AIMC Topic: Protein Transport

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Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder.

Nature communications May 4, 2025
Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protei...
Protein Transport Peptides Eukaryota Mitochondria Humans Autoencoder Animals
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In Silico Screening and Optimization of Cell-Penetrating Peptides Using Deep Learning Methods.

Biomolecules Mar 13, 2023
Cell-penetrating peptides (CPPs) have great potential to deliver bioactive agents into cells. Although there have been many recent advances in CPP-related research, it is still important to develop more efficient CPPs. The development of CPPs by in s...
Amino Acid Sequence Protein Transport Cell-Penetrating Peptides Humans Deep Learning
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Self-supervised deep learning encodes high-resolution features of protein subcellular localization.

Nature methods Jul 25, 2022
Explaining the diversity and complexity of protein localization is essential to fully understand cellular architecture. Here we present cytoself, a deep-learning approach for fully self-supervised protein localization profiling and clustering. Cytose...
Protein Transport Organelles Cluster Analysis Proteins Deep Learning
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Selective chemical probes can untangle the complexity of the plant cell endomembrane system.

Current opinion in plant biology May 11, 2022
The endomembrane system is critical for plant growth and development and understanding its function and regulation is of great interest for plant biology research. Small-molecule targeting distinctive endomembrane components have proven powerful tool...
Phenotype Plants Plant Cells Artificial Intelligence Protein Transport
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MLCPP 2.0: An Updated Cell-penetrating Peptides and Their Uptake Efficiency Predictor.

Journal of molecular biology Apr 28, 2022
Cell-penetrating peptides (CPPs) translocate into the cell as various biologically active conjugates and possess numerous biomedical applications. Several machine learning-based predictors have been proposed in the past, but they mostly focus on iden...
Software Algorithms Computational Biology Machine Learning Internet Use Protein Transport Cell-Penetrating Peptides
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Deep learning to design nuclear-targeting abiotic miniproteins.

Nature chemistry Aug 9, 2021
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...
Protein Conformation Protein Transport Datasets as Topic Cell Nucleus Cytosol Deep Learning Proteins Models, Molecular Molecular Weight
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In-Pero: Exploiting Deep Learning Embeddings of Protein Sequences to Predict the Localisation of Peroxisomal Proteins.

International journal of molecular sciences Jun 15, 2021
Peroxisomes are ubiquitous membrane-bound organelles, and aberrant localisation of peroxisomal proteins contributes to the pathogenesis of several disorders. Many computational methods focus on assigning protein sequences to subcellular compartments,...
Peroxisomes Mitochondrial Proteins Amino Acid Sequence Protein Transport Software Algorithms Deep Learning Reproducibility of Results Membrane Proteins
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Protein transfer learning improves identification of heat shock protein families.

PloS one May 18, 2021
Heat shock proteins (HSPs) play a pivotal role as molecular chaperones against unfavorable conditions. Although HSPs are of great importance, their computational identification remains a significant challenge. Previous studies have two major limitati...
Machine Learning Algorithms Humans Protein Transport Deep Learning Amino Acid Sequence Neural Networks, Computer Computational Biology Molecular Chaperones Heat-Shock Proteins
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DeepPred-SubMito: A Novel Submitochondrial Localization Predictor Based on Multi-Channel Convolutional Neural Network and Dataset Balancing Treatment.

International journal of molecular sciences Aug 9, 2020
Mitochondrial proteins are physiologically active in different compartments, and their abnormal location will trigger the pathogenesis of human mitochondrial pathologies. Correctly identifying submitochondrial locations can provide information for di...
Humans Neural Networks, Computer Mitochondrial Proteins Computational Biology Mitochondrial Membranes Mitochondria Algorithms Protein Transport Deep Learning
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autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences.

Journal of chemical information and modeling Aug 5, 2020
Deep learning has proven to be a powerful method with applications in various fields including image, language, and biomedical data. Thanks to the libraries and toolkits such as TensorFlow, PyTorch, and Keras, researchers can use different deep learn...
Deep Learning Protein Transport Neural Networks, Computer
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