As we all know, enzymes play an important role in the biological production of synthetic biology.
And compared with general catalysts, enzymes outstand for high efficiency and specificity.
By introducing various enzymes into reaction systems and biological devices, we can produce many valuable products under mild external conditions or in living organisms.

Usually, a complete biosynthesis or degradation pathway contains multiple nodes and multi-step reactions.
In the process of study, researchers often find that there is no suitable enzyme that can be directly found in the database to catalyze the target reaction, or the catalytic efficiency of enzymes found is not high, which brings difficulties to the study of metabolic pathways.

At present, there are some software for calculating anabolic pathways. However, pathway interruption often occurs when searching pathways containing unknown reactions.
In other software, only the structure of the compound structure is considered when predicting unknown reactions, which often leads to too many results and the difficulty in experimental verification so that the practical feasibility in experiment or industrial production is low.

Thus, our team developed MEI, Modified Enzyme Interface, to provide users with efficient enzymes candidates that may catalyze the target reaction.
Our project is based on a similarity comparison algorithm. Through structural comparison of chemical reactions, we screen out potential enzymes from the database and output them in a user-friendly way.

Under the initial assumption of single-step reaction, we gradually added more factors to be considered, such as the participation of coenzyme, the species of enzymes, the control of feed ratio by considering the reaction rate through biodynamic knowledge.
By MEI, we hope to help users shorten the experimental time and find the desired enzyme more quickly.