Authors
Yinghao Wu
Published in
Chembiochem : a European journal of chemical biology. Volume 27. Issue 21. Nov 12, 2026.
Abstract
Recent advances in AI-driven structure prediction have transformed structural biology but remain limited for cell-surface proteins mediating transient, context-dependent interactions. Multidomain architectures, flexible linkers, and coupled cis- and trans-interactions challenge current models, leading to inaccurate predictions for key adhesion molecules. These limitations highlight the need to incorporate cellular context, conformational dynamics, and multivalent interactions. Emerging strategies, including MD-informed machine learning, generative models, and multiscale simulations integrated with experimental restraints, offer promising solutions. Together, these approaches aim to bridge static structure prediction with dynamic, physiologically relevant modeling of protein interactions at cell-cell interfaces.
PMID:
42961090
Bibliographic data and abstract were imported from PubMed on 30 Oct 2026.
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