At the very beginning of our project, we went to meet our school’s wet team - USTC, to learn something about synthetic biology. During our visit, we found that screening for the enzyme by experiment is very time-consuming and often clueless in the beginning, when there is no readily suitable enzyme in the database to catalyze the target reaction. Being familiar with information technology, we are curious about the possibility of collaboration between computer science and biology, which means applying certain algorithm to predict enzymes.
We asked our wet team if there was any prediction platforms to solve this problem and was replied that existing software has some flaws, for example, it often produced results that are not the type of reaction they wanted. So we thought we should do some contributions in this area. With this belief, we design the software MEI ,contributed much to the iGEM community. Here are several of our contributions.
Due to the troublesome issue just mentioned, we planned to designed an enzyme prediction platform, and surely we made it. The platform receives the reactant and substrate structure, and the specified group, while selecting the required coenzyme and reaction type. Applying our algorithm, our platform can give the prediction of enzymes that users demand.
Users can find the enzyme that best meets their requirement by our well-designed platform. Through the similarity comparison algorithm of chemical structure, combined with the related equation of enzyme kinetics, our software can greatly lessen the users' searching pressure.
By using our software, in a very short time, users can obtain a series of candidates for potential enzyme that is most likely to catalyze the target reaction, with scores to describe the likelihood of the relevant catalysis. On this basis, they can do further modification and directional transformation. We are sure synthetic biologists can greatly benefit from our enzyme prediction and screening platform.
Compared with existing metabolic pathway software, MEI has a great visual input interface. Users don’t need to study different forms of chemical labeling ,and the only thing he needs to do is to assemble chemical formulas on our input interface, which is simple and vivid. Our input interface is set up with simple buttons and integrates some of the chemical groups most frequently used by users. At the same time, our software design cache interval, so that users can customize his chemical structure and save it in our platform.
Current software that predicts metabolic pathways only by structural comparison often yields results that are not the type of reaction that synthetic biologists are looking for. Therefore, our software screens enzymes on the basis of prioritizing reaction types, and then compares the reactions catalyzed by these enzymes with the reaction given by users. So that the output we’ve given is consistent with the type of reaction the user wants.
In practical industrial production, enzyme activity is an important factor when screening enzymes. With an enzyme of low activity, not only the product conversion rate is not high, it is also difficult to separate and purify the products after the reaction, which often leads to a lot of waste and high cost. Thus, we take the activity of the enzyme into consideration through the Michaelis-Menten equation when we screen enzymes, and use it as one of the scoring criteria for the enzyme.
Cofactors play an important role of transferring electrons, hydrogen and certain chemical groups in enzymatic reactions. But in actual industrial production, cofactor cost a lot, so coenzyme is usually added to transform and regenerate cofactor, so as to maintain the stability of enzymatic reaction system. Therefore, we add the option of cofactor in the platform, and users can choose the cofactor to be added by themselves.
To promote public awareness of synthetic biology and introduce its basic ideas to the laymen, our team is devoted to the development of a brochure, which aims at providing for non-biologists with a comprehensive overview of synthetic biology, from its development history, research content and practical applications. Compared with the boring explanations in other books, the whole set of brochures is lively and light-hearted, with easy-to-understand explanation, avoiding complicated and advanced terms as much as possible; and we also used cartoon images to visualize the theory, which makes the descriptions more graphic and more acceptable.
