AIMC Topic: Peptides

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A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society Oct 30, 2020
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...
Ubiquitin Spectrophotometry, Infrared Protein Structure, Secondary Protein Folding Proteins Amides Quantum Theory Temperature Peptides Machine Learning
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Predictive Modeling of Angiotensin I-Converting Enzyme Inhibitory Peptides Using Various Machine Learning Approaches.

Journal of agricultural and food chemistry Oct 1, 2020
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...
Models, Molecular Angiotensin-Converting Enzyme Inhibitors Hydrogen Bonding Peptidyl-Dipeptidase A Machine Learning Peptides Molecular Docking Simulation
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DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.

Proteomics Sep 27, 2020
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...
Humans Peptides Algorithms Deep Learning Reproducibility of Results Databases, Protein Tandem Mass Spectrometry
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Evolutionary artificial intelligence based peptide discoveries for effective Covid-19 therapeutics.

Biochimica et biophysica acta. Molecular basis of disease Sep 24, 2020
An epidemic caused by COVID-19 in China turned into pandemic within a short duration affecting countries worldwide. Researchers and companies around the world are working on all the possible strategies to develop a curative or preventive strategy for...
Virus Replication Antibodies, Viral Molecular Dynamics Simulation COVID-19 Drug Treatment Humans Artificial Intelligence Antiviral Agents COVID-19 Peptide Library Viral Vaccines SARS-CoV-2 Peptides
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PeptiDesCalculator: Software for computation of peptide descriptors. Definition, implementation and case studies for 9 bioactivity endpoints.

Proteins Sep 17, 2020
We present a novel Java-based program denominated PeptiDesCalculator for computing peptide descriptors. These descriptors include: redefinitions of known protein parameters to suite the peptide domain, generalization schemes for the global descriptio...
Software Anti-Bacterial Agents Neoplasms Peptides Humans Neural Networks, Computer Support Vector Machine Candida albicans Antifungal Agents Listeria monocytogenes Antineoplastic Agents HIV Infections Antiviral Agents Peptide Mapping Pseudomonas aeruginosa Hepatitis C Protein Stability
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Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Cell systems Sep 10, 2020
Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I expos...
Betacoronavirus SARS-CoV-2 Peptides Protein Binding Polymorphism, Genetic Viral Proteins Histocompatibility Antigens Class I Haplotypes Humans Neural Networks, Computer
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Prediction of Specific TCR-Peptide Binding From Large Dictionaries of TCR-Peptide Pairs.

Frontiers in immunology Aug 25, 2020
Current sequencing methods allow for detailed samples of T cell receptors (TCR) repertoires. To determine from a repertoire whether its host had been exposed to a target, computational tools that predict TCR-epitope binding are required. Currents too...
Receptors, Antigen, T-Cell Protein Binding Signal Transduction Protein Interaction Domains and Motifs Antigens Epitopes, T-Lymphocyte Databases, Protein Binding Sites Peptides Ligands Humans Deep Learning Software T-Lymphocytes
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Comprehensive Prediction of Molecular Recognition in a Combinatorial Chemical Space Using Machine Learning.

ACS combinatorial science Aug 17, 2020
In combinatorial chemical approaches, optimizing the composition and arrangement of building blocks toward a particular function has been done using a number of methods, including high throughput molecular screening, molecular evolution, and computat...
Ligands Peptide Library Peptides High-Throughput Screening Assays Structure-Activity Relationship Protein Binding Models, Molecular Combinatorial Chemistry Techniques Machine Learning Molecular Structure Amino Acid Sequence
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rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond.

Analytical chemistry Jul 21, 2020
We present herein rPTMDetermine, an adaptive and fully automated methodology for validation of the identification of rarely occurring post-translational modifications (PTMs), using a semisupervised approach with a linear discriminant analysis (LDA) a...
Automation Tyrosine Supervised Machine Learning Amino Acid Sequence Nitrates Peptides Protein Processing, Post-Translational Discriminant Analysis
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Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology Jun 24, 2020
Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contain...
Cytokines Peptides Humans Prognosis ROC Curve Female Biomarkers, Tumor Machine Learning Neoplasm Staging Melanoma Male Neoplasm Metastasis Middle Aged
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