AIMC Topic: Protein Binding

Clear Filters Showing 771 to 780 of 954 articles

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Journal of biomolecular structure & dynamics May 1, 2025
Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifical...
Drug Approval Inflammasomes Humans United States Food and Drug Administration Machine Learning Molecular Docking Simulation Drug Repositioning NLR Family, Pyrin Domain-Containing 3 Protein Molecular Dynamics Simulation Protein Binding Inflammation United States
View on PubMed DOI

Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Journal of biomolecular structure & dynamics May 1, 2025
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
Protein Kinase Inhibitors T-Lymphocytes Humans Thermodynamics Molecular Docking Simulation Protein Binding Machine Learning Protein Serine-Threonine Kinases Drug Discovery Signal Transduction Structure-Activity Relationship Molecular Dynamics Simulation
View on PubMed DOI

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...
Protein Kinase C Humans Protein Binding Machine Learning Ligands Enzyme Activation
View on PubMed DOI

Deep learning in GPCR drug discovery: benchmarking the path to accurate peptide binding.

Briefings in bioinformatics Mar 4, 2025
Deep learning (DL) methods have drastically advanced structure-based drug discovery by directly predicting protein structures from sequences. Recently, these methods have become increasingly accurate in predicting complexes formed by multiple protein...
Humans Peptides Ligands Protein Binding Drug Discovery Receptors, G-Protein-Coupled Benchmarking Deep Learning
View on PubMed DOI

ParaSurf: a surface-based deep learning approach for paratope-antigen interaction prediction.

Bioinformatics (Oxford, England) Feb 4, 2025
MOTIVATION: Identifying antibody binding sites, is crucial for developing vaccines and therapeutic antibodies, processes that are time-consuming and costly. Accurate prediction of the paratope's binding site can speed up the development by improving ...
Software Deep Learning Protein Binding Binding Sites, Antibody Computational Biology Models, Molecular Antigens
View on PubMed DOI

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data.

Nucleic acids research Jan 6, 2025
BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, trai...
Binding Sites Small Molecule Libraries Protein Binding Proteins Databases, Protein Internet Knowledge Bases Humans
View on PubMed DOI

CGPDTA: An Explainable Transfer Learning-Based Predictor With Molecule Substructure Graph for Drug-Target Binding Affinity.

Journal of computational chemistry Jan 5, 2025
Identifying interactions between drugs and targets is crucial for drug discovery and development. Nevertheless, the determination of drug-target binding affinities (DTAs) through traditional experimental methods is a time-consuming process. Conventio...
Molecular Structure Pharmaceutical Preparations Protein Binding Proteins Drug Discovery Deep Learning
View on PubMed DOI

iProtDNA-SMOTE: Enhancing protein-DNA binding sites prediction through imbalanced graph neural networks.

PloS one Jan 1, 2025
Protein-DNA interactions play a crucial role in cellular biology, essential for maintaining life processes and regulating cellular functions. We propose a method called iProtDNA-SMOTE, which utilizes non-equilibrium graph neural networks along with p...
Software Algorithms Protein Binding Neural Networks, Computer DNA-Binding Proteins Binding Sites Graph Neural Networks Computational Biology Databases, Protein DNA
View on PubMed DOI

Structure-Based Prediction of lncRNA-Protein Interactions by Deep Learning.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
The interactions between long noncoding RNA (lncRNA) and protein play crucial roles in various biological processes. Computational methods are essential for predicting lncRNA-protein interactions and deciphering their mechanisms. In this chapter, we ...
Software Humans Protein Binding Deep Learning RNA, Long Noncoding Neural Networks, Computer Computational Biology Proteins RNA-Binding Proteins
View on PubMed DOI

SG-ML-PLAP: A structure-guided machine learning-based scoring function for protein-ligand binding affinity prediction.

Protein science : a publication of the Protein Society Jan 1, 2025
Computational methods to predict binding affinity of protein-ligand complex have been used extensively to design inhibitors for proteins selected as drug targets. In recent years machine learning (ML) is being increasingly used for design of drugs/in...
Protein Binding Machine Learning Proteins Software Databases, Protein Molecular Docking Simulation Ligands
View on PubMed DOI
Popular Topics
Recent Journals