AIMC Topic: Binding Sites

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Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2.

Scientific reports Sep 30, 2024
Molecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based a...
Humans Protein Domains Protein Binding Molecular Dynamics Simulation Spike Glycoprotein, Coronavirus Mutation Angiotensin-Converting Enzyme 2 Binding Sites COVID-19 SARS-CoV-2 Deep Learning Protein Conformation
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Capture of RNA-binding proteins across mouse tissues using HARD-AP.

Nature communications Sep 28, 2024
RNA-binding proteins (RBPs) modulate all aspects of RNA metabolism, but a comprehensive picture of RBP expression across tissues is lacking. Here, we describe our development of the method we call HARD-AP that robustly retrieves RBPs and tightly asso...
RNA Binding Sites Protein Binding Mice RNA-Binding Proteins Machine Learning Animals Humans
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Development of a machine learning-based target-specific scoring function for structure-based binding affinity prediction for human dihydroorotate dehydrogenase inhibitors.

Journal of computational chemistry Sep 26, 2024
Human dihydroorotate dehydrogenase (hDHODH) is a flavin mononucleotide-dependent enzyme that can limit de novo pyrimidine synthesis, making it a therapeutic target for diseases such as autoimmune disorders and cancer. In this study, using the docking...
Enzyme Inhibitors Binding Sites Dihydroorotate Dehydrogenase Molecular Structure Molecular Dynamics Simulation Ligands Oxidoreductases Acting on CH-CH Group Donors Humans Machine Learning Molecular Docking Simulation Protein Binding
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Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.

Journal of chemical information and modeling Sep 16, 2024
Identifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Compet...
Protein Binding Proteins Molecular Dynamics Simulation Machine Learning Drug Discovery Ligands Protein Conformation Binding Sites
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DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Methods (San Diego, Calif.) Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Sequence Analysis, Protein Deep Learning DNA-Binding Proteins Protein Binding Neural Networks, Computer Databases, Protein Computational Biology Amino Acid Sequence Algorithms DNA Binding Sites Random Forest
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Predicting splicing patterns from the transcription factor binding sites in the promoter with deep learning.

BMC genomics Sep 3, 2024
BACKGROUND: Alternative splicing is a pivotal mechanism of post-transcriptional modification that contributes to the transcriptome plasticity and proteome diversity in metazoan cells. Although many splicing regulations around the exon/intron regions ...
Humans Deep Learning Binding Sites Exons Alternative Splicing Computational Biology Transcription Factors Promoter Regions, Genetic
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Deciphering the Language of Protein-DNA Interactions: A Deep Learning Approach Combining Contextual Embeddings and Multi-Scale Sequence Modeling.

Journal of molecular biology Aug 29, 2024
Deciphering the mechanisms governing protein-DNA interactions is crucial for understanding key cellular processes and disease pathways. In this work, we present a powerful deep learning approach that significantly advances the computational predictio...
Binding Sites Computational Biology DNA DNA-Binding Proteins Neural Networks, Computer Deep Learning Protein Binding
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Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure.

Journal of chemical information and modeling Aug 28, 2024
We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutati...
Machine Learning Molecular Structure Algorithms Binding Sites Ligands Protein Binding Small Molecule Libraries Protein Conformation Proteins Models, Molecular
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A Point Cloud Graph Neural Network for Protein-Ligand Binding Site Prediction.

International journal of molecular sciences Aug 27, 2024
Predicting protein-ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exp...
Databases, Protein Deep Learning Neural Networks, Computer Ligands Protein Binding Algorithms Binding Sites Proteins
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iCRBP-LKHA: Large convolutional kernel and hybrid channel-spatial attention for identifying circRNA-RBP interaction sites.

PLoS computational biology Aug 22, 2024
Circular RNAs (circRNAs) play vital roles in transcription and translation. Identification of circRNA-RBP (RNA-binding protein) interaction sites has become a fundamental step in molecular and cell biology. Deep learning (DL)-based methods have been ...
Deep Learning Computational Biology RNA-Binding Proteins Binding Sites RNA, Circular Humans Neural Networks, Computer Algorithms
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