The design of biosynthetic systems involves a large search space, therefore it is essential to have a computational tool to predict productive pathways to aid in that design. There are a number of pre-existing approaches including flux-based analysis based (host often limited to e.coli), reaction count-based, and thermodynamic favorability based (but the effects of competing reactions cannot be captured, and ranking doesn’t depend on the host’s metabolic system). They wanted to be able, given a starting material, a target product, and a host organism, to find promising biosynthetic routes by allowing the introduction of foreign metabolic enzymes into the host.
They have a host-dependent weighting scheme in which the ranking of pathways based on this can be widely different from the thermodynamic favorability approach. They first compute the weight for each edge in the function, such that they can have different weights even if the energy value is identical. In this way, you can include in the model additional further steps that may lower otherwise high-scoring reactions if their routes lead to undesirable consequences.
They have also developed SBOLme.
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