AIMC Topic: Protein Binding

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Binding mechanism of inhibitors to DFG-in and DFG-out P38α deciphered using multiple independent Gaussian accelerated molecular dynamics simulations and deep learning.

SAR and QSAR in environmental research Mar 20, 2025
P38α has been identified as a key target for drug design to treat a wide range of diseases. In this study, multiple independent Gaussian accelerated molecular dynamics (GaMD) simulations, deep learning (DL), and the molecular mechanics generalized Bo...
Drug Design Molecular Dynamics Simulation Deep Learning Quantitative Structure-Activity Relationship Protein Binding Mitogen-Activated Protein Kinase 14
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Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques.

Experimental biology and medicine (Maywood, N.J.) Mar 19, 2025
Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overd...
Receptors, Opioid, mu Ligands Structure-Activity Relationship Humans Protein Binding Analgesics, Opioid Deep Learning Machine Learning Support Vector Machine
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CacPred: a cascaded convolutional neural network for TF-DNA binding prediction.

BMC genomics Mar 18, 2025
BACKGROUND: Transcription factors (TFs) regulate the genes' expression by binding to DNA sequences. Aligned TFBSs of the same TF are seen as cis-regulatory motifs, and substantial computational efforts have been invested to find motifs. In recent yea...
Chromatin Immunoprecipitation Sequencing Transcription Factors DNA Binding Sites Protein Binding Neural Networks, Computer Algorithms Computational Biology Software Convolutional Neural Networks
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Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Journal of molecular graphics & modelling Mar 15, 2025
PI3KC2α is a lipid kinase associated with cancer metastasis and thrombosis. In this study, we present a novel computational workflow integrating structure-based pharmacophore modeling, machine learning (ML), and molecular dynamics (MD) simulations to...
Pharmacophore Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Molecular Docking Simulation Drug Discovery Humans Protein Binding Machine Learning
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Join Persistent Homology (JPH)-Based Machine Learning for Metalloprotein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Mar 13, 2025
With the crucial role of metalloproteins in respiration, oxidative stress protection, photosynthesis, and drug metabolism, the design and discovery of drugs that can target metalloproteins are extremely important. Recently, enormous potential has bee...
Machine Learning Ligands Metalloproteins Protein Binding
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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Drug Discovery Deep Learning Protein Binding Humans Algorithms Pharmaceutical Preparations Computational Biology Proteins
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TrGPCR: GPCR-Ligand Binding Affinity Prediction Based on Dynamic Deep Transfer Learning.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting G protein-coupled receptor (GPCR) -ligand binding affinity plays a crucial role in drug development. However, determining GPCR-ligand binding affinities is time-consuming and resource-intensive. Although many studies used data-driven metho...
Protein Binding Computational Biology Receptors, G-Protein-Coupled Ligands Humans Databases, Protein Deep Learning
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Development of DeepPQK and DeepQK sequence-based deep learning models to predict protein-ligand affinity and application in the directed evolution of ferulic esterase DLfae4.

International journal of biological macromolecules Mar 5, 2025
Affinity plays an essential role in the rate and stability of enzyme-catalyzed reactions, thus directly impacting the catalytic activity. In general, the predictive method for protein-ligand binding affinity mainly relies on high-resolution protein c...
Ligands Carboxylic Ester Hydrolases Directed Molecular Evolution Binding Sites Protein Binding Models, Molecular Amino Acid Sequence Neural Networks, Computer Deep Learning
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iScore: A ML-Based Scoring Function for De Novo Drug Discovery.

Journal of chemical information and modeling Mar 4, 2025
In the quest for accelerating de novo drug discovery, the development of efficient and accurate scoring functions represents a fundamental challenge. This study introduces iScore, a novel machine learning (ML)-based scoring function designed to predi...
Protein Binding Proteins Ligands Machine Learning Drug Discovery Neural Networks, Computer
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Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins Feb 28, 2025
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...
Algorithms Protein Binding Computational Biology Neural Networks, Computer Machine Learning Models, Molecular Ligands Binding Sites Proteins Databases, Protein
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