***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:  Spinal muscular atrophy is a severe neurogenic disease that is caused by mutations in the human survival motor neuron 1 (SMN1) gene. SMN protein is required for the assembly of small nuclear ribonucleoproteins and a dramatic reduction of the protein leads to cell death. It is currently unknown how the reduction of this ubiquitously essential protein can lead to tissue-specific abnormalities. In addition, it is still not known whether the disease is caused by developmental or degenerative defects. Using the Drosophila system, we show that SMN is enriched in postembryonic neuroblasts and forms a concentration gradient in the differentiating progeny. In addition to the developing Drosophila larval CNS, Drosophila larval and adult testes have a striking SMN gradient. When SMN is reduced in postembryonic neuroblasts using MARCM clonal analysis, cell proliferation and clone formation defects occur. These SMN mutant neuroblasts fail to correctly localise Miranda and have reduced levels of snRNAs. When SMN is removed, germline stem cells are lost more frequently. We also show that changes in SMN levels can disrupt the correct timing of cell differentiation. We conclude that highly regulated SMN levels are essential to drive timely cell proliferation and cell differentiation.


Output:

Spinal muscular atrophy is a debilitating disease that affects the motor nervous system. The disease is caused by the reduction of the protein survival motor neuron (SMN), which is involved in the assembly of ubiquitous small nuclear ribonucleoproteins. As SMN is required in every cell, it is important to understand the differential functionality of the protein within developing tissues. In this paper, we identify stem cells as having the highest levels of SMN. The concentration of SMN then decreases in a declining gradient until it reaches its lowest level in differentiated cells. SMN reduction, using clonal analysis, slows stem cell division and can lead to stem cell loss. These defects correlate with a reduction in the U2 and U5 small nuclear RNAs and with the mislocalisation of Miranda protein in postembryonic neuroblasts. In addition, we show that the overexpression of SMN can change the timing of development and cell differentiation. This research highlights possible mechanisms explaining how SMN expression alterations may affect tissue development.
