AIMC Topic: Molecular Conformation

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From mundane to surprising nonadditivity: drivers and impact on ML models.

Journal of computer-aided molecular design Jul 25, 2024
Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information rich phenomenon. It can indicate conformational flexibility, structural rearrangements, and errors in assay results and structural ...
Humans Machine Learning Ligands Molecular Conformation Structure-Activity Relationship Drug Discovery
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Modeling Zinc Complexes Using Neural Networks.

Journal of chemical information and modeling Apr 8, 2024
Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build...
Neural Networks, Computer Thermodynamics Models, Molecular Molecular Dynamics Simulation Zinc Quantum Theory Coordination Complexes Molecular Conformation
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MCPNET: Development of an interpretable deep learning model based on multiple conformations of the compound for predicting developmental toxicity.

Computers in biology and medicine Feb 7, 2024
The development of deep learning models for predicting toxicological endpoints has shown great promise, but one of the challenges in the field is the accuracy and interpretability of these models. The bioactive conformation of a compound plays a crit...
Software Animals Machine Learning Molecular Conformation Zebrafish Deep Learning
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Combining Force Fields and Neural Networks for an Accurate Representation of Bonded Interactions.

The journal of physical chemistry. A Jan 17, 2024
We present a formalism of a neural network encoding bonded interactions in molecules. This intramolecular encoding is consistent with the models of intermolecular interactions previously designed by this group. Variants of the encoding fed into a cor...
Neural Networks, Computer Molecular Conformation Dipeptides
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Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets.

Journal of chemical information and modeling Oct 26, 2023
Small-molecule conformer generation (SMCG) is an extremely important task in both ligand- and structure-based computer-aided drug design, especially during the hit discovery phase. Recently, a multitude of artificial intelligence (AI) models tailored...
Molecular Conformation Ligands Drug Design Models, Molecular Artificial Intelligence
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Biomolecular NMR spectroscopy in the era of artificial intelligence.

Structure (London, England : 1993) Oct 16, 2023
Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in ac...
Molecular Conformation Nuclear Magnetic Resonance, Biomolecular Drug Discovery Reproducibility of Results Artificial Intelligence
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Learning on topological surface and geometric structure for 3D molecular generation.

Nature computational science Oct 9, 2023
Highly effective de novo design is a grand challenge of computer-aided drug discovery. Practical structure-specific three-dimensional molecule generations have started to emerge in recent years, but most approaches treat the target structure as a con...
Neural Networks, Computer Molecular Conformation Drug Discovery
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A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks.

Nature communications Aug 17, 2023
The organisation of the genome in nuclear space is an important frontier of biology. Chromosome conformation capture methods such as Hi-C and Micro-C produce genome-wide chromatin contact maps that provide rich data containing quantitative and qualit...
Neural Networks, Computer Molecular Conformation Chromatin Deep Learning
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Topology-Based and Conformation-Based Decoys Database: An Unbiased Online Database for Training and Benchmarking Machine-Learning Scoring Functions.

Journal of medicinal chemistry Jun 14, 2023
Machine-learning-based scoring functions (MLSFs) have gained attention for their potential to improve accuracy in binding affinity prediction and structure-based virtual screening (SBVS) compared to classical SFs. Developing accurate MLSFs for SBVS r...
Protein Binding Molecular Conformation Ligands Databases, Factual Machine Learning Molecular Docking Simulation
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Rapid Prediction of a Liquid Structure from a Single Molecular Configuration Using Deep Learning.

Journal of chemical information and modeling Jun 12, 2023
Molecular dynamics simulation is an indispensable tool for understanding the collective behavior of atoms and molecules and the phases they form. Statistical mechanics provides accurate routes for predicting macroscopic properties as time-averages ov...
Temperature Molecular Conformation Molecular Dynamics Simulation Deep Learning Neural Networks, Computer
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