AIMC Topic: Protein Binding

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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...
Protein Binding Computational Biology Transcription Factors DNA Binding Sites Chromatin Immunoprecipitation Sequencing Software Algorithms Convolutional Neural Networks Neural Networks, Computer
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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...
Protein Binding Phosphatidylinositol 3-Kinases Molecular Dynamics Simulation Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Machine Learning Molecular Docking Simulation Drug Discovery Humans Pharmacophore
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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...
Ligands Metalloproteins Machine Learning 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...
Humans Algorithms Drug Discovery Computational Biology Proteins Pharmaceutical Preparations Deep Learning Protein Binding
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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...
Humans Ligands Deep Learning Computational Biology Protein Binding Databases, Protein Receptors, G-Protein-Coupled
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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...
Binding Sites Directed Molecular Evolution Deep Learning Protein Binding Models, Molecular Neural Networks, Computer Amino Acid Sequence Ligands Carboxylic Ester Hydrolases
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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...
Neural Networks, Computer Machine Learning Drug Discovery Protein Binding Proteins Ligands
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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 ...
Machine Learning Algorithms Protein Binding Neural Networks, Computer Models, Molecular Ligands Binding Sites Computational Biology Proteins Databases, Protein
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OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

Frontiers in immunology Feb 28, 2025
The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop a novel machine learning framework for predicting antigen peptide presentation by MHC Class I and I...
Cancer Vaccines Histocompatibility Antigens Class II Female Vaccine Development Antigen Presentation Peptides Humans Protein Binding Machine Learning Antigens, Neoplasm Histocompatibility Antigens Class I Endometrial Neoplasms
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Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Cell genomics Feb 27, 2025
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
Humans Animals Deep Learning Binding Sites Protein Binding SOX9 Transcription Factor Chromatin Mice Nucleosomes Transcription Factors
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