campaign-manager

Protein binder design campaign planning converts high-level goals like producing 10 binders for EGFR into a recommended pipeline, throughput targets, and expected yields. It provides stepwise pipeline recommendations and cost estimates to guide your GPU workloads.

Estimating GPU runtime and cost for a protein design pipeline involves calculating approximate cost per job and expected runtime based on your selected toolchain. The campaign manager provides budgeting and scheduling guidance for GPU workloads across recommended pipelines.

BoltzGen and Chai can be used together in a binder discovery pipeline. The skill recommends concrete toolchains like BoltzGen followed by Chai and protein-qc, or using BindCraft end-to-end, providing runtime and cost guidance for each configuration.

Protein binder campaigns fail quality control due to common failure modes surfaced by computing pass rates and classifying campaign health. The skill assesses QC metrics to classify campaign health as EXCELLENT, GOOD, MARGINAL, or POOR and diagnoses why candidate sets fail.

This campaign orchestration tool requires no specific dependencies or components to function. It operates independently to provide pipeline recommendations, pass-rate metrics, and cost estimates for protein binder discovery projects.

Assessing binder design campaign health involves computing pass rates and classifying campaign health into EXCELLENT, GOOD, MARGINAL, or POOR categories. The skill surfaces common failure modes and provides health assessment metrics to evaluate candidate set quality.