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Membrane Protein Design: From Reprogramming Functions to AI-Guided De Novo Design Approaches
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DOI：10.1021/acs.chemrev.5c01105.png)
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Abstract
En 中文
Computational membrane protein design has rapidly evolved from early physics-based modeling into a mature discipline powered by high-throughput experimental screening and cutting-edge AI technologies. The convergence of these approaches is transforming our capacity to probe natural membrane protein systems and to engineer sophisticated cell-based functions. Membrane proteins, in particular, offer a uniquely fertile landscape for computational engineering, enabling the stabilization of challenging therapeutic targets, the rewiring of cellular behaviors, and the de novo construction of entirely synthetic transmembrane architectures. Recent advances now allow designers to reprogram cellular signaling through distinct downstream pathways in response to custom-defined ligands. Together, these developments are laying the foundation for generalizable biosensing platforms and the creation of de novo transmembrane proteins with precisely tailored functions.
Keywords:
Cell signaling
De novo modeling
Ligands
Peptides and proteins
Receptors
Journal
IF:
55.8
Papers:
557
Citations:
24.7W
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Cited Papers