AIMC Topic: Peptides

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Recurrent Neural Networks Predict Future Peptide Aggregation for Drug Development.

Molecular pharmaceutics
Physical stability of an active pharmaceutical ingredient (API) is a key consideration in the development of a pharmaceutical drug. Solution conditions such as pH, excipient concentrations, and storage temperatures can impact the physical stability o...

Virtual screening of salty peptides from enzymatic and fermented products of wheat gluten and its molecular mechanism of interaction with TMC4 receptor.

Food chemistry
The health risks associated with excessive sodium intake have prompted an exploration of natural salt substitutes. This study was oriented to explore the salty peptides from enzymatic and fermented products of wheat gluten (WG) with different degrees...

Enhancing peptide identification in metaproteomics through curriculum learning in deep learning.

Nature communications
Metaproteomics offers a powerful window into the active functions of microbial communities, but accurately identifying peptides remains challenging due to the size and incompleteness of protein databases derived from metagenomes. These databases ofte...

BLSAM-TIP: Improved and robust identification of tyrosinase inhibitory peptides by integrating bidirectional LSTM with self-attention mechanism.

PloS one
Tyrosinase plays a central role in melanin biosynthesis, and its dysregulation has been implicated in the pathogenesis of various pigmentation disorders. The precise identification of tyrosinase inhibitory peptides (TIPs) is critical, as these bioact...

The Identification of Biological Stains at Crime Scenes: A Promising Role for Proteomics and Machine Learning.

Analytical chemistry
Forensic body fluid identification is crucial for reconstructing crime scene events. While DNA analysis provides individualization, it lacks information about the fluid's origin. We developed and evaluated three complementary proteomic approaches usi...

Discovering of novel umami-enhancing peptides from Flammulina filiformis: Combining virtual screening, machine learning, molecular dynamics simulations, and sensory evaluation.

Food chemistry
This research employed integrated machine learning and bioinformatics approaches to identify umami-enhancing peptides from Flammulina filiformis, elucidate their mechanisms of umami augmentation, and validate their efficacy through sensory evaluation...

DeepMaT: Prediction of Target Peptide Classification and Cleavage Site by Combining Mamba2 and Multiple Attention Mechanisms.

Journal of chemical information and modeling
Signal peptides and transit peptides are essential for directing mature proteins to their proper cellular locations, particularly through cleavage following transport. Although various prediction tools achieve strong performance in identifying and cl...

iBitter-Stack: A multi-representation ensemble learning model for accurate bitter peptide identification.

Journal of molecular biology
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the undesirable taste of hydrolyzed proteins but also play key roles in physi...

MCMFPP: A Multifunctional Peptides Prediction Method Based on Class Feature Enhancement and Classifier Fusion.

Journal of chemical information and modeling
With the increasing discovery of peptide sequences and the growing demand for peptide-targeted drugs, traditional wet-lab experiment methods have become inadequate for peptide function prediction due to their high cost and that they are time consumin...

Separation, characterization, AI screening, and bioactivities of marine bioactive peptides: A review.

Food chemistry
Marine bioactive peptides (MBPs) are short-chain amino acid polymers derived from marine sources that possess specific physiological activities. Owing to their unique origins and structural diversity, MBPs have attracted considerable research interes...