AIMC Topic: Ligands

Clear Filters Showing 41 to 50 of 634 articles

CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Feb 6, 2025
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...
Neural Networks, Computer Machine Learning Drug Discovery Proteins Protein Binding Ligands Graph Neural Networks
View on PubMed DOI

Protein ligand structure prediction: From empirical to deep learning approaches.

Current opinion in structural biology Feb 5, 2025
Protein-ligand structure prediction methods, aiming to predict the three-dimensional complex structure and binding energy of a compound and target protein, are essential in many structure-based drug discovery pipelines, including virtual screening an...
Protein Conformation Models, Molecular Ligands Drug Discovery Protein Binding Computational Biology Deep Learning Proteins
View on PubMed DOI

The prediction of RNA-small-molecule ligand binding affinity based on geometric deep learning.

Computational biology and chemistry Jan 29, 2025
Small molecule-targeted RNA is an emerging technology that plays a pivotal role in drug discovery and inhibitor design, with widespread applications in disease treatment. Consequently, predicting RNA-small-molecule ligand interactions is crucial. Wit...
Small Molecule Libraries Ligands Deep Learning Binding Sites RNA
View on PubMed DOI

Transformer Decoder Learns from a Pretrained Protein Language Model to Generate Ligands with High Affinity.

Journal of chemical information and modeling Jan 27, 2025
The drug discovery process can be significantly accelerated by using deep learning methods to suggest molecules with druglike features and, more importantly, that are good candidates to bind specific proteins of interest. We present a novel deep lear...
Models, Molecular Ligands Drug Discovery Protein Binding Deep Learning Proteins
View on PubMed DOI

DisDock: A Deep Learning Method for Metal Ion-Protein Redocking.

Proteins Jan 22, 2025
The structures of metalloproteins are essential for comprehending their functions and interactions. The breakthrough of AlphaFold has made it possible to predict protein structures with experimental accuracy. However, the type of metal ion that a met...
Software Algorithms Binding Sites Metals Metalloproteins Ligands Protein Binding Molecular Docking Simulation Databases, Protein Protein Conformation Computational Biology Deep Learning Ions
View on PubMed DOI

Active Learning to Select the Most Suitable Reagents and One-Step Organic Chemistry Reactions for Prioritizing Target-Specific Hits from Ultralarge Chemical Spaces.

Journal of chemical information and modeling Jan 16, 2025
Designing chemically novel and synthesizable ligands from the largest possible chemical space is a major issue in modern drug discovery to identify early hits that are easily amenable to medicinal chemistry optimization. Starting from the sole three-...
Molecular Docking Simulation Drug Discovery Machine Learning Indicators and Reagents Proteins Ligands
View on PubMed DOI

Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Nature Jan 15, 2025
Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules. Despite recent advanc...
Proto-Oncogene Proteins c-bcl-2 Bridged Bicyclo Compounds, Heterocyclic Deep Learning Protein Binding Models, Molecular Humans Ligands Drug Design Proteins
View on PubMed DOI

Coverage bias in small molecule machine learning.

Nature communications Jan 9, 2025
Small molecule machine learning aims to predict chemical, biochemical, or biological properties from molecular structures, with applications such as toxicity prediction, ligand binding, and pharmacokinetics. A recent trend is developing end-to-end mo...
Molecular Structure Ligands Small Molecule Libraries Machine Learning Algorithms
View on PubMed DOI

CovCysPredictor: Predicting Selective Covalently Modifiable Cysteines Using Protein Structure and Interpretable Machine Learning.

Journal of chemical information and modeling Jan 8, 2025
Targeted covalent inhibition is a powerful therapeutic modality in the drug discoverer's toolbox. Recent advances in covalent drug discovery, in particular, targeting cysteines, have led to significant breakthroughs for traditionally challenging targ...
Databases, Protein Models, Molecular Ligands Drug Discovery Proteins Protein Conformation Cysteine Humans Machine Learning
View on PubMed DOI

Evaluation of Machine Learning/Molecular Mechanics End-State Corrections with Mechanical Embedding to Calculate Relative Protein-Ligand Binding Free Energies.

Journal of chemical theory and computation Jan 3, 2025
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several ti...
Machine Learning Protein Binding Proteins Ligands Thermodynamics Molecular Dynamics Simulation Quantum Theory
View on PubMed DOI
Popular Topics
Recent Journals