AIMC Topic: Amino Acids

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FakeRotLib: Expedient Noncanonical Amino Acid Parametrization in Rosetta.

Journal of chemical information and modeling
Noncanonical amino acids (NCAAs) occupy an important place, both in natural biology and in synthetic applications. However, modeling these amino acids still lies outside the capabilities of most deep learning methods due to sparse training data sets ...

Machine learning-guided evolution of pyrrolysyl-tRNA synthetase for improved incorporation efficiency of diverse noncanonical amino acids.

Nature communications
The pyrrolysyl-tRNA synthetase (PylRS) is widely used to incorporate noncanonical amino acids (ncAAs) into proteins. However, the yields of most ncAA-containing protein  remain low due to the limited activity of PylRS variants. Here, we apply machine...

Immunodiagnostic plasma amino acid residue biomarkers detect cancer early and predict treatment response.

Nature communications
The immune response to tumour development is frequently targeted with therapeutics but remains largely unexplored in diagnostics, despite being stronger for early-stage tumours. We present an immunodiagnostic platform to detect this. We identify a pa...

Predicting the composition of multiple soybean varieties from whole and ground seeds using Fourier transform near-infrared spectroscopy (FT-NIRS) and machine learning.

Food chemistry
Soybean is being increasingly included in human diets, highlighting the importance of determining its composition. Although Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS) has become a promising technology, currently used models remain limited...

A novel UHPLC-HRMS method for simultaneous determination of 20 amino metabolites and proteins in lymphoma patients' cells and serum.

Scientific reports
Highly sensitive and selective monitoring of amino metabolites such as glutamine, arginine, tryptophan and related proteins played significant roles in early diagnosis and warning of lymphoma. But those limited abundance and lacked chromophore group ...

Microbiomics and machine learning-assisted approaches reveal amino acid patterns in high-temperature Daqu.

Food chemistry
Amino acids are crucial nitrogen sources in high-temperature Daqu (HTD), and they can significantly influence the quality of HTD. This study investigated amino acid patterns by analyzing fermentation parameters and microbial communities. Correlation ...

Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA-A0201.

PloS one
Class Ι major histocompatibility complexes (MHC-Ι), encoded by the highly polymorphic HLA-A, HLA-B, and HLA-C genes in humans, are expressed on all nucleated cells. Both self and foreign proteins are processed to peptides of 8-10 amino acids, loaded ...

New artificial neural network models for risk assessment of skin sensitization using amino acid derivative assay, KeratinoSens™, human cell line activation test and in silico structural alert parameter.

Regulatory toxicology and pharmacology : RTP
In the next-generation risk assessment (NGRA) of skin sensitization, estimating the point of departure (PoD) is crucial. The murine local lymph node assay (LLNA) has been considered the 'gold standard' for evaluating the skin sensitizing potential of...

Relationship between amino acid metabolism and inflammation in coronary heart disease (Review).

International journal of molecular medicine
This review delves into the intricate relationship between amino acid metabolism and inflammation in coronary heart disease (CHD). Research shows that disruptions in the metabolism of arginine, glutamate, branched‑chain amino acids (BCAAs) and trypto...

EMOCPD: Efficient Attention-Based Models for Computational Protein Design Using Amino Acid Microenvironment.

Journal of chemical information and modeling
Computational protein design (CPD) refers to the use of computational methods to design proteins. Traditional methods relying on energy functions and heuristic algorithms for sequence design are inefficient and do not meet the demands of the big data...