Characterize:
Protein Intelligence Engine
Characterize deciphers your protein’s function and context — from domains to PTMs and binding pockets — so you design smarter, faster experiments. Powered by Astra AI models, it integrates evolutionary signals and structural data to deliver residue-level, evidence-backed insights.
Protein function is scattered, noisy, and hard to trust.
Annotations are incomplete, evidence is hidden in papers, and context is missing — leaving teams to make critical design decisions half-blind.
Sparse Annotations
Most proteins have partial or outdated functional data — key PTMs, binding pockets, or motifs go completely unreported.
Scattered Evidence
Insights are buried across databases, papers, and lab notes, forcing researchers to reconcile conflicting data manually.
Costly Missteps
Missing or misinterpreting a critical residue leads to failed experiments, wasted constructs, and misleading hypotheses downstream.
From Blind Spots to Complete Context with Characterize
Characterize turns your protein sequence into a full functional profile — domains, PTMs, pockets, and partners — so you see every residue in context and make better design calls before you touch the bench.
Residue-Level Resolution
Characterize maps every residue’s potential role — from catalytic sites and motifs to PTMs and binding pockets — so you know what to preserve or probe.
Functional Context
See domain architecture, evolutionary conservation, subcellular localization, and interaction partners in one view, removing the guesswork from variant design.
Evidence You Can Trust
Each prediction is shown with confidence scores and flags for uncertainty — helping you focus on what’s actionable, and what's exploratory.
