TALEs of virulence and biotechnology
نویسندگان
چکیده
The amount of solved protein structures is continuously growing. Pharmaceutical research recently recognized the potential of computationally extracting information from this large data pool and using them for homology-based knowledge transfer to new structures. This article focuses on computational approaches for structure-based target assessment. Highlighted are novel approaches for target classification, i.e., druggability or function prediction, and target comparison together with the underlying methods for active site detection and description. Protein function predictions, e.g., yielded accuracies between 54% and 81% for predicting the correct main class, subclass and substrate-specific subsubclass on a test set of 26632 pockets. Besides the presentation of successful retrospective application studies of these methods, challenging tasks in the individual computational steps are discussed in this article.
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