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Peptides

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Energy-dependent protein folding: modeling how a protein folding machine may work.

F1000Research
Proteins fold robustly and reproducibly , but many cannot fold in isolation from cellular components. Despite the remarkable progress that has been achieved by the artificial intelligence approaches in predicting the protein native conformations, t...

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BMC bioinformatics
BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor r...

AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides.

Scientific reports
Dietary antioxidants are an important preservative in food and have been suggested to help in disease prevention. With consumer demands for less synthetic and safer additives in food products, the food industry is searching for antioxidants that can ...

ENNAACT is a novel tool which employs neural networks for anticancer activity classification for therapeutic peptides.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
The prevalence of cancer as a threat to human life, responsible for 9.6 million deaths worldwide in 2018, motivates the search for new anticancer agents. While many options are currently available for treatment, these are often expensive and impact t...

Noninvasive diagnostic of periprosthetic joint infection by urinary peptide markers: A preliminary study.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Previous immunohistochemical analyses revealed altered protein expression in the periprosthetic membranes of patients with periprosthetic joint infection (PJI). Proteins are degraded to peptides that may pass the blood-kidney barrier depending on the...

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

Scientific reports
The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cell...

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance.

Scientific reports
The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery of new antiviral therapies is imperative to address this challenge, and antiviral peptides (AVPs) rep...

A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...

Predictive Modeling of Angiotensin I-Converting Enzyme Inhibitory Peptides Using Various Machine Learning Approaches.

Journal of agricultural and food chemistry
Food-derived angiotensin I-converting enzyme (ACE) inhibitory peptides could potentially be used as safe supportive therapeutic products for high blood pressure. Theoretical approaches are promising methods with the advantage through exploring the re...

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.

Proteomics
The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (MS)-based immunopeptideomics relies largely on database search engines developed for proteomics data analysis. However, because immunopeptidomics expe...