mlsanityData to 14 Oct 2026

Molecular LLM Agents: From Architectural Design to Scientific Autonomy

arXiv 2608.23104 ↗First posted 24 Aug 2026cs.CL cs.AIcited by 0

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or web environments, molecular LLM agents must perceive, reason about, and act upon chemical objects across symbolic strings, molecular graphs, 3D conformations, spectra, simulations, and wet-lab measurements. Their capabilities depend on chemically faithful molecular perception, an LLM-centered agent framework, domain-specific tool grounding, and computational or experimental feedback, in addition to planning and tool use. This work develops a conceptual framework for molecular LLM agents from two complementary perspectives. First, we introduce an architectural view of molecular-agent design, covering molecular representation and perception, the agent framework, domain-specific toolboxes, and learning and optimization. Second, we propose a scientific autonomy ladder inspired by staged autonomy in engineering systems, categorizing agents into four levels: L1 assistive or fixed workflows, L2 adaptive computational agents, L3 feedback-aware physical experiment agents, and L4 scientific-agenda agents. Together, these two perspectives establish a comprehensive framework for comparing existing molecular LLM agents, identifying missing capabilities and deployment risks, and guiding the design, evaluation, and deployment of future agents in molecular discovery workflows.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 72 of its 168 references that are in the map. First posted on arXiv 24 Aug 2026.

Builds on

72 of 168 references.

Closest ancestors · 17

Same direction, newest first

  1. 2026MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents27 May
  2. 2026ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery12 May
  3. 2026Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning8 May
  4. 2026Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design22 Apr
  5. 2026Towards Agentic Intelligence for Materials Science29 Jan
  6. 2026M^4olGen: Multi-Agent, Multi-Stage Molecular Generation under Precise Multi-Property Constraints15 Jan
  7. 2025Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Functional Materials Discovery15 Dec
  8. 2025MADD: Multi-Agent Drug Discovery Orchestra11 Nov
  9. 2025FROGENT: An End-to-End Full-process Drug Design Multi-Agent System14 Aug
  10. 2025Large Language Model Agent for Modular Task Execution in Drug Discovery26 Jun
  11. 2025MT-Mol:Multi Agent System with Tool-based Reasoning for Molecular Optimization27 May
  12. 2025DrugPilot: LLM-based Parameterized Reasoning Agent for Drug Discovery20 May
5 more
  1. 2025El Agente: An Autonomous Agent for Quantum Chemistry5 May
  2. 2025RAG-Enhanced Collaborative LLM Agents for Drug Discovery22 Feb
  3. 2024AgentDrug: Utilizing Large Language Models in An Agentic Workflow for Zero-Shot Molecular Editing17 Oct
  4. 2024CACTUS: Chemistry Agent Connecting Tool-Usage to Science2 May
  5. 2023Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis16 Nov

Other references · 55

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2017MoleculeNet: A Benchmark for Molecular Machine Learningcited by 1,051
  5. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 765
  6. 2018Junction Tree Variational Autoencoder for Molecular Graph Generationcited by 652
  7. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 571
  8. 2019Analyzing Learned Molecular Representations for Property Predictioncited by 375
  9. 2018Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generationcited by 364
  10. 2018GuacaMol: Benchmarking Models for De Novo Molecular Designcited by 297
  11. 2018Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Modelscited by 275
  12. 2017Molecular De Novo Design through Deep Reinforcement Learningcited by 267
38 more
  1. 2021Pre-training Molecular Graph Representation with 3D Geometrycited by 248
  2. 2018Optimization of Molecules via Deep Reinforcement Learningcited by 200
  3. 2017Deep Reinforcement Learning for De-Novo Drug Designcited by 161
  4. 2024CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmarkcited by 123
  5. 2025Agent Lightning: Train ANY AI Agents with Reinforcement Learningcited by 109
  6. 2023Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspectivecited by 92
  7. 2025A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Modelscited by 87
  8. 2024ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Areacited by 71
  9. 2023DrugAssist: A Large Language Model for Molecule Optimizationcited by 59
  10. 2025Training a Scientific Reasoning Model for Chemistrycited by 56
  11. 2022MolScribe: Robust Molecular Structure Recognition with Image-To-Graph Generationcited by 49
  12. 2023Gotta be SAFE: A New Framework for Molecular Designcited by 48
  13. 2023SELFormer: Molecular Representation Learning via SELFIES Language Modelscited by 40
  14. 2022Group SELFIES: A Robust Fragment-Based Molecular String Representationcited by 33
  15. 2024Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planningcited by 29
  16. 2024Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generationcited by 25
  17. 2019Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representationcited by 23
  18. 2024UniMoT: Unified Molecule-Text Language Model with Discrete Token Representationcited by 23
  19. 2025MDCrow: Automating Molecular Dynamics Workflows with Large Language Modelscited by 22
  20. 2023De novo Drug Design using Reinforcement Learning with Multiple GPT Agentscited by 19
  21. 2024Large Language Models are In-Context Molecule Learnerscited by 18
  22. 2023Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Designcited by 17
  23. 2023Controlling risks of AI in chemical science with agentscited by 17
  24. 2025GeLLMO: Generalizing Large Language Models for Multi-property Molecule Optimizationcited by 17
  25. 2025Chem-R: Learning to Reason as a Chemistcited by 17
  26. 2025AutoLabs: Cognitive Multi-Agent Systems with Self-Correction for Autonomous Chemical Experimentationcited by 15
  27. 2026SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agentscited by 15
  28. 2025MatTools: Benchmarking Large Language Models for Materials Science Toolscited by 12
  29. 2026Benchmarking AI Agents for Addressing Scientific Challenges Across Scalescited by 12
  30. 2024A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoningcited by 11
  31. 2026MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamicscited by 7
  32. 2026MADE: Benchmark Environments for Closed-Loop Materials Discoverycited by 7
  33. 2025ASKCOS: an open source software suite for synthesis planningcited by 5
  34. 2025ChemHTS: Hierarchical Tool Stacking for Enhancing Chemical Agentscited by 4
  35. 2025AtomDisc: An Atom-level Tokenizer that Boosts Molecular LLMs and Reveals Structure--Property Associationscited by 4
  36. 2026MDGYM: Benchmarking AI Agents on Molecular Simulationscited by 4
  37. 2025ChemActor: Enhancing Automated Extraction of Chemical Synthesis Actions with LLM-Generated Datacited by 3
  38. 2026Chemical Chain-of-Thought Functions as a Hallucination-Prone Molecular Scratchpadcited by 3

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  3. 2026Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents
  4. 2026MDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
  5. 2026CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows
  6. 2024LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
  7. 2025Beyond Protein Language Models: An Agentic LLM Framework for Mechanistic Enzyme Design
  8. 2026M3OS: A Monte Carlo Graph Search-Orchestrated Multi-Agent LLM System for Evidence-Traced Molecular Optimization