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Motivation: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning., Results: Here, we propose to identify ligands using a deep learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can be used to train models that can be applied to cryoEM structures, but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands., Competing Interests: Conflict of Interest: none declared.

Chemotherapy is the commonly used treatment for advanced lung cancer. However, it produces side effects such as the development of chemoresistance. A possible responsible mechanism may be therapy-induced senescence (TIS). TIS cells display increased senescence-associated β-galactosidase (SA-β-gal) activity and irreversible growth arrest. However, recent data suggest that TIS cells can reactivate their proliferative potential and lead to cancer recurrence. Our previous study indicated that reactivation of proliferation by TIS cells might be related with autophagy modulation. However, exact relationship between both processes required further studies. Therefore, the aim of our study was to investigate the role of autophagy in the senescence-related chemoresistance of lung cancer cells. For this purpose, human and murine lung cancer cells were treated with two commonly used chemotherapeutics: cisplatin (CIS), which forms DNA adducts or docetaxel (DOC), a microtubule poison. Hypoxia, often overlooked in experimental settings, has been implicated as a mechanism responsible for a significant change in the response to treatment. Thus, cells were cultured under normoxic (~19% O 2 ) or hypoxic (1% O 2 ) conditions. Herein, we show that hypoxia increases resistance to CIS. Lung cancer cells cultured under hypoxic conditions escaped from CIS-induced senescence, displayed reduced SA-β-gal activity and a decreased percentage of cells in the G2/M phase of the cell cycle. In turn, hypoxia increased the proliferation of lung cancer cells and the proportion of cells proceeding to the G0/G1 phase. Further molecular analyses demonstrated that hypoxia inhibited the prosenescent p53/p21 signaling pathway and induced epithelial to mesenchymal transition in CIS-treated cancer cells. In cells treated with DOC, such effects were not observed. Of importance, pharmacological autophagy inhibitor, hydroxychloroquine (HCQ) was capable of overcoming short-term CIS-induced resistance of lung cancer cells in hypoxic conditions. Altogether, our data demonstrated that hypoxia favors cancer cell escape from CIS-induced senescence, what could be overcome by inhibition of autophagy with HCQ. Therefore, we propose that HCQ might be used to interfere with the ability of senescent cancer cells to repopulate following exposure to DNA-damaging agents. This effect, however, needs to be tested in a long-term perspective for preclinical and clinical applications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Olszewska, Borkowska, Granica, Karolczak, Zglinicki, Kieda and Was.)