{
  "id": 12206,
  "url": "https://arxiv.org/abs/2607.18144v1",
  "title": "Do Language Models Dream of Binding Molecules? Benchmarking LLMs under Spatial Constraints",
  "summary": "Structure-based drug design (SBDD) leverages the 3D structure of protein targets, often complemented by other spatial constraints, to generate candidate binding molecules. While diffusion models have dominated as a leading paradigm for high-quality 3D molecule generation, LLM-based methods are rapidly emerging in molecular design and have shown competitive performance in pocket-conditioned molecular generation. However, their ability to reason about physics and 3D spatial environments is largely",
  "authors": "Thomas MacDougall, Maksim Kuznetsov, Roman Schutski, Rim Shayakhmetov, Maxim Malkov, Vladimir Aladinskiy, Alex Aliper, Alex Zhavoronkov",
  "category": "research",
  "topics": "healthcare,environment,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-20T16:43:54.000Z",
  "fetched_at": "2026-07-21T05:10:12.656Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/12206",
  "original_url": "https://arxiv.org/abs/2607.18144v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}