AIMC Topic: Peptides

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Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates.

Food & function Jul 31, 2023
Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are multi-factor induced neurological disorders that require management from multiple pathologies. The peptides from natural proteins with diverse physiological activity can be candidat...
Peptides Molecular Docking Simulation Alzheimer Disease Juglans Deep Learning Neuroprotective Agents
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MSBooster: improving peptide identification rates using deep learning-based features.

Nature communications Jul 27, 2023
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFrag...
Algorithms Peptides Databases, Protein Tandem Mass Spectrometry Deep Learning Chromatography, Liquid
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PepScaf: Harnessing Machine Learning with In Vitro Selection toward De Novo Macrocyclic Peptides against IL-17C/IL-17RE Interaction.

Journal of medicinal chemistry Jul 22, 2023
The combination of library-based screening and artificial intelligence (AI) has been accelerating the discovery and optimization of hit ligands. However, the potential of AI to assist in de novo macrocyclic peptide ligand discovery has yet to be full...
Peptide Library Peptides Interleukin-17 Artificial Intelligence Machine Learning
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DbyDeep: Exploration of MS-Detectable Peptides via Deep Learning.

Analytical chemistry Jul 17, 2023
Predicting peptide detectability is useful in a variety of mass spectrometry (MS)-based proteomics applications, particularly targeted proteomics. However, most machine learning-based computational methods have relied solely on information from the p...
Amino Acid Sequence Tandem Mass Spectrometry Peptides Deep Learning Proteins
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A Novel LSTM-Based Machine Learning Model for Predicting the Activity of Food Protein-Derived Antihypertensive Peptides.

Molecules (Basel, Switzerland) Jun 21, 2023
Food protein-derived antihypertensive peptides are a representative type of bioactive peptides. Several models based on partial least squares regression have been constructed to delineate the relationship between the structure and activity of the pep...
Antihypertensive Agents Machine Learning Algorithms Peptides
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HLA-II immunopeptidome profiling and deep learning reveal features of antigenicity to inform antigen discovery.

Immunity Jun 9, 2023
CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on antigen-presenting cells. Underrepresentation of diverse alleles in ligand databases and an incomple...
HLA Antigens Captan SARS-CoV-2 Epitopes, T-Lymphocyte Peptides Deep Learning Humans COVID-19
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Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery.

Expert opinion on drug discovery May 29, 2023
INTRODUCTION: Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experime...
Drug Discovery Protein Binding Artificial Intelligence Peptides Humans Proteins Molecular Weight
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Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing.

Genes May 29, 2023
Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design ...
Molecular Docking Simulation Proteins Animals Feathers Artificial Intelligence Peptides
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CysPresso: a classification model utilizing deep learning protein representations to predict recombinant expression of cysteine-dense peptides.

BMC bioinformatics May 16, 2023
BACKGROUND: Cysteine-dense peptides (CDPs) are an attractive pharmaceutical scaffold that display extreme biochemical properties, low immunogenicity, and the ability to bind targets with high affinity and selectivity. While many CDPs have potential a...
Mammals Cysteine Deep Learning Proteins Algorithms Peptides Animals
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Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking.

Journal of chemical information and modeling May 11, 2023
The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide intera...
Software Peptides Protein Binding Protein Conformation Proteins Molecular Docking Simulation Deep Learning
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