***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
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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:  The biophysical nature of the interaction between a transcription factor and its target sequences in vitro is sufficiently well understood to allow for the effects of DNA sequence alterations on affinity to be predicted. But even in relatively simple in vivo systems, the complexities of promoter organization and activity have made it difficult to predict how altering specific interactions between a transcription factor and DNA will affect promoter output. To better understand this, we measured the relative fitness of nearly all Escherichia coli   binding sites in different promoter and environmental contexts by competing four randomized  promoter libraries controlling the expression of the tetracycline resistance gene (tet) against each other in increasing concentrations of drug. We sequenced populations after competition to determine the relative enrichment of each −35 sequence. We observed a consistent relationship between the frequency of recovery of each −35 binding site and its predicted affinity for  that varied depending on the sequence context of the promoter and drug concentration. Overall the relative fitness of each promoter could be predicted by a simple thermodynamic model of transcriptional regulation, in which the rate of transcriptional initiation (and hence fitness) is dependent upon the overall stability of the initiation complex, which in turn is dependent upon the energetic contributions of all sites within the complex. As implied by this model, a decrease in the free energy of association at one site could be compensated for by an increase in the binding energy at another to produce a similar output. Furthermore, these data show that a large and continuous range of transcriptional outputs can be accessed by merely changing the , suggesting that evolved or engineered mutations at this site could allow for subtle and precise control over gene expression.


Output:

A major challenge in molecular genetics has been to understand how cis-regulatory information is integrated to determine the amount of transcript generated. The difficulty has been that there are a large number of variables (known and unknown) that combine through an extensive array of possible mechanisms. Differences in the affinity of a binding site for its cognate binder within the initiation complex are known to account for significant differences in promoter output, but data for the activity of binding site variants in vivo has been limited. Here, we were able to map the fitness of nearly all E. coli   binding sites in multiple promoter and environmental contexts using a novel method that utilizes the sequencing power of a next generation DNA sequencer. These data for the first time show the phenotypic range and continuity of a nearly complete set of possible binding targets in vivo, and they are useful in our ability to understand the mechanism, evolution, and designability of gene regulation.
