概览介绍
Protein sequence design using ligand and atomic context. Designed sequences need expression and functional testing; not every ligand context is supported equally.
信息已比对权威文献或官方白皮书；非实验性跑分。 权威出处 · 最后核对: 16/09/2026, 17:33:40 UTC
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Protein sequence design using ligand and atomic context. Designed sequences need expression and functional testing; not every ligand context is supported equally.
Protein sequence design using ligand and atomic context. Designed sequences need expression and functional testing; not every ligand context is supported equally.
信息已比对权威文献或官方白皮书；非实验性跑分。 权威出处 · 最后核对: 16/09/2026, 17:33:40 UTC
Use this citation format when referencing LigandMPNN in scientific publications and benchmark papers.
@software{ligandmpnn_2026,
title = {{LigandMPNN}},
author = {{LigandMPNN authors}},
year = {2026},
url = {https://github.com/dauparas/LigandMPNN},
note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}Live scientific citations queried from Europe PMC and PubMed for LigandMPNN.
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LigandMPNN Scientific Architecture · Credit: LigandMPNN authors · Open original ↗
Research and editorial use Source & attribution ↗ License ↗
同一科学领域的同类算法与工具。
Research AI model / method · Research code or publication
All-atom protein structure diffusion conditioned on specific ligand or nucleic acid atomic context.
Baker Lab
AI Model · Research Preview
AI system for generating novel, high-affinity protein binders directly from target structures
Google DeepMind
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