***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:  Rift Valley fever (RVF) outbreaks in Kenya have increased in frequency and range to include northeastern Kenya where viruses are increasingly being isolated from known (Aedes mcintoshi) and newly-associated (Ae. ochraceus) vectors. The factors contributing to these changing outbreak patterns are unclear and the population genetic structure of key vectors and/or specific virus-vector associations, in particular, are under-studied. By conducting mitochondrial and nuclear DNA analyses on >220 Kenyan specimens of Ae. mcintoshi and Ae. ochraceus, we uncovered high levels of vector complexity which may partly explain the disease outbreak pattern. Results indicate that Ae. mcintoshi consists of a species complex with one of the member species being unique to the newly-established RVF outbreak-prone northeastern region of Kenya, whereas Ae. ochraceus is a homogeneous population that appears to be undergoing expansion. Characterization of specimens from a RVF-prone site in Senegal, where Ae. ochraceus is a primary vector, revealed direct genetic links between the two Ae. ochraceus populations from both countries. Our data strongly suggest that unlike Ae. mcintoshi, Ae. ochraceus appears to be a relatively recent, single 'introduction' into Kenya. These results, together with increasing isolations from this vector, indicate that Ae. ochraceus will likely be of greater epidemiological importance in future RVF outbreaks in Kenya. Furthermore, the overall vector complexity calls into question the feasibility of mosquito population control approaches reliant on genetic modification.


Output:

Despite the threat posed by Rift Valley fever (RVF), poor understanding of the disease epidemiology exists with respect to vector population structure in relation to differential outbreak patterns and future vector genetic control. Here, nuclear and mtDNA data reveal genetic complexities of RVF key vectors (Aedes mcintoshi and Ae. ochraceus) partly explaining the disease outbreak pattern in Kenya. While anticipating population differentiation, we found that the hitherto known Ae. mcintoshi in fact comprises a species complex, with one unique species restricted to northeastern Kenya where outbreaks have increased in frequency with evidence for new involvement of Ae. ochraceus in RVF epidemiology. We infer a relatively recent, single “introduction” of Ae. ochraceus into Kenya with genetic links to a RVF hotspot in Senegal. Ultimately, our findings provide an understanding of how the two primary mosquito vector species impact RVF, which is critical to the potential prediction of the emergence and spread of the disease in Kenya.
