AIMC Topic: Ligands

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High-Throughput Ligand Dissociation Kinetics Predictions Using Site Identification by Ligand Competitive Saturation.

Journal of chemical theory and computation May 13, 2025
The dissociation or off rate, , of a drug molecule has been shown to be more relevant to efficacy than affinity for selected systems, motivating the development of predictive computational methodologies. These are largely based on enhanced-sampling m...
Molecular Dynamics Simulation Ligands Thermodynamics Proteins Kinetics Machine Learning
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PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks.

Journal of chemical information and modeling May 12, 2025
This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model relies on a recurrent neural network that was trained to decode embedded molecular fingerprints into SMI...
Ligands Small Molecule Libraries Receptors, Dopamine D2 Drug Design Bayes Theorem Recurrent Neural Networks Neural Networks, Computer
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A Database for Large-Scale Docking and Experimental Results.

Journal of chemical information and modeling May 12, 2025
The rapid expansion of readily accessible compounds over the past six years has transformed molecular docking, improving hit rates and affinities. While many millions of molecules may score well in a docking campaign, the results are rarely fully sha...
Proteins Ligands Small Molecule Libraries Machine Learning Databases, Factual Molecular Docking Simulation
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Data-Driven Insights into Porphyrin Geometry: Interpretable AI for Non-Planarity and Aromaticity Analyses.

Journal of chemical information and modeling May 12, 2025
Porphyrins are involved in numerous and very different chemical and biological processes, due to the sensitivity of their application-relevant properties to subtle structural changes. Applying modern machine learning methodology is very appealing for...
Machine Learning Structure-Activity Relationship Ligands Models, Molecular Porphyrins
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Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening.

Molecules (Basel, Switzerland) May 8, 2025
Butyrylcholinesterase (BChE), plays a critical role in alleviating the symptoms of Alzheimer's disease (AD) by regulating acetylcholine levels, emerging as an attractive target for AD treatment. This study employed a quantitative structure-activity r...
Cholinesterase Inhibitors Quantitative Structure-Activity Relationship Butyrylcholinesterase Alzheimer Disease Ligands Drug Discovery Protein Binding Molecular Dynamics Simulation Neuroprotective Agents Humans Machine Learning Drug Evaluation, Preclinical Molecular Docking Simulation
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Deep Eutectic Solvent Extraction Assisted Ligand Affinity Assay for α-Glucosidase Inhibitors Screening From the Plasma of Rats Administrated Pueraria lobata Extracts.

Journal of separation science May 1, 2025
In this work, for the first time, a deep eutectic solvent assisted ligand affinity assay was proposed. Several critical parameters affecting the analysis performance were investigated and the optimized DES extract conditions were as follows: the solu...
Plant Extracts Isoflavones Deep Eutectic Solvents Rats Pueraria Rats, Sprague-Dawley alpha-Glucosidases Animals Glycoside Hydrolase Inhibitors Male Drugs, Chinese Herbal Ligands
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Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency.

PLoS computational biology May 1, 2025
With a burgeoning number of artificial intelligence (AI) applications in various fields, biomolecular science has also given a big welcome to advanced AI techniques in recent years. In this broad field, scoring a protein-ligand binding structure to o...
Proteins Models, Molecular Deep Learning Protein Conformation Algorithms Binding Sites Protein Binding Drug Discovery Computational Biology Ligands
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Validation of machine learning-assisted screening of PKC ligands: PKC binding affinity and activation.

Bioscience, biotechnology, and biochemistry Apr 22, 2025
Protein kinase C (PKC) is a family of serine/threonine kinases, and PKC ligands have the potential to be therapeutic seeds for cancer, Alzheimer's disease, and human immunodeficiency virus infection. However, in addition to desired therapeutic effect...
Machine Learning Protein Binding Ligands Humans Enzyme Activation Protein Kinase C
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DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning.

Nucleic acids research Mar 20, 2025
Ribonucleic Acid (RNA) is the central conduit for information transfer in the cell. Identifying potential RNA targets in disease conditions is a challenging task, given the vast repertoire of functional non-coding RNAs in a human cell. A potential dr...
Nucleic Acid Conformation Binding Sites Software Algorithms RNA Ligands Molecular Docking Simulation Humans Machine Learning
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Increase Docking Score Screening Power by Simple Fusion With CNNscore.

Journal of computational chemistry Mar 5, 2025
Scoring functions (SFs) of molecular docking is a vital component of structure-based virtual screening (SBVS). Traditional SFs yield their inherent shortage for idealized approximations and simplifications predicting the binding affinity. Complementa...
Deep Learning Drug Evaluation, Preclinical Protein Kinase Inhibitors Ligands Humans Neural Networks, Computer Molecular Docking Simulation
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