Metallothionein and a peptide modeled after metallothionein, EmtinB, induce neuronal differentiation and survival through binding to receptors of the low-density lipoprotein receptor family.

Accumulating evidence suggests that metallothionein (MT)-I and -II promote neuronal survival and regeneration in vivo. The present study investigated the molecular mechanisms underlying the differentiation and survival-promoting effects of MT and a peptide modeled after MT, EmtinB. Both MT and EmtinB directly stimulated neurite outgrowth and promoted survival in vitro using primary cultures of cerebellar granule neurons. In addition, expression and surface localization of megalin, a known MT receptor, and the related lipoprotein receptor-related protein-1 (LRP) are demonstrated in cerebellar granule neurons. By means of surface plasmon resonance MT and EmtinB were found to bind to both megalin and LRP. The bindings were abrogated in the presence of receptor-associated protein-1, an antagonist of the low-density lipoprotein receptor family, which also inhibited MT- and EmtinB-induced neurite outgrowth and survival. MT-mediated neurite outgrowth was furthermore inhibited by an anti-megalin serum. EmtinB-mediated inhibition of apoptosis occurred without a reduction of caspase-3 activity, but was associated with reduced expression of the pro-apoptotic B-cell leukemia/lymphoma-2 interacting member of cell death (Bim(S)). Finally, evidence is provided that MT and EmtinB activate extracellular signal-regulated kinase, protein kinase B, and cAMP response element binding protein. Altogether, these results strongly suggest that MT and EmtinB induce their neuronal effects through direct binding to surface receptors belonging to the low-density lipoprotein receptor family, such as megalin and LRP, thereby activating signal transduction pathways resulting in neurite outgrowth and survival.

Crosstalk between metal ions in Bacillus subtilis ferrochelatase.

Ferrochelatase (EC 4.99.1.1), the terminal enzyme in the heme biosynthetic pathway, catalyzes the insertion of Fe2+ into protoporphyrin IX, generating heme. In vitro assays have shown that all characterized ferrochelatases can also incorporate Zn2+ into protoporphyrin IX. Previously Zn2+ has been observed at an inner metal binding site close to the porphyrin binding site. Mg2+, which stimulates Zn2+ insertion by Bacillus subtilis ferrochelatase, has been observed at an outer metal binding site. Exchange of Glu272 to a serine eliminated the stimulative effect of Mg2+. We found that Zn2+ quenched the fluorescence of B. subtilis ferrochelatase and this quenching was used to estimate the metal affinity. Trp230 was identified as the intrinsic fluorophore responsible for the observed quenching pattern. The affinity for Zn2+ could be increased by incubating the ferrochelatase with the transition state analogue N-methyl mesoporphyrin IX, which reflected a close collaborative arrangement between the two substrates in the active site. We also showed that the affinity for Zn2+ was lowered in the presence of Mg2+ and that bound Zn2+ was released upon binding of Mg2+. In the ferrochelatase with a Glu272Ser modification, the interaction between Zn2+ and Mg2+ was abolished. It could thereby be demonstrated that the presence of a metal at one metal binding site affected the metal affinity of another, providing the enzyme with a site that regulates the enzymatic activity.

Potential for dramatic improvement in sequence alignment against structures of remote homologous proteins by extracting structural information from multiple structure alignment.

A novel method has been developed for acquiring the correct alignment of a query sequence against remotely homologous proteins by extracting structural information from profiles of multiple structure alignment. A systematic search algorithm combined with a group of score functions based on sequence information and structural information has been introduced in this procedure. A limited number of top solutions (15,000) with high scores were selected as candidates for further examination. On a test-set comprising 301 proteins from 75 protein families with sequence identity less than 30%, the proportion of proteins with completely correct alignment as first candidate was improved to 39.8% by our method, whereas the typical performance of existing sequence-based alignment methods was only between 16.1% and 22.7%. Furthermore, multiple candidates for possible alignment were provided in our approach, which dramatically increased the possibility of finding correct alignment, such that completely correct alignments were found amongst the top-ranked 1000 candidates in 88.3% of the proteins. With the assistance of a sequence database, completely correct alignment solutions were achieved amongst the top 1000 candidates in 94.3% of the proteins. From such a limited number of candidates, it would become possible to identify more correct alignment using a more time-consuming but more powerful method with more detailed structural information, such as side-chain packing and energy minimization, etc. The results indicate that the novel alignment strategy could be helpful for extending the application of highly reliable methods for fold identification and homology modeling to a huge number of homologous proteins of low sequence similarity. Details of the methods, together with the results and implications for future development are presented.