AIMC Topic: Molecular Conformation

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Benchmarking 3D Structure-Based Molecule Generators.

Journal of chemical information and modeling Jul 25, 2025
To understand the benefits and drawbacks of 3D combinatorial and deep learning generators, a novel benchmark was created focusing on the recreation of important protein-ligand interactions and 3D ligand conformations. Using the BindingMOAD data set w...
Deep Learning Proteins Ligands Molecular Conformation Benchmarking Models, Molecular
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Combination of Molecular Dynamics Simulations and Machine Learning Reveals Structural Characteristics of Stereochemistry-Specific Interdigitation of Synthetic Monomycoloyl Glycerol Analogs.

Journal of chemical information and modeling Jul 3, 2025
Synthetic monomycoloyl glycerol (MMG) analogs possess robust immunostimulatory activity and are investigated as adjuvants for subunit vaccines in preclinical and clinical studies. These synthetic lipids consist of a glycerol moiety attached to a cory...
Molecular Dynamics Simulation Molecular Conformation Machine Learning Stereoisomerism Thermodynamics Glycerol
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DCGCN: Dual-Channel Graph Convolutional Network-Based Drug-Target Interaction Prediction Method with 3D Molecular Structure.

Journal of chemical information and modeling Jul 2, 2025
Exploring drug-target interactions (DTIs) is crucial for drug discovery. Most existing methods for predicting DTIs rely solely on the linear structures of molecules, such as SMILES or the amino acid sequence. However, these linear features fail to re...
Molecular Conformation Drug Discovery Neural Networks, Computer Pharmaceutical Preparations Molecular Structure
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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...
Bayes Theorem Molecular Conformation Models, Molecular Cryoelectron Microscopy Computer Simulation Neural Networks, Computer Image Processing, Computer-Assisted Deep Learning
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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...
Diffusion Models, Molecular 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 Ligands Molecular Conformation Quantum Theory Machine Learning Density Functional Theory Pharmaceutical Preparations
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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 Molecular Dynamics Simulation Biological Products 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...
Molecular Dynamics Simulation Machine Learning Drug Discovery Diffusion Algorithms Molecular Conformation
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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...
Drug Discovery Molecular Dynamics Simulation Molecular Conformation Machine Learning
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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...
Models, Molecular Molecular Conformation Neural Networks, Computer Artificial Intelligence Ligands Drug Discovery
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