Solution structure of the antiapoptotic protein bcl-2

The structures of two isoforms of Bcl-2 that differ by two amino acids have been determined by NMR spectroscopy. Because wild-type Bcl-2 behaved poorly in solution, the structures were determined by using Bcl-2/Bcl-xL chimeras in which part of the putative unstructured loop of Bcl-2 was replaced with a shortened loop from Bcl-xL. These chimeric proteins have a low pI compared with the wild-type protein and are soluble. The structures of the two Bcl-2 isoforms consist of 6 α-helices with a hydrophobic groove on the surface similar to that observed for the homologous protein, Bcl-xL. Comparison of the Bcl-2 structures to that of Bcl-xL shows that although the overall fold is the same, there are differences in the structural topology and electrostatic potential of the binding groove. Although the structures of the two isoforms of Bcl-2 are virtually identical, differences were observed in the ability of the proteins to bind to a 25-residue peptide from the proapoptotic Bad protein and a 16-residue peptide from the proapoptotic Bak protein. These results suggest that there are subtle differences in the hydrophobic binding groove in Bcl-2 that may translate into differences in antiapoptotic activity for the two isoforms.

The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small

In the maximum parsimony (MP) and minimum evolution (ME) methods of phylogenetic inference, evolutionary trees are constructed by searching for the topology that shows the minimum number of mutational changes required (M) and the smallest sum of branch lengths (S), respectively, whereas in the maximum likelihood (ML) method the topology showing the highest maximum likelihood (A) of observing a given data set is chosen. However, the theoretical basis of the optimization principle remains unclear. We therefore examined the relationships of M, S, and A for the MP, ME, and ML trees with those for the true tree by using computer simulation. The results show that M and S are generally greater for the true tree than for the MP and ME trees when the number of nucleotides examined (n) is relatively small, whereas A is generally lower for the true tree than for the ML tree. This finding indicates that the optimization principle tends to give incorrect topologies when n is small. To deal with this disturbing property of the optimization principle, we suggest that more attention should be given to testing the statistical reliability of an estimated tree rather than to finding the optimal tree with excessive efforts. When a reliability test is conducted, simplified MP, ME, and ML algorithms such as the neighbor-joining method generally give conclusions about phylogenetic inference very similar to those obtained by the more extensive tree search algorithms.