AIMC Topic: Peptides

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High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England) Jul 23, 2015
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...
Molecular Sequence Data Major Histocompatibility Complex Epitopes Amino Acid Sequence Peptides Support Vector Machine ROC Curve Databases, Protein Humans Area Under Curve Neural Networks, Computer Protein Binding Algorithms
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TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins.

Bioinformatics (Oxford, England) Jun 16, 2015
MOTIVATION: Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can...
Peptides Support Vector Machine Mitochondria Protein Transport Eukaryota Sequence Analysis, Protein Mitochondrial Proteins Chloroplast Proteins Chloroplasts Machine Learning Software
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NIEluter: Predicting peptides eluted from HLA class I molecules.

Journal of immunological methods Apr 7, 2015
The immune system has evolved to make a diverse repertoire of peptides processed from self and foreign proteomes, which are displayed in antigen-binding grooves of major histocompatibility complex (MHC) proteins at cell surface for surveillance by T ...
Histocompatibility Antigens Class I Markov Chains Protein Binding Immunity, Cellular Support Vector Machine Humans Algorithms T-Lymphocytes Peptides
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Machine learning assisted design of highly active peptides for drug discovery.

PLoS computational biology Apr 7, 2015
The discovery of peptides possessing high biological activity is very challenging due to the enormous diversity for which only a minority have the desired properties. To lower cost and reduce the time to obtain promising peptides, machine learning ap...
Machine Learning Sequence Analysis, Protein Structure-Activity Relationship Peptides Bacterial Physiological Phenomena Amino Acid Sequence Drug Discovery Protein Interaction Mapping Pattern Recognition, Automated Antimicrobial Cationic Peptides Molecular Sequence Data
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Prediction and analysis of quorum sensing peptides based on sequence features.

PloS one Mar 17, 2015
Quorum sensing peptides (QSPs) are the signaling molecules used by the Gram-positive bacteria in orchestrating cell-to-cell communication. In spite of their enormous importance in signaling process, their detailed bioinformatics analysis is lacking. ...
Quorum Sensing Bacteria Software Support Vector Machine Peptides Sequence Analysis, Protein Bacterial Proteins
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Virtual screening of umami peptides during sufu ripening based on machine learning and molecular docking to umami receptor T1R1/T1R3.

Food chemistry Sep 15, 2025
Umami peptides might significantly contribute to the taste of sufu. However, the inefficiencies of traditional identification methods had great limitations. This study explored a new approach for umami peptides characterization in sufu. Combining pep...
Machine Learning Peptides Molecular Docking Simulation Humans Flavoring Agents Glycine max Soy Foods Receptors, G-Protein-Coupled Amino Acid Sequence Taste
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Heterojunction nanofluidic memristors based on peptide chain valves for neuromorphic applications.

Biosensors & bioelectronics Aug 15, 2025
Memristors exhibit significant potential for neuromorphic computing due to their unique properties. This study introduces a heterojunction nanofluidic memristor (HJNFM) and explores its applications in simulating synapses and constructing neural netw...
Disulfides Tin Compounds Peptides Biosensing Techniques Equipment Design Molybdenum Nanostructures Nanotechnology Neural Networks, Computer
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Virtual Hydrolysis-Based Screening of Wheat-Derived DPP-IV Inhibitory Peptides: A Mechanistic Analysis Integrating Cell Experiments and Molecular Dynamics Simulations.

Journal of agricultural and food chemistry Aug 6, 2025
Dipeptidyl peptidase-IV (DPP-IV) inhibitors play a critical role in the treatment of diabetes and metabolic diseases. This study combines computational simulations with experimental validation to identify peptides with potential DPP-IV inhibitory act...
Plant Proteins Molecular Dynamics Simulation Dipeptidyl Peptidase 4 Amino Acid Sequence Humans Hydrolysis Dipeptidyl-Peptidase IV Inhibitors Peptides Triticum
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PSR-MAPMS: A new approach for the interpretable prediction of myelin autoantigenic peptides in multiple sclerosis using multi-source propensity scores.

Protein science : a publication of the Protein Society Aug 1, 2025
Within the central nervous system, the myelin sheath is composed of elements known as myelin autoantigens that are mistakenly targeted by the immune system in multiple sclerosis (MS). This autoimmune attack leads to the destruction of myelin, resulti...
Myelin Sheath Propensity Score Peptides Autoantigens Multiple Sclerosis Humans Machine Learning T-Lymphocytes
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A large language model for predicting neurotoxic peptides and neurotoxins.

Protein science : a publication of the Protein Society Aug 1, 2025
The accurate prediction of neurotoxicity in peptides and proteins is essential for the safety evaluation of therapeutic proteins and genetically modified (GM) organisms. Existing tools, including our earlier method NTxPred, typically use a single pre...
Databases, Protein Machine Learning Humans Large Language Models Software Neurotoxins Peptides
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