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Aminoacyl-tRNA synthetases are crucial enzymes involved in protein synthesis and various cellular physiological reactions. Aside from their standard role in linking amino acids to the corresponding tRNAs, they also impact protein homeostasis by controlling the level of soluble amino acids within the cell. For instance, leucyl-tRNA synthetase (LARS1) acts as a leucine sensor for the mammalian target of rapamycin complex 1 (mTORC1), and may also function as a probable GTPase-activating protein (GAP) for the RagD subunit of the heteromeric activator of mTORC1. In turn, mTORC1 regulates cellular processes, such as protein synthesis, autophagy, and cell growth, and is implicated in various human diseases including cancer, obesity, diabetes, and neurodegeneration. Hence, inhibitors of mTORC1 or a deregulated mTORC1 pathway may offer potential cancer therapies. In this study, we investigated the structural requirements for preventing the sensing and signal transmission from LARS to mTORC1. Building upon recent studies on mTORC1 regulation activation by leucine, we lay the foundation for the development of chemotherapeutic agents against mTORC1 that can overcome resistance to rapamycin. Using a combination of in-silico approaches to develop and validate an alternative interaction model, discussing its benefits and advancements. Finally, we identified a set of compounds ready for testing to prevent LARS1/RagD protein-protein interactions. We establish a basis for creating chemotherapeutic drugs targeting mTORC1, which can conquer resistance to rapamycin. We utilize in-silico methods to generate and confirm an alternative interaction model, outlining its advantages and improvements, and pinpoint a group of novel substances that can prevent LARS1/RagD interactions.Communicated by Ramaswamy H. Sarma.

Background: The most serious challenge in the treatment of tuberculosis is the multidrug resistance of Mycobacterium tuberculosis to existing antibiotics. As a strategy to overcome resistance we used a multitarget drug design approach. The purpose of the work was to discover dual-targeted inhibitors of mycobacterial LeuRS and MetRS with machine learning. Methods: The artificial neural networks were built using module nnet from R 3.6.1. The inhibitory activity of compounds toward LeuRS and MetRS was investigated in aminoacylation assays. Results: Using a machine-learning approach, we identified dual-targeted inhibitors of LeuRS and MetRS among 2-(quinolin-2-ylsulfanyl)-acetamide derivatives. The most active compound inhibits MetRS and LeuRS with IC 50 values of 33 μm and 23.9 μm, respectively. Conclusion: 2-(Quinolin-2-ylsulfanyl)-acetamide scaffold can be useful for further research.

The increase of antibiotic resistance amongst Mycobacterium tuberculosis strains has become one of the most pressing problems of modern medicine. Therefore, the search of antibiotics against M. tuberculosis with novel mechanisms of action is very important. We have identified inhibitors of M. tuberculosis leucyl-tRNA synthetase (LeuRS) among the derivatives of 5-phenylamino-2H-[1,2,4]triazin-3-one. The most active compounds 5-(5-chloro-2-hydroxy-phenylamino)-6-methyl-2H-[1,2,4]triazin-3-one and 5-(5-chloro-2-hydroxy-phenylamino)-2H-[1,2,4]triazin-3-one inhibit M. tuberculosis LeuRS with IC 50 of 7.6 μМ and 7.2 μМ, respectively. It was established that the inhibitory activity of compounds against pathogenic LeuRS is 10-fold better, than for human enzyme.