BackgroundGene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, most existing semantic similarity approaches rely only on GO annotations and structure, or incorporate only local interactions in the co-functional network. This may lead to inaccurate GO-based similarity resulting from the incomplete GO topology structure and gene annotations.ResultsWe present NETSIM2, a new network-based method that allows researchers to measure GO-based gene functional similarities by considering the global structure of the co-functional network with a random walk with restart (RWR)-based method, and by selecting the significant term pairs to decrease the noise information. Based on the EC number (Enzyme Commission)-based groups of yeast and Arabidopsis, evaluation test shows that NETSIM2 can enhance the accuracy of Gene Ontology-based gene functional similarity.ConclusionsUsing NETSIM2 as an example, we found that the accuracy of semantic similarities can be significantly improved after effectively incorporating the global gene-to-gene interactions in the co-functional network, especially on the species that gene annotations in GO are far from complete.
Tailoring of enzyme toward α‐tetralones, a class of bulky‐bulky ketones, is still a challenge. In this work, the mutants of carbonyl reductase BaSDR1 with improved catalytic performance toward α‐tetralone 1 a were obtained by adjusting the steric hindrance and hydrophobicity of the residues that affect the approach of α‐tetralone with the catalytic residues. The designed mutants also showed enhanced catalytic performance toward halogenated α‐tetralones 2 a–6 a. Remarkably, the activity of the mutant Q237V/I291F toward 7‐fluoro‐α‐tetralone 5 a was 16.3‐fold higher than the wildtype enzyme with improved stereoselectivity (98.8 % ee). More notably, the mutants Q139S and Q139S/V187S exhibited decreased or reversed stereoselectivity toward α‐tetralone 1 a, 5‐bromo‐α‐tetralone 2 a, 7‐fluoro‐α‐tetralone 5 a and 7‐chloro‐α‐tetralone 6 a, while the relatively high ee values were obtained in the presence of 6‐chloro‐α‐tetralone 3 a and 6‐bromo‐α‐tetralone 4 a as substrates. Further analysis showed the larger size of the substrates was beneficial for the substrates binding to the active cavity with a more specific binding mode, which endows the reaction with higher stereoselectivity. Moreover, the recombinant E. coli expressing the variant Q237V/I291F successfully catalyzed the reduction of a high concentration 7‐fluoro‐α‐tetralone 5 a. These results not only offered a potential tool for chiral α‐tetralols, but also provided guiding information for the enzyme engineering toward bulky‐bulky ketones.
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