AIMC Topic: Peptides

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BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.

BMC biology Jul 15, 2025
BACKGROUND: Diabetes is a global metabolic disease that urgently calls for the development of new and effective therapeutic agents. Anti-diabetic peptides (ADPs) have emerged as a research hotspot due to their therapeutic potential and natural safety...
Peptides Computational Biology Hypoglycemic Agents Humans
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NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.

BMC biology Jul 15, 2025
BACKGROUND: Accurate identification of anti-inflammatory peptides (AIPs) is crucial for drug development and inflammatory disease treatment. However, the short length and limited informational content of peptide sequences make precise computational r...
Machine Learning Anti-Inflammatory Agents Peptides Deep Learning
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Cysteine pattern barcoding-based dataset filtration enhances the machine learning-assisted interpretation of Conus venom peptide therapeutics.

PloS one Jul 11, 2025
Crude cone snail venom is a rich source of bioactive compounds with significant therapeutic potential. In this study, we conducted a comprehensive analysis of 5,985 cone snail peptides across 82 Conus species to identify unique cysteine (Cys) pattern...
Machine Learning Animals Cysteine Conotoxins Peptides Amino Acid Sequence Mollusk Venoms Conus Snail
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StackPIP: An Effective Computational Framework for Accurate and Balanced Identification of Proinflammatory Peptides.

Journal of chemical information and modeling Jul 10, 2025
Proinflammatory peptides (PIPs) play a crucial role in immune response modulation by orchestrating cytokine release and leukocyte recruitment. Accurate identification of PIPs is essential for understanding inflammation-related diseases and developing...
Inflammation Machine Learning Algorithms Peptides Computational Biology Humans
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Integrating Protein Language Models and Geometric Deep Learning for Peptide Toxicity Prediction.

Journal of chemical information and modeling Jul 8, 2025
Peptide toxicity prediction is a critical task in biomedical research, influencing drug safety and therapeutic development. Traditional methods, relying on sequence similarity or handcrafted features, struggle to capture the complex relationship betw...
Protein Conformation Amino Acid Sequence Peptides Humans Deep Learning Proteins Neural Networks, Computer Models, Molecular
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iACP-DPNet: a dual-pooling causal dilated convolutional network for interpretable anticancer peptide identification.

Functional & integrative genomics Jul 4, 2025
Anticancer peptides (ACPs) are acknowledged for their potential in cancer therapy, attributed to their safety, low side effects, and high target specificity. However, the discovery of ACPs is slowed by the high cost and labor-intensive nature of expe...
Humans Peptides Antineoplastic Agents Deep Learning Computational Biology
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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...
Genetic Algorithms Deep Learning Computational Biology Peptides Algorithms Humans Interleukin-6 Machine Learning
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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 ...
Amino Acids Humans HLA-A2 Antigen Protein Binding Machine Learning Peptides
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From precision synthesis to cross-industry applications: The future of emerging peptide technologies.

Pharmacological research Jun 25, 2025
Peptides, derived primarily from natural bioactive sources, play essential roles in human physiological processes such as hormone regulation and nerve signal transmission. Recent advances in phage display technology have revolutionized peptide screen...
Humans Peptides Food Industry Artificial Intelligence Animals
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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-...
Protein Binding Peptides Neural Networks, Computer Molecular Docking Simulation
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