The nuclear pore complex (NPC) is the gateway betwceen the cytoplasm and the nucleoplasm. This massive structure embedded in the nuclear envelope is one of the largest protein complexes in the cell and thus contains many intricacies that remain poorly understood. One such question is how the proteins within the NPC, called FG-Nups, named for their numerous phenylalanine-glycine (FG) repeats, filter cargo molecules during nuclear transport. These cargos often require the support of a nuclear transport receptor (NTR) to complete the traversal. NTRs such as importin-β interact transiently with FG motifs to traverse the pore, but the relative contribution of proposed importin-β binding sites to efficient transport remains unclear. Building on the binding motifs mapped by Isgro and Schulten (2005), we constructed a coarse-grained model comprising FG-Nup polymers and an importin-β representation with site-specific FG interaction parameters. We executed >25,000 independent simulations (20 μs each) and performed systematic “site-ablation” tests by selectively deactivating individual importin-β sites. Transport was quantified by pore-crossing probability, flux, mean first-passage time, and bound-state lifetimes under physiologically relevant crowding. Results: A small subset of importin-β sites disproportionately governs NPC traversal. Ablation of these high-impact sites decreased crossing probability and flux and increased non-productive dwell times, while secondary sites offered partial redundancy that buffered transport. Contact-map analyses revealed a redistribution of FG interaction hotspots when key sites were removed. Our results support a functionally unequal, partially redundant” affinity landscape for importin-β, yielding testable predictions for site-directed mutagenesis and FG-chemistry perturbations. Rather than defining generic “optimal cargos,” the work provides a principled way to rank importin-β sites that nucleate productive hopping through the FG network, refining mechanistic models of NPC transport and informing NTR-guided delivery strategies.
Mansour et al. (Sun,) studied this question.