AIMC Topic: Peptides

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A robust ensemble framework for anticancer peptide classification using multi-model voting approach.

Computers in biology and medicine Apr 1, 2025
Anticancer peptides (ACPs) hold great potential for cancer therapeutics, yet accurately identifying them remains a challenging task due to the complexity of peptide sequences and their interactions with biological systems. In this study, we propose a...
Machine Learning Algorithms Neoplasms Humans Voting Computational Biology Databases, Protein Peptides Antineoplastic Agents
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Deep learning in GPCR drug discovery: benchmarking the path to accurate peptide binding.

Briefings in bioinformatics Mar 4, 2025
Deep learning (DL) methods have drastically advanced structure-based drug discovery by directly predicting protein structures from sequences. Recently, these methods have become increasingly accurate in predicting complexes formed by multiple protein...
Receptors, G-Protein-Coupled Benchmarking Deep Learning Protein Binding Ligands Peptides Drug Discovery Humans
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iMFP-LG: Identify Novel Multi-functional Peptides Using Protein Language Models and Graph-based Deep Learning.

Genomics, proteomics & bioinformatics Jan 15, 2025
Functional peptides are short amino acid fragments that have a wide range of beneficial functions for living organisms. The majority of previous studies have focused on mono-functional peptides, but an increasing number of multi-functional peptides h...
Humans Peptides Deep Learning
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Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

PloS one Jan 1, 2025
Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present...
Male Middle Aged Peptides Female Adult Depression Oxidative Stress Mitochondria Depressive Disorder, Major Severity of Illness Index Humans Algorithms Biomarkers Machine Learning
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ACP-DPE: A Dual-Channel Deep Learning Model for Anticancer Peptide Prediction.

IET systems biology Jan 1, 2025
Cancer is a serious and complex disease caused by uncontrolled cell growth and is becoming one of the leading causes of death worldwide. Anticancer peptides (ACPs), as a bioactive peptide with lower toxicity, emerge as a promising means of effectivel...
Deep Learning Computational Biology Neoplasms Humans Peptides Antineoplastic Agents
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StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.

IET systems biology Jan 1, 2025
Hypertension, often known as high blood pressure, is a major concern to millions of individuals globally. Recent studies have demonstrated the significant efficacy of naturally derived peptides in reducing blood pressure. Hypertension is one of the r...
Algorithms Peptides Antihypertensive Agents Computational Biology Humans Machine Learning
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iACVP-MR: Accurate Identification of Anti-coronavirus Peptide based on Multiple Features Information and Recurrent Neural Network.

Current medicinal chemistry Jan 1, 2025
BACKGROUND: Over the years, viruses have caused human illness and threatened human health. Therefore, it is pressing to develop anti-coronavirus infection drugs with clear function, low cost, and high safety. Anti-coronavirus peptide (ACVP) is a key ...
Antiviral Agents Coronavirus Recurrent Neural Networks Neural Networks, Computer Humans Peptides
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EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

Current medicinal chemistry Jan 1, 2025
BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe acute respiratory syndrome (SARS-CoV) and SARS-CoV-2. Many peptides in the host defense system have an...
Antiviral Agents COVID-19 Drug Treatment SARS-CoV-2 Peptides Machine Learning COVID-19 Humans Neural Networks, Computer
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TPepRet: a deep learning model for characterizing T-cell receptors-antigen binding patterns.

Bioinformatics (Oxford, England) Dec 26, 2024
MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer immunotherapy, vaccine design, and autoimmune disease management. Understanding the intricate binding ...
SARS-CoV-2 Computational Biology Deep Learning Humans Peptides COVID-19 Protein Binding Receptors, Antigen, T-Cell
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TPepPro: a deep learning model for predicting peptide-protein interactions.

Bioinformatics (Oxford, England) Dec 26, 2024
MOTIVATION: Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing approval rates by the FDA of USA. To identify the most potential peptides, study on peptide-pr...
Computational Biology Software Databases, Protein Peptides Proteins Deep Learning
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