AIMC Topic: Peptides
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Machine learning models for predicting configuration of modified knuckle epitope peptides of BMP-2 protein using mesoscale simulation data.
Physical chemistry chemical physics : PCCP
Apr 30, 2025
The high doses of bone morphogenetic proteins (BMPs) cause undesired side effects in skeletal tissue regeneration. An alternative approach is to use the bioactive knuckle epitope domain of BMP-2 (BMP2-KEP) with an open-arm structure as part of the pr...
Dynamics and Machine Learning Reveal the Link between Tripeptide Sequences and Evaporation-Driven Material Properties.
Nano letters
Apr 27, 2025
Previous research showed that a peptide composed of three tyrosines (YYY) can turn into organic glass and cause strong adhesion between substrates via evaporation. However, the mechanisms of these processes remain unclear, and the exploration of appl...
Topology-Enhanced Machine Learning Model (Top-ML) for Anticancer Peptide Prediction.
Journal of chemical information and modeling
Apr 14, 2025
Recently, therapeutic peptides have demonstrated great promise for cancer treatment. To explore powerful anticancer peptides, artificial intelligence (AI)-based approaches have been developed to systematically screen potential candidates. However, th...
Peptide Property Prediction for Mass Spectrometry Using AI: An Introduction to State of the Art Models.
Proteomics
Apr 10, 2025
This review explores state of the art machine learning and deep learning models for peptide property prediction in mass spectrometry-based proteomics, including, but not limited to, models for predicting digestibility, retention time, charge state di...
From prediction to design: Revealing the mechanisms of umami peptides using interpretable deep learning, quantum chemical simulations, and module substitution.
Food chemistry
Apr 9, 2025
This study screened and designed umami peptides using deep learning model and module substitution strategies. The predictive model, which integrates pre-training, enhanced feature, and contrastive learning module, achieved an accuracy of 0.94, outper...
SeqNovo: De Novo Peptide Sequencing Prediction in IoMT via Seq2Seq.
IEEE journal of biomedical and health informatics
Apr 4, 2025
In the Internet of Medical Things (IoMT), de novo peptide sequencing prediction is one of the most important techniques for the fields of disease prediction, diagnosis, and treatment. Recently, deep-learning-based peptide sequencing prediction has be...
Production of bioactive peptides by high-voltage pulsed electric field: Protein extraction, mechanism, research status and collaborative application.
Food chemistry
Apr 1, 2025
Bioactive peptides exhibit a variety of potential applications in the fields of medicine, food and cosmetics. However, studies have shown that the traditional preparation is characterized by low efficiency, substantial pollution, limited activities a...
Machine learning-driven discovery of bioactive peptides from duckweed (Lemnaceae) protein hydrolysates: Identification and experimental validation of 20 novel antihypertensive, antidiabetic, and/or antioxidant peptides.
Food chemistry
Mar 28, 2025
Duckweed, a sustainable, protein-rich aquatic plant, has recently emerged as a promising source of bioactive peptides. However, their identification remains limited and challenging in such complex mixtures. Following duckweed hydrolysis with pepsin, ...
Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.
Molecular diversity
Mar 28, 2025
Antiviral peptides (AVPs) represent a novel and promising therapeutic alternative to conventional antiviral treatments, due to their broad-spectrum activity, high specificity, and low toxicity. The emergence of zoonotic viruses such as Zika, Ebola, a...
Learning the rules of peptide self-assembly through data mining with large language models.
Science advances
Mar 26, 2025
Peptides are ubiquitous and important biomolecules that self-assemble into diverse structures. Although extensive research has explored the effects of chemical composition and exterior conditions on self-assembly, a systematic study consolidating the...
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