AIMC Topic: Peptides

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iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Artificial intelligence in medicine Mar 26, 2024
Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emerg...
Wavelet Analysis Antifungal Agents Mycoses Peptides Humans Neural Networks, Computer COVID-19 Algorithms
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In-depth discovery and taste presentation mechanism studies on umami peptides derived from fermented sea bass based on peptidomics and machine learning.

Food chemistry Mar 16, 2024
Umami peptides originating from fermented sea bass impart a distinctive flavor to food. Nevertheless, large-scale and rapid screening for umami peptides using conventional techniques is challenging because of problems such as prolonged duration and c...
Molecular Docking Simulation Proteomics Peptides Flavoring Agents Fish Proteins Fermentation Taste Humans Machine Learning Animals Bass
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Prediction of matrilineal specific patatin-like protein governing in-vivo maternal haploid induction in maize using support vector machine and di-peptide composition.

Amino acids Mar 9, 2024
The mutant matrilineal (mtl) gene encoding patatin-like phospholipase activity is involved in in-vivo maternal haploid induction in maize. Doubling of chromosomes in haploids by colchicine treatment leads to complete fixation of inbreds in just one g...
Haploidy Phospholipases Peptides Support Vector Machine Zea mays
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MMDB: Multimodal dual-branch model for multi-functional bioactive peptide prediction.

Analytical biochemistry Mar 7, 2024
Bioactive peptides can hinder oxidative processes and microbial spoilage in foodstuffs and play important roles in treating diverse diseases and disorders. While most of the methods focus on single-functional bioactive peptides and have obtained prom...
Amino Acid Sequence Peptides Deep Learning
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Building trust in deep learning-based immune response predictors with interpretable explanations.

Communications biology Mar 6, 2024
The ability to predict whether a peptide will get presented on Major Histocompatibility Complex (MHC) class I molecules has profound implications in designing vaccines. Numerous deep learning-based predictors for peptide presentation on MHC class I m...
Humans Reproducibility of Results Deep Learning Immunity Trust Peptides
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EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features.

Journal of bioinformatics and computational biology Feb 26, 2024
Antimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application with good prospects. Identifying AMPs through wet lab experiments remains expensive, time-consuming and challenging. Many machine learning methods have...
Deep Learning Neural Networks, Computer Peptides Algorithms Anti-Bacterial Agents
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Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations.

Nature communications Feb 21, 2024
We introduce a computational approach for the design of target-specific peptides. Our method integrates a Gated Recurrent Unit-based Variational Autoencoder with Rosetta FlexPepDock for peptide sequence generation and binding affinity assessment. Sub...
NF-kappa B Molecular Dynamics Simulation beta Catenin Deep Learning Protein Binding Peptides
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SME-MFP: A novel spatiotemporal neural network with multiangle initialization embedding toward multifunctional peptides prediction.

Computational biology and chemistry Feb 20, 2024
As a promising alternative to conventional antibiotic drugs in the biomedical field, functional peptide has been widely used in disease treatment owing to its low toxicity, high absorption rate, and biological activity. Recently, several machine lear...
Amino Acid Sequence Machine Learning Peptides Neural Networks, Computer
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Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

European journal of medicinal chemistry Feb 19, 2024
Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and li...
Technology Drug Development Structure-Activity Relationship Peptides Deep Learning
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From Organic Fragments to Photoswitchable Catalysts: The OFF-ON Structural Repository for Transferable Kernel-Based Potentials.

Journal of chemical information and modeling Feb 6, 2024
Structurally and conformationally diverse databases are needed to train accurate neural networks or kernel-based potentials capable of exploring the complex free energy landscape of flexible functional organic molecules. Curating such databases for s...
Neural Networks, Computer Organic Chemicals Entropy Databases, Factual Peptides
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