Can this skill estimate project costs?

Yes, it provides detailed cost and time breakdowns for various tools (like RFdiffusion, ProteinMPNN, and ColabFold) based on typical GPU compute usage.

How does the skill assess campaign health?

It analyzes structural metrics such as pLDDT (confidence), ipTM (interface quality), and scRMSD (structural accuracy) to determine if a design batch is likely to succeed in the lab.

Does it support different design strategies?

Yes, it offers specialized templates for high-throughput diversity, high-quality precision, and quick exploration using faster models like ESMFold.

What is a protein binder design campaign?

A binder design campaign is a structured sequence of computational steps—including backbone generation, sequence design, and structural validation—aimed at creating new proteins that bind specifically to a target molecule.

Protein Design Campaign Manager

Name: Protein Design Campaign Manager
Author: adaptyvbio

byadaptyvbio

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Ciencia de Datos y ML

Orchestrates complex protein binder design campaigns from high-level goal definition to high-throughput pipeline execution.

The Protein Design Campaign Manager skill provides a comprehensive framework for planning, monitoring, and optimizing protein binder design projects. It acts as a high-level orchestrator for specialized tools like RFdiffusion and ProteinMPNN, helping users convert abstract biological objectives into executable computational pipelines. By providing precise cost estimates, time projections, and automated health assessment metrics, it enables researchers to maximize design yields and efficiently diagnose bottlenecks in the design-to-validation workflow.

Características Principales

01Target difficulty assessment and tool selection guidance

02End-to-end pipeline orchestration for protein binder design

03Campaign health monitoring with automated pass-rate analysis

04Accurate GPU compute cost and time estimation

05Standardized templates for high-throughput and high-quality design variants

0675 GitHub stars

Casos de Uso

01Planning a complete binder design campaign for therapeutic protein targets like EGFR

02Diagnosing failures in design quality control metrics like pLDDT, ipTM, or scRMSD

03Estimating the required budget and GPU time for large-scale protein screenings

Características Principales

01Target difficulty assessment and tool selection guidance

02End-to-end pipeline orchestration for protein binder design

03Campaign health monitoring with automated pass-rate analysis

04Accurate GPU compute cost and time estimation

05Standardized templates for high-throughput and high-quality design variants

0675 GitHub stars

Casos de Uso

01Planning a complete binder design campaign for therapeutic protein targets like EGFR

02Diagnosing failures in design quality control metrics like pLDDT, ipTM, or scRMSD

03Estimating the required budget and GPU time for large-scale protein screenings