AIMC Topic: Models, Molecular

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Evaluating native-like structures of RNA-protein complexes through the deep learning method.

Nature communications Feb 24, 2023
RNA-protein complexes underlie numerous cellular processes, including basic translation and gene regulation. The high-resolution structure determination of the RNA-protein complexes is essential for elucidating their functions. Therefore, computation...
Algorithms Molecular Docking Simulation RNA Protein Conformation Deep Learning Protein Binding Proteins Models, Molecular
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Integrating Molecular Models Into CryoEM Heterogeneity Analysis Using Scalable High-resolution Deep Gaussian Mixture Models.

Journal of molecular biology Feb 16, 2023
Resolving the structural variability of proteins is often key to understanding the structure-function relationship of those macromolecular machines. Single particle analysis using Cryogenic electron microscopy (CryoEM), combined with machine learning...
Cryoelectron Microscopy Neural Networks, Computer Algorithms Models, Molecular Microscopy, Electron
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Deep learning for reconstructing protein structures from cryo-EM density maps: Recent advances and future directions.

Current opinion in structural biology Feb 9, 2023
Cryo-Electron Microscopy (cryo-EM) has emerged as a key technology to determine the structure of proteins, particularly large protein complexes and assemblies in recent years. A key challenge in cryo-EM data analysis is to automatically reconstruct a...
Deep Learning Amino Acid Sequence Protein Conformation Cryoelectron Microscopy Proteins Models, Molecular
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Combining Group-Contribution Concept and Graph Neural Networks Toward Interpretable Molecular Property Models.

Journal of chemical information and modeling Jan 30, 2023
Quantitative structure-property relationships (QSPRs) are important tools to facilitate and accelerate the discovery of compounds with desired properties. While many QSPRs have been developed, they are associated with various shortcomings such as a l...
Machine Learning Models, Molecular Quantitative Structure-Activity Relationship Neural Networks, Computer
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Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps.

Journal of molecular biology Jan 18, 2023
The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been th...
Models, Molecular Macromolecular Substances Software Proteins Protein Conformation Cryoelectron Microscopy Artificial Intelligence
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3D Conformational Generative Models for Biological Structures Using Graph Information-Embedded Relative Coordinates.

Molecules (Basel, Switzerland) Dec 31, 2022
Developing molecular generative models for directly generating 3D conformation has recently become a hot research area. Here, an autoencoder based generative model was proposed for molecular conformation generation. A unique feature of our method is ...
Neural Networks, Computer Models, Molecular Ligands Protein Conformation
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Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Methods in enzymology Dec 8, 2022
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...
Epitopes X-Ray Diffraction Protein Conformation Cryoelectron Microscopy Proteins Models, Molecular Humans Deep Learning Scattering, Small Angle Proprotein Convertase 9 Antigen-Antibody Complex
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Exposing the Limitations of Molecular Machine Learning with Activity Cliffs.

Journal of chemical information and modeling Dec 1, 2022
Machine learning has become a crucial tool in drug discovery and chemistry at large, , to predict molecular properties, such as bioactivity, with high accuracy. However, activity cliffs─pairs of molecules that are highly similar in their structure bu...
Drug Discovery Structure-Activity Relationship Models, Molecular Machine Learning Algorithms
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Fast and accurate Ab Initio Protein structure prediction using deep learning potentials.

PLoS computational biology Sep 16, 2022
Despite the immense progress recently witnessed in protein structure prediction, the modeling accuracy for proteins that lack sequence and/or structure homologs remains to be improved. We developed an open-source program, DeepFold, which integrates s...
Protein Folding Proteins Databases, Protein Deep Learning Software Models, Molecular Computational Biology Algorithms Protein Conformation
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Hallucinating symmetric protein assemblies.

Science (New York, N.Y.) Sep 15, 2022
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-...
Models, Molecular Cryoelectron Microscopy Deep Learning Biocompatible Materials Protein Subunits Protein Conformation Protein Engineering
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