AIMC Topic: Peptides
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A genetic algorithm-based ensemble model for efficiently identifying interleukin 6 inducing peptides.
Scientific reports
Jul 1, 2025
Interleukin-6 (IL-6) is a cytokine with diverse biological activities that contribute to a variety of physiologic and immune responses. IL-6-inducing peptides are the short protein fragments that are critical for playing a contributing role in biolog...
Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA-A0201.
PloS one
Jun 27, 2025
Class Ι major histocompatibility complexes (MHC-Ι), encoded by the highly polymorphic HLA-A, HLA-B, and HLA-C genes in humans, are expressed on all nucleated cells. Both self and foreign proteins are processed to peptides of 8-10 amino acids, loaded ...
generation of peptide binders with desired properties by deep generative models reinforced through enrichment of focused sets for iterative fine-tuning.
Chemical communications (Cambridge, England)
Jun 24, 2025
Recurrent neural networks underwent reinforcement procedures for generation of peptide binders with desired properties. Docking and scoring of peptides from these models allowed enrichment of focused sets with validated sequences for iterative fine-...
Self-assembling peptide hydrogels: design, mechanisms, characterization, and biomedical applications.
Soft matter
Jun 19, 2025
Self-assembled peptide hydrogels have emerged as a research frontier in biomedical engineering due to their exceptional water-retention capacity and spatiotemporal drug release kinetics. Researchers can fabricate biomaterials with customizable struct...
Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.
Drug design, development and therapy
Jun 14, 2025
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the disease progression or reduce its harmful effects, and exhibit toxicity and side effects such as ga...
AVP-HNCL: Innovative Contrastive Learning with a Queue-Based Negative Sampling Strategy for Dual-Phase Antiviral Peptide Prediction.
Journal of chemical information and modeling
Jun 6, 2025
Viral infections have long been a core focus in the field of public health. Antiviral peptides (AVPs), due to their unique mechanisms of action and significant inhibitory effects against a wide range of viruses, exhibit tremendous potential in protec...
AI, docking, and molecular dynamics to track the binding of structural peptides to different keratin models.
International journal of biological macromolecules
May 30, 2025
The present work shows a computational approach to assess the interactions of different nature-inspired peptides with hair keratin models. An updated keratin model was validated, and comparisons with previous models were traced, thereby highlighting ...
Novel Computational Approaches in the Discovery and Identification of Bioactive Peptides: A Bioinformatics Perspective.
Journal of agricultural and food chemistry
May 24, 2025
Bioactive peptides are protein molecules known for their specific biological functions, offering promising applications across various fields including medicine, food, and cosmetics. Traditional approaches to the investigation of bioactive peptides t...
Immunopeptidomics-guided discovery and characterization of neoantigens for personalized cancer immunotherapy.
Science advances
May 21, 2025
Neoantigens have emerged as ideal targets for personalized cancer immunotherapy. We depict the pan-cancer peptide atlas by comprehensively collecting immunopeptidomics from 531 samples across 14 cancer and 29 normal tissues, and identify 389,165 cano...
Assessing the generalization capabilities of TCR binding predictors via peptide distance analysis.
PloS one
May 20, 2025
Understanding the interaction between T Cell Receptors (TCRs) and peptide-bound Major Histocompatibility Complexes (pMHCs) is crucial for comprehending immune responses and developing targeted immunotherapies. While recent machine learning (ML) model...
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