AIMC Topic: Amino Acid Sequence

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Cyclic peptide structure prediction and design using AlphaFold2.

Nature communications May 21, 2025
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here...
Proto-Oncogene Proteins c-mdm2 Kelch-Like ECH-Associated Protein 1 Crystallography, X-Ray Protein Conformation Deep Learning Computational Biology Models, Molecular Amino Acid Sequence Peptides, Cyclic Humans Drug Design
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Machine learning models for predicting configuration of modified knuckle epitope peptides of BMP-2 protein using mesoscale simulation data.

Physical chemistry chemical physics : PCCP Apr 30, 2025
The high doses of bone morphogenetic proteins (BMPs) cause undesired side effects in skeletal tissue regeneration. An alternative approach is to use the bioactive knuckle epitope domain of BMP-2 (BMP2-KEP) with an open-arm structure as part of the pr...
Bone Morphogenetic Protein 2 Amino Acid Sequence Quantitative Structure-Activity Relationship Peptides Models, Molecular Humans Epitopes Machine Learning
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Dynamics and Machine Learning Reveal the Link between Tripeptide Sequences and Evaporation-Driven Material Properties.

Nano letters Apr 27, 2025
Previous research showed that a peptide composed of three tyrosines (YYY) can turn into organic glass and cause strong adhesion between substrates via evaporation. However, the mechanisms of these processes remain unclear, and the exploration of appl...
Oligopeptides Hydrogen Bonding Dimethylpolysiloxanes Hydrophobic and Hydrophilic Interactions Surface Properties Molecular Dynamics Simulation Machine Learning Amino Acid Sequence Peptides Water
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Encoding and decoding selectivity and promiscuity in the human chemokine-GPCR interaction network.

Cell Apr 23, 2025
In humans, selective and promiscuous interactions between 46 secreted chemokine ligands and 23 cell surface chemokine receptors of the G-protein-coupled receptor (GPCR) family form a complex network to coordinate cell migration. While chemokines and ...
Chemokines Receptors, Chemokine Humans Protein Binding Receptors, G-Protein-Coupled Models, Molecular Amino Acid Sequence Ligands
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Neural network conditioned to produce thermophilic protein sequences can increase thermal stability.

Scientific reports Apr 23, 2025
This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 mill...
Neural Networks, Computer Temperature Animals Homeodomain Proteins Protein Stability Drosophila Proteins Transcription Factors Drosophila melanogaster Amino Acid Sequence
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Optimizing lipocalin sequence classification with ensemble deep learning models.

PloS one Apr 16, 2025
Deep learning (DL) has become a powerful tool for the recognition and classification of biological sequences. However, conventional single-architecture models often struggle with suboptimal predictive performance and high computational costs. To addr...
Lipocalins Deep Learning Humans Computational Biology Neural Networks, Computer Amino Acid Sequence
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Grain protein function prediction based on improved FCN and bidirectional LSTM.

Food chemistry Apr 4, 2025
With the development of high-throughput sequencing technologies, predicting grain protein function from amino acid sequences based on intelligent model has become one of the significant tasks in bioinformatics. The soybean, maize, indica, and japonic...
Neural Networks, Computer Computational Biology Zea mays Plant Proteins Glycine max Grain Proteins Amino Acids Edible Grain Amino Acid Sequence
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Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine Mar 30, 2025
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...
Humans Protein Binding Computational Biology Proteins Neural Networks, Computer Algorithms Deep Learning Protein Conformation Protein Interaction Mapping Sequence Analysis, Protein Databases, Protein Amino Acid Sequence
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Crystallography, X-Ray Protein Conformation Amino Acid Sequence Deep Learning Ligands Protein Binding Proteins Models, Molecular
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CPPCGM: A Highly Efficient Sequence-Based Tool for Simultaneously Identifying and Generating Cell-Penetrating Peptides.

Journal of chemical information and modeling Mar 19, 2025
Cell-penetrating peptides (CPPs) are usually short oligopeptides with 5-30 amino acid residues. CPPs have been proven as important drug delivery vehicles into cells through different mechanisms, demonstrating their potential as therapeutic candidates...
Humans Deep Learning Amino Acid Sequence Cell-Penetrating Peptides
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