AIMC Topic: Nucleic Acid Conformation

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Deep generative design of RNA aptamers using structural predictions.

Nature computational science Nov 6, 2024
RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure...
Computer Simulation Deep Learning RNA Nucleic Acid Conformation Aptamers, Nucleotide Computational Biology
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Predicting RNA sequence-structure likelihood via structure-aware deep learning.

BMC bioinformatics Sep 30, 2024
BACKGROUND: The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many rese...
RNA Nucleic Acid Conformation Neural Networks, Computer Computational Biology Deep Learning Sequence Analysis, RNA
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Wfold: A new method for predicting RNA secondary structure with deep learning.

Computers in biology and medicine Sep 27, 2024
Precise estimations of RNA secondary structures have the potential to reveal the various roles that non-coding RNAs play in regulating cellular activity. However, the mainstay of traditional RNA secondary structure prediction methods relies on thermo...
Humans Software Sequence Analysis, RNA RNA Deep Learning Computational Biology Nucleic Acid Conformation
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RNAfcg: RNA Flexibility Prediction Based on Topological Centrality and Global Features.

Journal of chemical information and modeling Sep 14, 2024
The dynamics of RNAs are related intimately to their functions. Molecular flexibility, as a starting point for understanding their dynamics, has been utilized to predict many characteristics associated with their functions. Since the experimental mea...
Nucleic Acid Conformation Computational Biology RNA Machine Learning
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A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

Journal of chemical information and modeling Sep 12, 2024
The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence...
Nucleic Acid Conformation Machine Learning Small Molecule Libraries Models, Molecular RNA
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MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction.

IEEE journal of biomedical and health informatics Aug 6, 2024
This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-mo...
Binding Sites Small Molecule Libraries Ligands Nucleic Acid Conformation Algorithms Deep Learning Computational Biology RNA
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Exploring protein-mediated compaction of DNA by coarse-grained simulations and unsupervised learning.

Biophysical journal Jul 23, 2024
Protein-DNA interactions and protein-mediated DNA compaction play key roles in a range of biological processes. The length scales typically involved in DNA bending, bridging, looping, and compaction (≥1 kbp) are challenging to address experimentally ...
HIV Integrase Molecular Dynamics Simulation Nucleic Acid Conformation Unsupervised Machine Learning DNA Protein Binding
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Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.

mSystems Jul 2, 2024
UNLABELLED: The erythromycin resistance RNA methyltransferase () confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of is often induced by the macrolide-mediated rib...
Anti-Bacterial Agents Drug Resistance, Bacterial Bacterial Proteins Alleles Machine Learning Nucleic Acid Conformation Erythromycin Genetic Variation Methyltransferases
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Deep Learning for Elucidating Modifications to RNA-Status and Challenges Ahead.

Genes May 15, 2024
RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations al...
RNA-Binding Proteins RNA Deep Learning Humans RNA, Messenger Nucleic Acid Conformation
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DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

Journal of chemical information and modeling Apr 22, 2024
It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary ...
Models, Molecular Base Sequence Deep Learning Thermodynamics RNA Computational Biology Nucleic Acid Conformation
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