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Peptides

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Evolutionary artificial intelligence based peptide discoveries for effective Covid-19 therapeutics.

Biochimica et biophysica acta. Molecular basis of disease
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...

PeptiDesCalculator: Software for computation of peptide descriptors. Definition, implementation and case studies for 9 bioactivity endpoints.

Proteins
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...

Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Cell systems
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...

Prediction of Specific TCR-Peptide Binding From Large Dictionaries of TCR-Peptide Pairs.

Frontiers in immunology
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...

Comprehensive Prediction of Molecular Recognition in a Combinatorial Chemical Space Using Machine Learning.

ACS combinatorial science
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...

rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond.

Analytical chemistry
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...

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology
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...

IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Immunogenetics
Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen...

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Frontiers in immunology
Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adve...

The proteome landscape of the kingdoms of life.

Nature
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported, ...