***TASK***
the task is to simplify the input abstract of a biomedical literature

***INPUT***
the input is the abstract of a biomedical literature

***OUTPUT***
the output is the simplified abstract for the input abstract of a biomedical literature
***DOCUMENTATION*** 
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Input: Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.
Output:  When species evolve, their genes duplicate and diverge to allow for adaptation of their functional repertoires to the changing environment. In this scenario, unrelated genes can convergently evolve to produce proteins with the same molecular function, termed “functionally analogous.” A quantitative determination of the reaction similarities among functionally analogous enzymes could provide insight about the different structural solutions nature has used to evolve similar catalysts. Bond changes between substrates and products, and between successive reaction intermediates, were used to compare the reactions catalyzed and the mechanisms of catalysis for 95 pairs of functionally analogous enzymes. Less than half of the reactions catalyzed by unrelated enzymes, but defined as similar by the Enzyme Commission (EC) classification, are similar in terms of bond changes, suggesting that this classification often fails to capture quantitative differences between many enzyme reactions. Furthermore, we addressed for the first time whether the chemical mechanisms by which similar overall reactions are achieved in functional analogs are also similar. We conclude that convergence of reaction is often accompanied by convergence of chemical mechanism. These results will be useful for classifying enzymes, guiding functional annotation of newly determined enzyme sequences and structures and for informing the engineering of enzymes with new functions.

Input:  Yeast RNA polymerase II (Pol II) terminates transcription of coding transcripts through the polyadenylation (pA) pathway and non-coding transcripts through the non-polyadenylation (non-pA) pathway. We have used PAR-CLIP to map the position of Pol II genome-wide in living yeast cells after depletion of components of either the pA or non-pA termination complexes. We show here that Ysh1, responsible for cleavage at the pA site, is required for efficient removal of Pol II from the template. Depletion of Ysh1 from the nucleus does not, however, lead to readthrough transcription. In contrast, depletion of the termination factor Nrd1 leads to widespread runaway elongation of non-pA transcripts. Depletion of Sen1 also leads to readthrough at non-pA terminators, but in contrast to Nrd1, this readthrough is less processive, or more susceptible to pausing. The data presented here provide delineation of in vivo Pol II termination regions and highlight differences in the sequences that signal termination of different classes of non-pA transcripts.


Output:

Transcription termination is an important regulatory event for both non-coding and coding transcripts. Using high-throughput sequencing, we have mapped RNA Polymerase II's position in the genome after depletion of termination factors from the nucleus. We found that depletion of Ysh1 and Sen1 cause build up of polymerase directly downstream of coding and non-coding genes, respectively. Depletion of Nrd1 causes an increase in polymerase that is distributed up to 1,000 bases downstream of non-coding genes. The depletion of Nrd1 helped us to identify more than 250 unique termination regions for non-coding RNAs. Within this set of newly identified non-coding termination regions, we are further able to classify them based on sequence motif similarities, suggesting a functional role for different terminator motifs. The role of these factors in transcriptional termination of coding and/or non-coding transcripts can be inferred from the effect of polymerase's position downstream of given termination sites. This method of depletion and sequencing can be used to further elucidate other factors whose importance to transcription has yet to be determined.
