All eukaryotes possess several E s

All eukaryotes possess several E2s ranging from about 8 to 11 in certain apicomplexans and Giardia to a little over 50 in certain multicellular plants and animals (Supplementary material). Most of them, barring those in the autophagy pathway (Apg3 and Apg10), are relatively close to each other in sequence. The entire Cinchonidine of eukaryotic E2s has not been systematically explored through the application of evolutionary principles to identify key functional residues. The extreme divergence of Apg3 and Apg10 families also did not allow for a direct comparison with the classical E2s (Ichimura et al., 2000, Yamada et al., 2007). More recently, we discovered the first prokaryotic homologs of the E2 enzymes proposed to function analogous to their eukaryotic counterparts in predicted Ub-conjugation like systems in bacteria (Iyer et al., 2006). A comparison of their conservation profiles with the eukaryotic E2s revealed that while the E2 catalytic cysteine is strictly conserved, they include representatives which are highly divergent in sequence. Importantly, comparisons of the prokaryotic and eukaryotic sequences suggested that the residues besides the catalytic cysteine proposed to be involved in E2 function might not be generally conserved. Concomitantly, several new crystal structures of E2 enzymes have been solved, including that of Apg3, which was also shown to lack the other residues involved in E2 function, despite conserving the catalytic cysteine (Arai et al., 2006, Mizushima et al., 2007, Yamada et al., 2007). Structures of catalytically inactive versions of the E2 fold such as UEV1, Tsg101 (UEV) and the RWD domain have also been solved, providing structural information regarding the non-enzymatic adaptations of the fold (Eddins et al., 2006, Hau et al., 2006, Nameki et al., 2004).
Results and discussion
General conclusions
Material and methods The non-redundant (NR) database of protein sequences (National Center for Biotechnology Information, NIH, Bethesda, MD) was searched with the BLASTP program (Altschul et al., 1997). Profile searches were conducted using the PSI-BLAST program (Altschul et al., 1997) with either single sequences or multiple alignments as queries, with a profile inclusion expectation (e) value threshold of 0.01; searched were iterated until convergence. Hidden Markov models (HMMs) built from alignments using the hmmbuild program were also employed in searches carried out using the hmmsearch program from the HMMER package (Eddy, 1998). For queries and searches containing compositionally biased segments, the statistical correction option built into the BLAST program was used (Schaffer et al., 2001). Multiple alignments were constructed using the MUSCLE (Edgar, 2004) and/or KALIGN programs (Lassmann and Sonnhammer, 2005), followed by manual adjustment based on PSI-BLAST hsps and information provided by solved three-dimensional structures. Protein structures were visualized using the Swiss-PDB viewer (Guex and Peitsch, 1997) and cartoons were constructed with the PyMOL program (http://www.pymol.org). Protein secondary structure predictions were made with the JPRED program, which computes a consensus predicted structure using the information from the conservation profile, a PSI-BLAST position-specific score matrix and a hidden Markov model (Cuff and Barton, 2000).