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Motivation The emergence of drug-resistant pathogens represents a formidable challenge to global health. Using computational methods to identify the antibacterial peptides (ABPs), an alternative antimicrobial agent, has demonstrated advantages in further drug design studies. Most of the current approaches, however, rely on handcrafted features and underutilize structural information, which may affect prediction performance. Results To present an ultra-accurate model for ABP identification, we propose a novel deep learning approach, PGAT-ABPp. PGAT-ABPp leverages structures predicted by AlphaFold2 and a pretrained protein language model, ProtT5-XL-U50 (ProtT5), to construct graphs. Then the graph attention network (GAT) is adopted to learn global discriminative features from the graphs. PGAT-ABPp outperforms the other fourteen state-of-the-art models in terms of accuracy, F1-score and Matthews Correlation Coefficient on the independent test dataset. The results show that ProtT5 has significant advantages in the identification of ABPs and the introduction of spatial information further improves the prediction performance of the model. The interpretability analysis of key residues in known active ABPs further underscores the superiority of PGAT-ABPp. Availability and implementation The datasets and source codes for the PGAT-ABPp model are available at https://github.com/moonseter/PGAT-ABPp/. [ABSTRACT FROM AUTHOR]

The cell nucleus is the main site for the storage and replication of genetic material, and the synthesis of substances in the nucleus is rhythmic, regular and strictly regulated by physiological processes. However, whether exogenous substances, such as nanoparticles, can be synthesized in situ in the nucleus of live cells has not been reported. Here, we have achieved in-situ synthesis of CdS x Se1−x quantum dots (QDs) in the nucleus by regulation of the glutathione (GSH) metabolic pathway. High enrichment of GSH in the nucleus can be accomplished by the addition of GSH with the help of the Bcl-2 protein. Then, high-valence Se is reduced to low-valence Se by glutathione-reductase-catalyzed GSH, and interacts with the Cd precursor formed through Cd and thiol-rich proteins, eventually generating QDs in the nucleus. Our work contributes to a new understanding of the syntheses of substances in the cell nucleus and will pave the way for the development of advanced 'supercells'. [ABSTRACT FROM AUTHOR]