Do I need special credentials to use this skill?

Yes, you must request an API access token from Adaptyv Bio (support@adaptyvbio.com) to authenticate your requests.

How long does the wet-lab validation process take?

Experimental results are typically delivered in approximately 21 days following the submission of your protein sequences.

What experimental results can I get with Adaptyv?

Adaptyv provides data on binding assays, expression testing, thermostability measurements, and enzyme activity assays.

Which computational tools are supported for sequence optimization?

The skill integrates with NetSolP, SoluProt, SolubleMPNN, ESM, ipTM, and pSAE to help address solubility and stability before lab submission.

Is Adaptyv suitable for high-throughput workflows?

Absolutely. It is specifically designed to support high-throughput, AI-driven protein design cycles that require scalable experimental feedback.

Adaptyv Cloud Protein Lab

Name: Adaptyv Cloud Protein Lab
Author: Activer007

byActiver007

数据科学与机器学习

Facilitates automated protein design, sequence optimization, and wet-lab validation via a cloud-based laboratory platform.

关于

Adaptyv is a specialized skill for Claude Code that bridges the gap between computational protein design and physical laboratory validation. It enables researchers and developers to optimize protein sequences using advanced tools like SolubleMPNN and ESM, and then submit those designs directly to a cloud-based wet lab for automated testing. This skill streamlines the entire protein engineering lifecycle—from addressing solubility and aggregation issues in-silico to receiving real-world data on binding assays, expression levels, and thermostability within a unified workflow.

主要功能

Wet-lab validation for protein expression and thermostability
Automated protein sequence submission and experiment tracking via API
0 GitHub stars
Support for binding assays and protein-target interaction testing
In-silico optimization using SolubleMPNN, ESM, and NetSolP
Managed workflows for high-throughput AI-driven protein design

使用场景

Optimizing protein sequences for improved solubility and expression before synthesis
Validating AI-generated protein designs with real-world laboratory data
High-throughput screening of protein-target interactions using automated binding assays

关于

主要功能

Wet-lab validation for protein expression and thermostability
Automated protein sequence submission and experiment tracking via API
0 GitHub stars
Support for binding assays and protein-target interaction testing
In-silico optimization using SolubleMPNN, ESM, and NetSolP
Managed workflows for high-throughput AI-driven protein design

使用场景

Optimizing protein sequences for improved solubility and expression before synthesis
Validating AI-generated protein designs with real-world laboratory data
High-throughput screening of protein-target interactions using automated binding assays