AIMC Topic: Amino Acid Sequence

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Machine learning designs new GCGR/GLP-1R dual agonists with enhanced biological potency.

Nature chemistry May 16, 2024
Several peptide dual agonists of the human glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R) are in development for the treatment of type 2 diabetes, obesity and their associated complications. Candidates must have high poten...
Peptides Drug Design Hypoglycemic Agents Humans Machine Learning Receptors, Glucagon Glucagon-Like Peptide-1 Receptor Agonists Amino Acid Sequence Glucagon-Like Peptide-1 Receptor
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Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.

Journal of chemical information and modeling May 13, 2024
Currently, antimicrobial resistance constitutes a serious threat to human health. Drugs based on antimicrobial peptides (AMPs) constitute one of the alternatives to address it. Shallow and deep learning (DL)-based models have mainly been built from a...
Antimicrobial Peptides Deep Learning Models, Molecular Amino Acid Sequence Protein Conformation Amino Acids
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Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

Physical chemistry chemical physics : PCCP May 8, 2024
The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability lea...
Machine Learning COVID-19 SARS-CoV-2 Humans Viral Nonstructural Proteins Protein Multimerization Coronavirus RNA-Dependent RNA Polymerase Mutation Amino Acid Sequence
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Co-Mutations and Possible Variation Tendency of the Spike RBD and Membrane Protein in SARS-CoV-2 by Machine Learning.

International journal of molecular sciences Apr 25, 2024
Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike p...
Machine Learning COVID-19 Protein Binding Spike Glycoprotein, Coronavirus SARS-CoV-2 Humans Amino Acid Sequence Coronavirus M Proteins Mutation Protein Domains
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Computational scoring and experimental evaluation of enzymes generated by neural networks.

Nature biotechnology Apr 23, 2024
In recent years, generative protein sequence models have been developed to sample novel sequences. However, predicting whether generated proteins will fold and function remains challenging. We evaluate a set of 20 diverse computational metrics to ass...
Algorithms Computational Biology Protein Engineering Neural Networks, Computer Enzymes Amino Acid Sequence
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Model fusion for predicting unconventional proteins secreted by exosomes using deep learning.

Proteomics Apr 21, 2024
Unconventional secretory proteins (USPs) are vital for cell-to-cell communication and are necessary for proper physiological processes. Unlike classical proteins that follow the conventional secretory pathway via the Golgi apparatus, these proteins a...
Algorithms Deep Learning Humans Neural Networks, Computer Computational Biology Proteins Amino Acid Sequence Exosomes
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KEGG orthology prediction of bacterial proteins using natural language processing.

BMC bioinformatics Apr 11, 2024
BACKGROUND: The advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing the capacity of manual curation. A large number of bacterial protein sequences remain unannotated by ...
Molecular Sequence Annotation Genome Bacterial Proteins Amino Acid Sequence Natural Language Processing
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sAMP-VGG16: Force-field assisted image-based deep neural network prediction model for short antimicrobial peptides.

Proteins Mar 23, 2024
During the last three decades, antimicrobial peptides (AMPs) have emerged as a promising therapeutic alternative to antibiotics. The approaches for designing AMPs span from experimental trial-and-error methods to synthetic hybrid peptide libraries. T...
Deep Learning Computational Biology Amino Acid Sequence Antimicrobial Peptides Antimicrobial Cationic Peptides Software Algorithms Humans Neural Networks, Computer
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Kinetic Ensemble of Tau Protein through the Markov State Model and Deep Learning Analysis.

Journal of chemical theory and computation Mar 19, 2024
The ordered assembly of Tau protein into filaments characterizes Alzheimer's and other neurodegenerative diseases, and thus, stabilization of Tau protein is a promising avenue for tauopathies therapy. To dissect the underlying aggregation mechanisms ...
Amino Acid Sequence tau Proteins Humans Deep Learning gamma-Globulins Melphalan Protein Structure, Secondary Tauopathies
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Using protein language models for protein interaction hot spot prediction with limited data.

BMC bioinformatics Mar 16, 2024
BACKGROUND: Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained signifi...
Amino Acid Sequence Machine Learning Proteins Humans
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