AIMC Topic: Ligands

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Discovery of a Novel DCAF1 Ligand Using a Drug-Target Interaction Prediction Model: Generalizing Machine Learning to New Drug Targets.

Journal of chemical information and modeling Jun 23, 2023
DCAF1 functions as a substrate recruitment subunit for the RING-type CRL4 and the HECT family EDVP E3 ubiquitin ligases. The WDR domain of DCAF1 serves as a binding platform for substrate proteins and is also targeted by HIV and SIV lentiviral adapto...
Artificial Intelligence Machine Learning Ubiquitin-Protein Ligases Carrier Proteins Ligands
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Interaction of systemic drugs causing ocular toxicity with organic cation transporter: an artificial intelligence prediction.

Journal of biomolecular structure & dynamics Jun 20, 2023
Chronic disease patients (cancer, arthritis, cardiovascular diseases) undergo long-term systemic drug treatment. Membrane transporters in ocular barriers could falsely recognize these drugs and allow their trafficking into the eye from systemic circu...
Humans Artificial Intelligence Ligands Binding Sites Protein Binding Machine Learning Organic Cation Transport Proteins Molecular Dynamics Simulation Molecular Docking Simulation Organic Cation Transporter 1
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Leveraging Cell Painting Images to Expand the Applicability Domain and Actively Improve Deep Learning Quantitative Structure-Activity Relationship Models.

Chemical research in toxicology Jun 16, 2023
The search for chemical hit material is a lengthy and increasingly expensive drug discovery process. To improve it, ligand-based quantitative structure-activity relationship models have been broadly applied to optimize primary and secondary compound ...
Quantitative Structure-Activity Relationship Deep Learning Ligands Drug Discovery
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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...
Machine Learning Protein Binding Ligands Molecular Conformation Databases, Factual Molecular Docking Simulation
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Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.

Computers in biology and medicine Jun 12, 2023
BACKGROUND: Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.
Ligands Endothelial Cells Deep Learning Sequence Analysis, RNA Head and Neck Neoplasms Cell Communication Squamous Cell Carcinoma of Head and Neck Tumor Microenvironment Transcriptome Humans Melanoma
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DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein-Ligand Interaction Prediction.

Molecules (Basel, Switzerland) Jun 10, 2023
The core of large-scale drug virtual screening is to select the binders accurately and efficiently with high affinity from large libraries of small molecules in which non-binders are usually dominant. The binding affinity is significantly influenced ...
Protein Binding Neural Networks, Computer Proteins Ligands Drug Evaluation, Preclinical Protein Conformation
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GraphPLBR: Protein-Ligand Binding Residue Prediction With Deep Graph Convolution Network.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating dr...
Neural Networks, Computer Protein Binding Ligands Proteins Amino Acids
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Design of Nurr1 Agonists Fragment-Augmented Generative Deep Learning in Low-Data Regime.

Journal of medicinal chemistry May 31, 2023
Generative neural networks trained on SMILES can design innovative bioactive molecules . These so-called chemical language models (CLMs) have typically been trained on tens of template molecules for fine-tuning. However, it is challenging to apply CL...
Ligands Deep Learning Neural Networks, Computer Models, Chemical Drug Design
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The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

British journal of pharmacology May 26, 2023
The application of artificial intelligence (AI) approaches to drug discovery for G protein-coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding ou...
Drug Discovery Receptors, G-Protein-Coupled Ligands Machine Learning Animals Humans Artificial Intelligence
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Discovery of novel PARP-1 inhibitors using tandem studies: integrated docking, e-pharmacophore, deep learning based de novo and molecular dynamics simulation approach.

Journal of biomolecular structure & dynamics May 22, 2023
Cancer accounts for the majority of deaths worldwide, and the increasing incidence of breast cancer is a matter of grave concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as an attractive target for the treatment of breast cancer as it has...
Humans Deep Learning Artificial Intelligence Protein Binding Molecular Dynamics Simulation Poly(ADP-ribose) Polymerase Inhibitors Breast Neoplasms Poly (ADP-Ribose) Polymerase-1 Female Ligands Pharmacophore Molecular Docking Simulation
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