Research GroupsKalesse Group
Research - Statistical structure prediction

Research - Statistical structure prediction

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Our structure prediction works for Type I Polyketides. Through analyzing keto-reduktases one can predict the configuration at secondary alcohols as well as at adjacent methyl branches.

The required Hidden-Markov-Modell together with the required data set is available at https://akitsche.shinyapps.io/profileHMM_App/. It is easy to use: Just copy pate your keto-reductase sequence and run the program. The output generates the Fischer nomenclature descriptors D/L as well as the absolute figure as an indication of the confidence of the prediction.

Ideally, the input of the sequence starts with positions TGGT or a corresponding sequence and ends with AWG or correspondingly.

As an example, the input for a salinomycine keto-reductase is given below.