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Peptides

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Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...

AntiVPP 1.0: A portable tool for prediction of antiviral peptides.

Computers in biology and medicine
Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity a...

Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.

Journal of chemical theory and computation
Accurate force fields are crucial for molecular dynamics investigation of complex biological systems. Building accurate protein force fields from quantum mechanical (QM) calculations is challenging due to the complexity of proteins and high computati...

Predicting peptide presentation by major histocompatibility complex class I: an improved machine learning approach to the immunopeptidome.

BMC bioinformatics
BACKGROUND: To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data...

Peptide Extract from Exhibits Broad-Spectrum Antibacterial Activity.

BioMed research international
Increasing reports of infectious diseases worldwide have become a global concern in recent times. Depleted antibiotic pipelines, rapid and complex cases of antimicrobial resistance, and emergence and re-emergence of infectious disease have necessitat...

Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry.

Nature methods
We present DeepNovo-DIA, a de novo peptide-sequencing method for data-independent acquisition (DIA) mass spectrometry data. We use neural networks to capture precursor and fragment ions across m/z, retention-time, and intensity dimensions. They are t...

Photoelectrochemical biosensor for protein kinase A detection based on carbon microspheres, peptide functionalized Au-ZIF-8 and TiO/g-CN.

Talanta
In this work, a novel and sensitive photoelectrochemical (PEC) strategy was designed for protein kinase A (PKA) detection, comprising carbon microsphere (CMS) modified ITO electrode, TiO as the phosphate group recognition material and graphite-carbon...

Discovering de novo peptide substrates for enzymes using machine learning.

Nature communications
The discovery of peptide substrates for enzymes with exclusive, selective activities is a central goal in chemical biology. In this paper, we develop a hybrid computational and biochemical method to rapidly optimize peptides for specific, orthogonal ...

Isolation and identification of immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates.

Food chemistry
The RAW264.7 cell model was employed to screen immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates (SPHs). Moreover, the selenium-containing peptides of high-activity protein hydrolysates were purified by Se...

Improved Peptide Retention Time Prediction in Liquid Chromatography through Deep Learning.

Analytical chemistry
The accuracy of peptide retention time (RT) prediction model in liquid chromatography (LC) is still not sufficient for wider implementation in proteomics practice. Herein, we propose deep learning as an ideal tool to considerably improve this predict...