Can I optimize sequences before lab submission?

Yes, the skill provides workflows for using computational tools like SolubleMPNN, ESM, and NetSolP to address issues like aggregation and poor solubility.

How long does it take to get experimental results?

Experimental results for submitted protein sequences are typically delivered within approximately 21 days.

How do I get API access for Adaptyv?

The platform is currently in alpha/beta; you must contact support@adaptyvbio.com to request an API access token.

What types of protein assays can I perform?

The platform supports binding assays (using biolayer interferometry), expression testing, thermostability characterization, and enzyme activity assays.

What is the Adaptyv Claude Code Skill?

It is a specialized capability that allows Claude to interact with Adaptyv's cloud laboratory platform to automate protein testing, sequence optimization, and validation.

Adaptyv Protein Engineering

Name: Adaptyv Protein Engineering
Author: pathvanasoftware

bypathvanasoftware

데이터 과학 및 ML

Automates protein testing and validation through a cloud laboratory platform for high-throughput protein design workflows.

소개

Adaptyv is a specialized Claude Code Skill that connects computational protein design with real-world wet-lab validation. It enables researchers to submit protein sequences for automated testing—including binding assays, thermostability measurements, and expression testing—directly through an API-driven cloud lab. The skill also provides integrated guidance for sequence optimization using advanced tools like SolubleMPNN and ESM, streamlining the transition from AI-generated designs to experimental results with a typical 21-day turnaround.

주요 기능

Automated protein sequence submission for wet-lab validation
Support for binding, expression, thermostability, and enzyme assays
0 GitHub stars
API-driven workflow management for high-throughput protein design
Real-time experiment status tracking and result downloading
Integrated sequence optimization using SolubleMPNN, ESM, and NetSolP

사용 사례

Validating AI-generated protein designs in a physical laboratory environment
High-throughput screening of protein-target interactions for drug discovery
Optimizing protein sequences for improved solubility and expression levels

소개

주요 기능

Automated protein sequence submission for wet-lab validation
Support for binding, expression, thermostability, and enzyme assays
0 GitHub stars
API-driven workflow management for high-throughput protein design
Real-time experiment status tracking and result downloading
Integrated sequence optimization using SolubleMPNN, ESM, and NetSolP

사용 사례

Validating AI-generated protein designs in a physical laboratory environment
High-throughput screening of protein-target interactions for drug discovery
Optimizing protein sequences for improved solubility and expression levels