AIMC Topic: Amino Acids

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Establishment of an amino acid metabolism related signature for prognostic and therapeutic sensitivity prediction in breast cancer by machine learning.

PloS one
Amino acid metabolism plays a critical role in tumor growth and immune regulation, yet its comprehensive function in breast cancer remains underexplored. We developed an amino acid metabolism-related gene signature (AAMRGS) to predict prognosis and t...

Nanopore Fingerprinting of Structurally Diverse Amino Acid-Conjugated Bile Acids.

Nano letters
Bile acids are key signaling molecules implicated in various hepatobiliary and metabolic diseases. Synthesized via distinct pathways and undergoing diverse modifications, bile acids exhibit significant structural variation. The discovery of novel ami...

Programmable motion of an enzyme-powered macroscale gel boat: a functional sensing platform.

Materials horizons
An augmented strategy for constructing intelligent soft robots includes the transfer of biogenic features from nature to man-made artificial systems serving a range of life-like functions. Inspired by living technology, we have customized macroscale ...

Conditional deep learning model reveals translation elongation determinants during amino acid deprivation.

Communications biology
Translation elongation plays a key role in cellular homeostasis, and dysregulation of this process has been implicated in various diseases and metabolic disorders. Uncovering the causes of intragenic heterogeneity of translation, especially in contex...

Investigation on the isotopic exchange radiofluorination of the pentafluorosulfanyl group.

Organic & biomolecular chemistry
The pentafluorosulfanyl group (-SF) is one of the most promising fluorinated functional groups, recently developed as an alternative to the trifluoromethyl group (-CF) in drug design. Fluorine-18 allows researchers to investigate activity and biodis...

Prediction of peptide cleavage sites using protein language models and graph neural networks.

Scientific reports
The growing interest in using peptide molecules as therapeutic agents, driven by their high selectivity and efficacy, has become a significant trend in the pharmaceutical industry. However, their oral administration remains challenging due to their l...

Deep-Learning-Guided Mining and Clustering of Remote Amino Acid Residues for the Simultaneous Engineering of the Catalytic Activity and Thermostability of a Processive Endoglucanase.

ACS synthetic biology
Processive endoglucanases, which possess both endo- and exoglucanase activities, are considered highly promising catalysts in cellulose degradation. In this study, we employed multiple deep learning models, including MutCompute, DeepSequence, and ESM...

Prediction of reduction behavior by heating and strain variability of Campylobacter jejuni using amino acid phylogenetics from whole genome sequencing data.

International journal of food microbiology
Predicting bacterial behavior and strain variability is essential for quantitative microbial risk assessments in food safety. The growing availability of whole-genome sequencing (WGS) data enables deeper insights into microbial thermotolerance. Howev...

Regression model and artificial neural network model to predict halonitromethane formation from amino acids during UV/monochloramine disinfection in bromide-containing real water.

Environmental pollution (Barking, Essex : 1987)
Halonitromethanes (HNMs) were high-toxicity nitrogenous disinfection byproducts generated by amino acids (AAs) during UV/monochloramine (UV/NHCl) disinfection in bromide-containing water. HNM concentrations fell over time, highlighting disinfection t...

Nanopore sequencing of intact aminoacylated tRNAs.

Nature communications
The intricate landscape of tRNA modification presents persistent analytical challenges, which have impeded efforts to simultaneously resolve sequence, modification, and aminoacylation state at the level of individual tRNAs. To address these challenge...