AIMC Topic: Peptides

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PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

European journal of medicinal chemistry Jun 25, 2024
Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial in...
Humans Deep Learning Dose-Response Relationship, Drug Peptides Peptides, Cyclic Macrocyclic Compounds Structure-Activity Relationship Molecular Structure
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mACPpred 2.0: Stacked Deep Learning for Anticancer Peptide Prediction with Integrated Spatial and Probabilistic Feature Representations.

Journal of molecular biology Jun 25, 2024
Anticancer peptides (ACPs), naturally occurring molecules with remarkable potential to target and kill cancer cells. However, identifying ACPs based solely from their primary amino acid sequences remains a major hurdle in immunoinformatics. In the pa...
Amino Acid Sequence Deep Learning Computational Biology Peptides Antineoplastic Agents Humans Neural Networks, Computer Software
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Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences.

Scientific reports Jun 22, 2024
Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angiogenic peptides (AAPs), with the capability of inhibiting angiogenesis, are promising candidates in cancer treatment. We propose AAPL, a sequence-base...
Machine Learning Algorithms Angiogenesis Inhibitors Amino Acid Sequence Peptides Humans
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Hybrid transformer-CNN model for accurate prediction of peptide hemolytic potential.

Scientific reports Jun 20, 2024
Hemolysis is a crucial factor in various biomedical and pharmaceutical contexts, driving our interest in developing advanced computational techniques for precise prediction. Our proposed approach takes advantage of the unique capabilities of convolut...
Hemolysis Peptides Computational Biology Humans Neural Networks, Computer
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DP-site: A dual deep learning-based method for protein-peptide interaction site prediction.

Methods (San Diego, Calif.) Jun 12, 2024
BACKGROUND: Protein-peptide interaction prediction is an important topic for several applications including various biological processes, understanding drug discovery, protein function abnormal cellular behaviors, and treating diseases. Over the year...
Software Peptides Deep Learning Humans Neural Networks, Computer Binding Sites Protein Interaction Mapping Proteins Databases, Protein Protein Binding Computational Biology
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Sequence homology score-based deep fuzzy network for identifying therapeutic peptides.

Neural networks : the official journal of the International Neural Network Society Jun 10, 2024
The detection of therapeutic peptides is a topic of immense interest in the biomedical field. Conventional biochemical experiment-based detection techniques are tedious and time-consuming. Computational biology has become a useful tool for improving ...
Computational Biology Fuzzy Logic Area Under Curve Deep Learning ROC Curve Humans Algorithms Peptides Neural Networks, Computer
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HeteroTCR: A heterogeneous graph neural network-based method for predicting peptide-TCR interaction.

Communications biology Jun 4, 2024
Identifying interactions between T-cell receptors (TCRs) and immunogenic peptides holds profound implications across diverse research domains and clinical scenarios. Unsupervised clustering models (UCMs) cannot predict peptide-TCR binding directly, w...
Neural Networks, Computer Peptides Humans Computational Biology Receptors, Antigen, T-Cell Protein Binding
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Raman Spectra of Amino Acids and Peptides from Machine Learning Polarizabilities.

Journal of chemical information and modeling Jun 3, 2024
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides, and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations, which can n...
Neural Networks, Computer Machine Learning Density Functional Theory Amino Acids Molecular Dynamics Simulation Peptides Spectrum Analysis, Raman
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UmamiPreDL: Deep learning model for umami taste prediction of peptides using BERT and CNN.

Computational biology and chemistry May 29, 2024
Taste is crucial in driving food choice and preference. Umami is one of the basic tastes defined by characteristic deliciousness and mouthfulness that it imparts to foods. Identification of ingredients to enhance umami taste is of significant value t...
Deep Learning Humans Taste Peptides
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Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining.

Microbiome May 24, 2024
BACKGROUND: Microbial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising...
Bacteriophages Peptides Oceans and Seas Deep Learning Metagenomics Metagenome Protein Processing, Post-Translational Seawater Ribosomes Microbiota Bacteria
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