Retrosynthesis Comparison
AiZynthFinder vs ASKCOS vs RetroTRAE: Retrosynthesis Planning (2026)
Last updated: 2026-04-16
Retrosynthesis planning — working backward from a target molecule to purchasable starting materials — is a core challenge in medicinal chemistry. AiZynthFinder (AstraZeneca) and ASKCOS (MIT) are the two leading open-source multi-step planning tools, both using MCTS-based tree search but with different design philosophies. RetroTRAE offers a template-free single-step alternative that avoids SMILES translation artifacts. Here's how they compare.
AiZynthFinder
AstraZeneca Molecular AI
RetroTRAE
KNU LCBC (Kyungpook National University)
Head-to-Head
Structured comparison across key dimensions.
| Dimension | AiZynthFinder | RetroTRAE | |
|---|---|---|---|
| Approach | MCTS tree search with template-based expansion policy | MCTS + Retro* tree search with template-based AND template-free models | Template-free single-step using atom environment translation (no SMILES) |
| Multi-step planning? | Yes — MCTS with configurable depth and time limits | Yes — MCTS + Retro* + interactive path planner (IPP) | No — single-step only (needs external tree search for multi-step) |
| Single-step accuracy | Depends on expansion policy; template-based models competitive on USPTO | Multiple models available; template-based ~50-60% top-1 on USPTO-50K | 58.3% top-1 on USPTO-50K (61.6% with analogs); avoids invalid SMILES |
| Template-free? | Primarily template-based; supports custom models | Both — 4 one-step models covering template-based and template-free | Yes — fully template-free (atom environment representation) |
| Web UI | Basic Jupyter widget; no production web UI | Full-featured web application with interactive path planner | No — command-line/library only |
| Additional modules | Route scoring, stock databases, clustering | Forward synthesis, condition recommendation, reaction feasibility, site selectivity, solubility | Single-step retrosynthesis only |
| Speed | Fast — seconds per target molecule (MCTS) | Moderate — more comprehensive search, slightly slower | Fast — single inference per step |
| Codebase complexity | Clean, modular Python — easy to extend and customize | Large full-stack application (Django + React); complex to self-host | Small research codebase |
| License | MIT | MIT (ASKCOS open-source) | Open source |
| Key limitation | Template-dependent by default; no built-in condition recommendation | Heavy deployment (Docker/microservices); harder to integrate into custom pipelines | Single-step only; less adopted; no multi-step planning capability |
When to Use Each
AiZynthFinder
You want a lightweight, fast Python library for retrosynthetic planning. You need MCTS-based multi-step search. You want to extend or customize the search with your own reaction models. You're integrating retrosynthesis into a larger pipeline.
RetroTRAE
You need template-free single-step retrosynthesis without SMILES translation artifacts. You want atom-environment-based predictions that generalize to novel chemistry. You're benchmarking or comparing single-step model architectures.
Practitioner Verdict
Use AiZynthFinder for fast, extensible retrosynthetic planning in a Python-native workflow — it's the most developer-friendly option with strong MCTS search. Use ASKCOS for the most comprehensive synthesis planning suite with interactive path planning, condition recommendation, and both template-based and template-free models. Use RetroTRAE when you need template-free single-step retrosynthesis that avoids SMILES-based translation errors.
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