AIMC Topic: Models, Molecular

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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...
Amino Acid Sequence Quantitative Structure-Activity Relationship Bone Morphogenetic Protein 2 Models, Molecular Epitopes Machine Learning Peptides Humans
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Artificial intelligence for RNA-ligand interaction prediction: advances and prospects.

Drug discovery today Apr 24, 2025
Accurate prediction of RNA-ligand interactions is vital for understanding biological processes and advancing RNA-targeted drug discovery. Given their complexity, artificial intelligence (AI) is revolutionizing the study of RNA-ligand interactions, of...
Binding Sites Humans Artificial Intelligence RNA Drug Discovery Models, Molecular Ligands
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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 ...
Protein Binding Receptors, G-Protein-Coupled Ligands Humans Chemokines Receptors, Chemokine Models, Molecular Amino Acid Sequence
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A hybrid variational autoencoder and WGAN with gradient penalty for tertiary protein structure generation.

Scientific reports Apr 23, 2025
Elucidating the tertiary structure of proteins is important for understanding their functions and interactions. While deep neural networks have advanced the prediction of a protein's native structure from its amino acid sequence, the focus on a singl...
Proteins Models, Molecular Protein Structure, Tertiary Autoencoder Deep Learning Computational Biology Neural Networks, Computer Algorithms
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The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

International journal of biological macromolecules Apr 21, 2025
Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the ...
Models, Molecular RNA Ligands Deep Learning Computational Biology Small Molecule Libraries Nucleic Acid Conformation Binding Sites
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Emerging frontiers in protein structure prediction following the AlphaFold revolution.

Journal of the Royal Society, Interface Apr 16, 2025
Models of protein structures enable molecular understanding of biological processes. Current protein structure prediction tools lie at the interface of biology, chemistry and computer science. Millions of protein structure models have been generated ...
Proteins Models, Molecular Deep Learning Computational Biology Protein Conformation Protein Folding
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Crystal Structure Prediction Using a Self-Attention Neural Network and Semantic Segmentation.

Journal of chemical information and modeling Apr 14, 2025
The development of new materials is a time-consuming and resource-intensive process. Deep learning has emerged as a promising approach to accelerate this process. However, accurately predicting crystal structures using deep learning remains a signifi...
Neural Networks, Computer Semantics Deep Learning Crystallography, X-Ray Models, Molecular
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Deep learning tools predict variants in disordered regions with lower sensitivity.

BMC genomics Apr 12, 2025
BACKGROUND: The recent AI breakthrough of AlphaFold2 has revolutionized 3D protein structural modeling, proving crucial for protein design and variant effects prediction. However, intrinsically disordered regions-known for their lack of well-defined ...
Computational Biology Proteome Models, Molecular Mutation Humans Deep Learning Protein Conformation, alpha-Helical Intrinsically Disordered Proteins Methionine
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Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem.

Journal of chemical information and modeling Apr 8, 2025
Deep learning has revolutionized difficult tasks in chemistry and biology, yet existing language models often treat these domains separately, relying on concatenated architectures and independently pretrained weights. These approaches fail to fully e...
Deep Learning Computational Biology Models, Molecular Proteins Drug Discovery
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A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning.

Journal of chemical information and modeling Apr 2, 2025
Kinases are critical regulators in numerous cellular processes, and their dysregulation is linked to various diseases, including cancer. Thus, protein kinases have emerged as major drug targets at present, with approximately a quarter to a third of g...
Protein Kinases Protein Kinase Inhibitors Deep Learning Models, Molecular Drug Design
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