AIMC Topic: Peptides

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Deep Learning Protocol for Predicting Full-Spectrum Infrared and Raman Spectra of Polypeptides and Proteins Using All-Atom Models.

The journal of physical chemistry letters Feb 18, 2025
Infrared (IR) spectroscopy and Raman spectroscopy are powerful tools for probing protein and peptide structures due to their capability to provide molecular fingerprints. As a popular spectral simulation method, the quantum chemistry (QC) calculation...
Spectrophotometry, Infrared Deep Learning Spectrum Analysis, Raman Proteins Models, Molecular Quantum Theory Peptides
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Dynamic Electronic Structure Fluctuations in the De Novo Peptide ACC-Dimer Revealed by First-Principles Theory and Machine Learning.

Journal of chemical information and modeling Feb 14, 2025
Recent studies have reported long-range charge transport in peptide- and protein-based fibers and wires, rendering this class of materials as promising charge-conducting interfaces between biological systems and electronic devices. In the complex mol...
Peptides Density Functional Theory Molecular Dynamics Simulation Machine Learning Electrons Protein Conformation Protein Multimerization
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Intelligent decoding platform for peptide sequences: SERS detection via high affinity self-assembled silver nanoparticles and machine learning analysis.

Analytica chimica acta Feb 13, 2025
BACKGROUND: Peptides are compounds formed by the dehydration-condensation reaction of two or more amino acids which play an important role in the life functions of the organism. Changes in the structure of amino acids and peptides are vital for eluci...
Silver Amino Acid Sequence Spectrum Analysis, Raman Metal Nanoparticles Machine Learning Peptides
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Advances of deep Neural Networks (DNNs) in the development of peptide drugs.

Future medicinal chemistry Feb 12, 2025
Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexi...
Humans Neural Networks, Computer Peptides Drug Development Drug Design Deep Learning
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Enhanced authentication of organic milk using MALDI-TOF MS with combined lipid-peptide fingerprinting and machine learning integration.

Food chemistry Feb 10, 2025
This study introduces a method for authenticating organic milk and determining its geographic region using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Both lipids and peptides were analyzed, and their ...
Animals Peptides Cattle Machine Learning Milk Food, Organic Peptide Mapping Food Contamination Lipids Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Deep Learning Combined with Quantitative Structure‒Activity Relationship Accelerates De Novo Design of Antifungal Peptides.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 8, 2025
Novel antifungal drugs that evade resistance are urgently needed for Candida infections. Antifungal peptides (AFPs) are potential candidates due to their specific mechanism of action, which makes them less prone to developing drug resistance. An AFP ...
Drug Design Deep Learning Quantitative Structure-Activity Relationship Microbial Sensitivity Tests Candida albicans Candidiasis Antifungal Agents Animals Peptides
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Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms.

Biosensors Jan 28, 2025
Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical dev...
SARS-CoV-2 Peptides Humans Molecular Docking Simulation Artificial Intelligence Saliva COVID-19 Biosensing Techniques Machine Learning Algorithms Spike Glycoprotein, Coronavirus Electrochemical Techniques
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Deep Learning Predicts Non-Normal Transmission Distributions in High-Field Asymmetric Waveform Ion Mobility (FAIMS) Directly from Peptide Sequence.

Analytical chemistry Jan 26, 2025
Peptide ion mobility adds an extra dimension of separation to mass spectrometry-based proteomics. The ability to accurately predict peptide ion mobility would be useful to expedite assay development and to discriminate true answers in a database sear...
Ions Ion Mobility Spectrometry Escherichia coli Mass Spectrometry Amino Acid Sequence Humans Peptides Neural Networks, Computer Deep Learning
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Feature selection enhances peptide binding predictions for TCR-specific interactions.

Frontiers in immunology Jan 23, 2025
INTRODUCTION: T-cell receptors (TCRs) play a critical role in the immune response by recognizing specific ligand peptides presented by major histocompatibility complex (MHC) molecules. Accurate prediction of peptide binding to TCRs is essential for a...
Mice Peptide Library Peptides Machine Learning Receptors, Antigen, T-Cell Animals Protein Binding
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PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification.

Journal of proteome research Jan 22, 2025
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, d...
Humans Machine Learning Software Algorithms Tandem Mass Spectrometry Proteome Search Engine Peptides Escherichia coli HEK293 Cells Supervised Machine Learning Escherichia coli Proteins Proteomics
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