AIMC Topic: Molecular Conformation

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Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.

Proceedings of the National Academy of Sciences of the United States of America Jun 4, 2025
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...
Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Computer Simulation Molecular Conformation Cryoelectron Microscopy Models, Molecular Bayes Theorem
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DihedralsDiff: A Diffusion Conformation Generation Model That Unifies Local and Global Molecular Structures.

Journal of chemical information and modeling May 20, 2025
Significant advancements have been made in utilizing artificial intelligence to learn to generate molecular conformations, which has greatly facilitated the discovery of drug molecules. In particular, the rapid development of diffusion models has led...
Models, Molecular Diffusion Molecular Conformation
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Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods.

Chemphyschem : a European journal of chemical physics and physical chemistry Feb 27, 2025
Accurate and efficient prediction of high energy ligand conformations is important in structure-based drug discovery for the exclusion of unrealistic structures in docking-based virtual screening and de novo design approaches. In this work, we constr...
Thermodynamics Pharmaceutical Preparations Quantum Theory Ligands Molecular Conformation Machine Learning Density Functional Theory
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Accurate Prediction of ωB97X-D/6-31G* Equilibrium Geometries from a Neural Net Starting from Merck Molecular Force Field (MMFF) Molecular Mechanics Geometries.

Journal of chemical information and modeling Feb 17, 2025
Starting from Merck Molecular Force Field (MMFF) geometries, a neural-net based model has been formulated to closely reproduce ωB97X-D/6-31G* equilibrium geometries for organic molecules. The model involves training to >6 million energy and force cal...
Neural Networks, Computer Biological Products Molecular Dynamics Simulation Molecular Conformation
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AGDIFF: Attention-Enhanced Diffusion for Molecular Geometry Prediction.

Journal of chemical information and modeling Feb 11, 2025
Accurate prediction of molecular geometries is crucial for drug discovery and materials science. Existing fast conformer prediction algorithms often rely on approximate empirical energy functions, resulting in low accuracy. More accurate methods like...
Machine Learning Algorithms Molecular Conformation Molecular Dynamics Simulation Diffusion Drug Discovery
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ConfRank: Improving GFN-FF Conformer Ranking with Pairwise Training.

Journal of chemical information and modeling Nov 20, 2024
Conformer ranking is a crucial task for drug discovery, with methods for generating conformers often based on molecular (meta)dynamics or sophisticated sampling techniques. These methods are constrained by the underlying force computation regarding r...
Molecular Conformation Machine Learning Drug Discovery Molecular Dynamics Simulation
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Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 29, 2024
The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, and is an essential module applied across a wide range of artificial intelligence-driven drug discovery scenarios. Ho...
Neural Networks, Computer Models, Molecular Ligands Artificial Intelligence Molecular Conformation Drug Discovery
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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 ...
Molecular Conformation Machine Learning Humans Structure-Activity Relationship Drug Discovery Ligands
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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...
Models, Molecular Molecular Dynamics Simulation Zinc Coordination Complexes Thermodynamics Neural Networks, Computer Quantum Theory 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...
Deep Learning Software Zebrafish Animals Machine Learning Molecular Conformation
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