ReviewMolecular cell2026
Programming biological behavior with AI-guided de novo protein design.
Review in Molecular cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
Abstract
Driven by advances in artificial intelligence, de novo protein design can now generate diverse molecular functions from the ground up, achieving remarkable success in engineering binders against many macromolecular targets. Here, we provide a perspective on how de novo design can progress beyond bimolecular interactions toward the bottom-up construction of protein reaction networks. We highlight how programmable, modular, and controllable de novo components can drive complex, emergent biological behaviors. Overcoming current challenges-including designable protein dynamics, multi-step functionalities, and non-equilibrium systems-is essential for this transition. With continued foundational method improvements, the field is poised to pioneer precise protein perturbations for systems-level insight and to engineer emergent cellular behaviors like signal amplification, decision-making, and error correction de novo to fundamentally advance synthetic biology, biotechnology, and medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.