemical liabilities (N-glycosylation sequons, deamidation NG, isomerisation DG, oxidation, unpaired cysteine, fragmentation), compute pI, net charge, extinction coefficient and hydrophobicity, and plan humanisation by CDR grafting. Also trigger on antibody, nanobody, VHH, scFv, Fab, CDR, framework, ANARCI, abnumber, IgBLAST, OAS, SAbDab, humanization, Vernier residues, or developability.Știință★ 51
- rfdiffusionadaptyvbio/protein-design-skillsGenerate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers. For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold or chai. For QC thresholds, use protein-qc.Design★ 173
- binder-designadaptyvbio/protein-design-skillsGuidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).Design★ 173
- boltzgenBioTender-max/awesome-bio-agent-skillsAll-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.Design★ 213
- proteinmpnnaipoch/open-scienceInverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.Design★ 5.4K
Note și recenzii
—
nicio recenzie
Ai încercat acest skill? Notează-l ca să-i ajuți pe alții. Autentifică-te
Discuție
Intră în discuție. Autentifică-te