AIMC Topic: Peptides

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Classification of small blue round cell tumors by integrating peptide and N-glycan mass imaging spectrometric profiles.

Analytica chimica acta
BACKGROUND: Small blue round cell tumor (SBRCT) is an umbrella term for several tumor types of completely different cellular origin and differentiation. Members of this tumor group share a common morphological phenotype, which is characterized by sma...

Accelerating Prediction of Antiviral Peptides Using Genetic Algorithm-Based Weighted Multiperspective Descriptors with Self-Normalized Deep Networks.

Journal of chemical information and modeling
The accurate prediction of antiviral peptides (AVPs) plays a crucial role in accelerating the development of peptide-based therapeutics. Despite extensive production of antiviral medications, viral diseases remain a major human health concern. AVPs h...

IQUP identifies quantitatively unreliable spectra with machine learning for isobaric labeling-based proteomics.

Scientific reports
Mass spectrometry‑based proteomics using isobaric labeling technology has become popular for proteomic quantitation. Existing approaches rely on the mechanism of target-decoy search and false discovery rate control to examine whether a peptide-spectr...

PepBAN: A Deep Learning Framework with Bilinear Attention and Adversarial Learning for Peptide-Protein Interaction Prediction.

Journal of chemical information and modeling
Accurate prediction of the peptide-protein interaction (PepPI) is crucial for developing peptide-based therapeutics and vaccines. However, this computational task has traditionally faced significant challenges, such as the scarcity of structure data ...

Modeling skin sensitization: hierarchical support vector regression-based prediction of lysine depletion in DPRA.

Chemico-biological interactions
Skin sensitization is a critical endpoint in toxicology, especially in the context of drug discovery and development process for topical and transdermal treatments. Accurate evaluation of skin sensitization potential is essential to ensure the safety...

Machine Learning-Assisted Real-Time Inflammation Monitoring and Optimal Treatment of Diabetic Wounds Based on a Ratiometric Fluorescent Sensing Peptide Hydrogel.

Nano letters
Managing inflammation in diabetic chronic wounds remains a major clinical challenge, primarily due to the lack of real-time monitoring techniques. To address this issue, we developed a peptide hydrogel capable of simultaneously monitoring the inflamm...

MetaMBP: Few-Shot Multilabel Prediction of Bioactive Peptides Based on Deep Metric Meta-Learning.

Journal of chemical information and modeling
Bioactive peptides are highly specific and have low toxicity, making them a promising treatment option. There are many different types of bioactive peptides, while some types have limited samples (under 500). Methods that can handle limited types of ...

Unveiling anticancer peptides; from the mechanisms of action to their development through artificial intelligence.

European journal of pharmacology
Cancer is a leading cause of death worldwide and a major burden on the healthcare system. Current treatment methods are limited as they have low selectivity, unspecific targeting and increasing multidrug resistance. Therefore, newer modes of therapeu...

Umami-Transformer: A deep learning framework for high-precision prediction and experimental validation of umami peptides.

Food chemistry
In food field, both identification of umami peptides and their sensory evaluation are limited by low efficiency of traditional methods and subjectivity of human-based assessments. To overcome these issues, Umami-Transformer was developed by integrati...

PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction.

Journal of chemical information and modeling
Accurate modeling of protein-peptide interactions is essential for understanding fundamental biological processes and designing peptide-based drugs. However, predicting the complex structures of these interactions remains challenging, primarily due t...