AIMC Topic: Peptides

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Multi-positive contrastive learning-based cross-attention model for T cell receptor-antigen binding prediction.

Computer methods and programs in biomedicine Aug 1, 2025
BACKGROUND AND OBJECTIVE: T cells play a vital role in the immune system by recognizing and eliminating infected or cancerous cells, thus driving adaptive immune responses. Their activation is triggered by the binding of T cell receptors (TCRs) to ep...
Protein Binding Computational Biology Major Histocompatibility Complex Peptides Receptors, Antigen, T-Cell Algorithms T-Lymphocytes Humans Machine Learning
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pACPs-DNN: Predicting anticancer peptides using novel peptide transformation into evolutionary and structure matrix-based images with self-attention deep learning model.

Computational biology and chemistry Aug 1, 2025
Globally, cancer remains a major health challenge due to its high mortality rates. Traditional experimental approaches and therapies are resource-intensive and often cause significant side effects. Anticancer peptides (ACPs) have emerged as alternati...
Peptides Antineoplastic Agents Humans Neural Networks, Computer Deep Learning
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Exploring the impact of bioactive peptides from fermented Milk proteins: A review with emphasis on health implications and artificial intelligence integration.

Food chemistry Jul 30, 2025
This review explores the health benefits of bioactive peptides (BAPs) from fermented milk proteins, emphasizing the transformative role of artificial intelligence (AI) and machine learning (ML) in advancing this field. BAPs exhibit diverse biological...
Fermentation Animals Humans Functional Food Peptides Milk Proteins Artificial Intelligence Cultured Milk Products
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iAVP-RFVOT: Identify Antiviral Peptides by Random Forest Voting Machine Learning with Unified Manifold Learning Embedded Features.

Biochemistry Jul 15, 2025
Viruses are transmitted through multiple routes and can cause a wide range of diseases. Antiviral peptides (AVPs) have emerged as a cost-effective and low-side-effect strategy for combating viral infections. However, identifying antiviral peptides ex...
Humans Machine Learning Antiviral Agents Random Forest Voting Algorithms Peptides
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Assessing Substrate Scope of the Cyclodehydratase LynD by mRNA Display-Enabled Machine Learning Models.

Biochemistry Jul 1, 2025
Many members of the broad family of enzymes, known as YcaOs have been shown to install azoline heterocycles post-translationally into peptide substrates. These moieties can help rigidify structures and contribute to the potent bioactivities of the ev...
RNA, Messenger Substrate Specificity Machine Learning Peptides
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Structure-based artificial intelligence-aided design of MYC-targeting degradation drugs for cancer therapy.

Biochemical and biophysical research communications Jun 20, 2025
The MYC protein is an oncoprotein that plays a crucial role in various cancers. Although its significance has been well recognized in research, the development of drugs targeting MYC remains relatively slow. In this study, we developed a novel MYC pe...
Humans Artificial Intelligence Peptides Drug Design Neoplasms Autophagy Cell Proliferation Antineoplastic Agents Proto-Oncogene Proteins c-myc Proteolysis Apoptosis Cell Line, Tumor
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PLPTP: A Motif-based Interpretable Deep Learning Framework Based on Protein Language Models for Peptide Toxicity Prediction.

Journal of molecular biology Jun 15, 2025
Peptide toxicity prediction holds significant importance in drug development and biotechnology, as accurately identifying toxic peptide sequences is crucial for designing safer peptide-based drugs. This study proposes a deep learning-based model for ...
Amino Acid Sequence Neural Networks, Computer Amino Acid Motifs Peptides Computational Biology Humans Deep Learning Proteins
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Discovery of unconventional and nonintuitive self-assembling peptide materials using experiment-driven machine learning.

Science advances Jun 13, 2025
Prediction of peptide secondary structure is challenging because of complex molecular interactions, sequence-specific behavior, and environmental factors. Traditional design strategies, based on hydrophobicity and structural propensity, can be biased...
Amino Acid Sequence Machine Learning Hydrophobic and Hydrophilic Interactions Peptides Protein Conformation, beta-Strand
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Using Machine Learning to Fast-Track Peptide Nanomaterial Discovery.

ACS nano Jun 10, 2025
Peptides can serve as building blocks for supramolecular materials because of their unique ability to self-assemble, offering potential applications in drug delivery, tissue engineering, and nanotechnology. In this review, we describe peptide self-as...
Humans Machine Learning Peptides Nanostructures Nanotechnology
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Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics.

Journal of chemical information and modeling Jun 9, 2025
Understanding the binding interactions within protein-peptide complexes is crucial for elucidating key physicochemical phenomena in biological systems. Among the outcomes of these interactions, biomolecular condensates have recently emerged as vital ...
Mutation Molecular Dynamics Simulation Peptides Protein Binding Hydrophobic and Hydrophilic Interactions src Homology Domains Artificial Intelligence
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