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Unraveling the activation mechanism of taspase1 which controls the oncogenic AF4–MLL fusion protein
(2015)
We have recently demonstrated that Taspase1-mediated cleavage of the AF4–MLL oncoprotein results in the formation of a stable multiprotein complex which forms the key event for the onset of acute proB leukemia in mice. Therefore, Taspase1 represents a conditional oncoprotein in the context of t(4;11) leukemia. In this report, we used site-directed mutagenesis to unravel the molecular events by which Taspase1 becomes sequentially activated. Monomeric pro-enzymes form dimers which are autocatalytically processed into the enzymatically active form of Taspase1 (αββα). The active enzyme cleaves only very few target proteins, e.g., MLL, MLL4 and TFIIA at their corresponding consensus cleavage sites (CSTasp1) as well as AF4–MLL in the case of leukemogenic translocation. This knowledge was translated into the design of a dominant-negative mutant of Taspase1 (dnTASP1). As expected, simultaneous expression of the leukemogenic AF4–MLL and dnTASP1 causes the disappearance of the leukemogenic oncoprotein, because the uncleaved AF4–MLL protein (328 kDa) is subject to proteasomal degradation, while the cleaved AF4–MLL forms a stable oncogenic multi-protein complex with a very long half-life. Moreover, coexpression of dnTASP1 with a BFP-CSTasp1-GFP FRET biosensor effectively inhibits cleavage. The impact of our findings on future drug development and potential treatment options for t(4;11) leukemia will be discussed.
The repertoire of natural products offers tremendous opportunities for chemical biology and drug discovery. Natural product-inspired synthetic molecules represent an ecologically and economically sustainable alternative to the direct utilization of natural products. De novo design with machine intelligence bridges the gap between the worlds of bioactive natural products and synthetic molecules. On employing the compound Marinopyrrole A from marine Streptomyces as a design template, the algorithm constructs innovative small molecules that can be synthesized in three steps, following the computationally suggested synthesis route. Computational activity prediction reveals cyclooxygenase (COX) as a putative target of both Marinopyrrole A and the de novo designs. The molecular designs are experimentally confirmed as selective COX-1 inhibitors with nanomolar potency. X-ray structure analysis reveals the binding of the most selective compound to COX-1. This molecular design approach provides a blueprint for natural product-inspired hit and lead identification for drug discovery with machine intelligence.
Chemical language models enable de novo drug design without the requirement for explicit molecular construction rules. While such models have been applied to generate novel compounds with desired bioactivity, the actual prioritization and selection of the most promising computational designs remains challenging. Herein, we leveraged the probabilities learnt by chemical language models with the beam search algorithm as a model-intrinsic technique for automated molecule design and scoring. Prospective application of this method yielded novel inverse agonists of retinoic acid receptor-related orphan receptors (RORs). Each design was synthesizable in three reaction steps and presented low-micromolar to nanomolar potency towards RORγ. This model-intrinsic sampling technique eliminates the strict need for external compound scoring functions, thereby further extending the applicability of generative artificial intelligence to data-driven drug discovery.