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Peer-reviewedCC BY 4.0Chemistry (Weinheim an Der Bergstrasse, Germany)

From Caffeine to Aspirin: Everyday Molecules as Triggers for Genetically Encoded Proximity Systems

  • Mingguang Cui1
  • Tianlu Wang1
  • Yaoyu Han1
  • Yun Huang2,3
  • Tien‐Hung Lan1
  • Yunbin Zhou1,3
  1. 1Center for Translational Cancer Research Institute of Biosciences and Technology Texas A&M University Houston Texas USA
  2. 2Center for Epigenetics and Disease Prevention Institute of Biosciences and Technology Texas A&M University Houston Texas USA
  3. 3Department of Translational Medical Sciences College of Medicine Texas A&M University Houston Texas USA
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Abstract

Chemically induced proximity (CIP) enables programmable control of gene expression, protein activity, cellular signaling, and engineered cell functions using small molecules. Yet many classical CIP platforms rely on ligands that may limit therapeutic translation owing to unfavorable biosafety profiles, off‐target activity, incomplete reversibility, dosing constraints, and potential immunogenicity of engineered components. This perspective highlights dietary small molecule‐ and OTC drug‐responsive CIP systems as emerging platforms for translational chemogenetic control. We focus on two complementary design strategies. One exploits nanobody‐derived binders against familiar small molecules, as exemplified by synthetic anti‐caffeine nanobody‐based systems. The other adapts naturally evolved ligand‐binding proteins through rational protein engineering, as illustrated by salicylate‐responsive platforms derived from plant salicylic acid (SA)‐binding receptors for reversible proximity control and aspirin‐responsive gene regulation. Together, these engineered systems demonstrate how familiar molecules such as caffeine, SA, and aspirin can be transformed into programmable biological inputs. We further discuss how artificial intelligence (AI)‐guided protein engineering may expand this design space by enabling de novo construction and functional reprogramming of ligand‐responsive modules, leading to safer and clinically compatible proximity‐control systems.

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Cite

BibTeXRIS
BibTeX
@article{cui2026from,
  title = {{From Caffeine to Aspirin: Everyday Molecules as Triggers for Genetically Encoded Proximity Systems}},
  author = {Mingguang Cui and Tianlu Wang and Yaoyu Han and Yun Huang and Tien‐Hung Lan and Yunbin Zhou},
  journal = {Chemistry (Weinheim an Der Bergstrasse, Germany)},
  year = {2026},
  month = aug,
  doi = {10.1002/chem.71530},
  url = {https://doi.org/10.1002/chem.71530},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - From Caffeine to Aspirin: Everyday Molecules as Triggers for Genetically Encoded Proximity Systems
AU  - Mingguang Cui
AU  - Tianlu Wang
AU  - Yaoyu Han
AU  - Yun Huang
AU  - Tien‐Hung Lan
AU  - Yunbin Zhou
PY  - 2026
DA  - 2026/08/03
JO  - Chemistry (Weinheim an Der Bergstrasse, Germany)
DO  - 10.1002/chem.71530
UR  - https://doi.org/10.1002/chem.71530
AB  - Chemically induced proximity (CIP) enables programmable control of gene expression, protein activity, cellular signaling, and engineered cell functions using small molecules. Yet many classical CIP platforms rely on ligands that may limit therapeutic translation owing to unfavorable biosafety profiles, off‐target activity, incomplete reversibility, dosing constraints, and potential immunogenicity of engineered components. This perspective highlights dietary small molecule‐ and OTC drug‐responsive CIP systems as emerging platforms for translational chemogenetic control. We focus on two complementary design strategies. One exploits nanobody‐derived binders against familiar small molecules, as exemplified by synthetic anti‐caffeine nanobody‐based systems. The other adapts naturally evolved ligand‐binding proteins through rational protein engineering, as illustrated by salicylate‐responsive platforms derived from plant salicylic acid (SA)‐binding receptors for reversible proximity control and aspirin‐responsive gene regulation. Together, these engineered systems demonstrate how familiar molecules such as caffeine, SA, and aspirin can be transformed into programmable biological inputs. We further discuss how artificial intelligence (AI)‐guided protein engineering may expand this design space by enabling de novo construction and functional reprogramming of ligand‐responsive modules, leading to safer and clinically compatible proximity‐control systems.
SN  - 0947-6539
SN  - 1521-3765
ER  -