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Astrid Jung

Publications and source records attributed to Astrid Jung.

2 recordsLinked to original sources

Uncoupling Kapbeta2 substrate dissociation and ran binding.

Karyopherinbeta2 (Kapbeta2) imports a variety of mRNA binding proteins into the nucleus. Release of import substrates in the nucleus involves formation of a high-affinity Kapbeta2-RanGTP complex and concomitant dissociation of import substrates. The crystal structure of the Kapbeta2-RanGppNHp complex shows that Ran binds in the Kapbeta2 N-terminal arch and substrate most likely binds its C-terminal arch. The structure suggested a mechanism for Ran-mediated substrate dissociation where a long internal acidic loop in Kapbeta2 transmits structural information between the GTPase and substrate sites, leading to displacement of substrate by the loop when Ran is bound. To study the molecular mechanism of substrate dissociation, we have cleaved the acidic loop of Kapbeta2 proteolytically (cl-Kapbeta2) and also constructed a mutant of Kapbeta2 with a truncated loop (TL-Kapbeta2). Both modified Kapbeta2s are unable to undergo Ran-mediated substrate dissociation. We have also mapped the boundaries of the Kapbeta2 binding site of substrate mRNA binding protein A1 using a widely applicable method employing NMR spectroscopy. This has allowed design of reagents to quantitate the affinities of the Kapbeta2 proteins for Ran and substrate. cl-Kapbeta2, TL-Kapbeta2, and native Kapbeta2 have comparable affinities for both RanGppNHp and import substrates, indicating that perturbation of the loop has not altered the strength of binary Kapbeta2-Ran or Kapbeta2-substrate interactions. The TL-Kapbeta2 mutant also binds RanGppNHp and substrate simultaneously to form a ternary complex, indicating that in addition to the loss of coupling between Ran binding and substrate dissociation, the two ligand sites on Kapbeta2 are spatially distinct. The uncoupling of Ran binding and substrate dissociation in the TL-Kapbeta2 mutant is further evident in significant loss of Ran-mediated nuclear uptake of fluorescent substrate in digitonin-permeabilized HeLa cells. These results support our previously proposed GTPase-mediated Kapbeta2-substrate dissociation mechanism where the acidic loop of Kapbeta2 physically couples distinct Ran and substrate binding sites.

Active Transport, Cell Nucleus↗

Automated assignment of NOESY NMR spectra using a knowledge based method (KNOWNOE).

Automated assignment of NOESY spectra is a prerequisite for automated structure determination of biological macromolecules. With the program KNOWNOE we present a novel, knowledge based approach to this problem. KNOWNOE is devised to work directly with the experimental spectra without interference of an expert. Besides making use of routines already implemented in AUREMOL, it contains as a central part a knowledge driven Bayesian algorithm for solving ambiguities in the NOE assignments. These ambiguities mainly arise from chemical shift degeneration which allows multiple assignments of cross peaks. Using a set of 326 protein NMR structures, statistical tables in the form of atom-pairwise volume probability distributions (VPDs) were derived. VPDs for all assignment possibilities relevant to the assignments of interproton NOEs were calculated. With these data for a given cross peak with N possible assignments Ai (i = 1,...,N) the conditional probabilities P(Ai, a/V0) can be calculated that the assignment Ai determines essentially all (a-times) of the cross peak volume V0. An assignment Ak with a probability P(Ak, a/V0) higher than 0.8 is transiently considered as unambiguously assigned. With a list of unambiguously assigned peaks a set of structures is calculated. These structures are used as input for a next cycle of iteration where a distance threshold Dmax is dynamically reduced. The program KNOWNOE was tested on NOESY spectra of a medium size protein, the cold shock protein (TmCsp) from Thermotoga maritima. The results show that a high quality structure of this protein can be obtained by automated assignment of NOESY spectra which is at least as good as the structure obtained from manual data evaluation.

Algorithms↗