***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:  Phosphorus (P) is essential for all living cells and organisms, and low-P stress is a major factor constraining plant growth and yield worldwide. In plants, P efficiency is a complex quantitative trait involving multiple genes, and the mechanisms underlying P efficiency are largely unknown. Combining linkage analysis, genome-wide and candidate-gene association analyses, and plant transformation, we identified a soybean gene related to P efficiency, determined its favorable haplotypes and developed valuable functional markers. First, six major genomic regions associated with P efficiency were detected by performing genome-wide associations (GWAs) in various environments. A highly significant region located on chromosome 8, qPE8, was identified by both GWAs and linkage mapping and explained 41% of the phenotypic variation. Then, a regional mapping study was performed with 40 surrounding markers in 192 diverse soybean accessions. A strongly associated haplotype (P = 10−7) consisting of the markers Sat_233 and BARC-039899-07603 was identified, and qPE8 was located in a region of approximately 250 kb, which contained a candidate gene GmACP1 that encoded an acid phosphatase. GmACP1 overexpression in soybean hairy roots increased P efficiency by 11–20% relative to the control. A candidate-gene association analysis indicated that six natural GmACP1 polymorphisms explained 33% of the phenotypic variation. The favorable alleles and haplotypes of GmACP1 associated with increased transcript expression correlated with higher enzyme activity. The discovery of the optimal haplotype of GmACP1 will now enable the accurate selection of soybeans with higher P efficiencies and improve our understanding of the molecular mechanisms underlying P efficiency in plants.


Output:

In soybean plants, low-phosphorus (P) stress is more detrimental than other nutrient deficiencies, toxicities or diseases; however, it is difficult to select soybean varieties with high P efficiencies based on phenotypes. Although QTL map-based cloning is a powerful method, it is time-consuming, and the QTLs underlying P efficiency in soybeans have not been identified. Combining linkage and association analyses, we identified a highly significant region on chromosome 8, qPE8, which is associated with soybean P efficiency. Gene expression and plant transformation experiments indicated that the gene GmACP1 within qPE8 affects P efficiency. A haplotype survey of GmACP1 identified 10 haplotypes that explained 33% of the variation in P efficiency. The discovery of the optimal haplotype of GmACP1 will improve the accuracy of selecting soybeans with higher P efficiencies and increase our understanding of the molecular mechanisms underlying P efficiency in plants.
