AIMC Topic: Protein Binding

Clear Filters Showing 151 to 160 of 954 articles

Evaluations of the Perturbation Resistance of the Deep-Learning-Based Ligand Conformation Optimization Algorithm.

Journal of chemical information and modeling Dec 26, 2024
In recent years, the deep learning (DL) technique has rapidly developed and shown great success in scoring the protein-ligand binding affinities. The protein-ligand conformation optimization based on DL-derived scoring functions holds broad applicati...
Algorithms Deep Learning Protein Binding Molecular Docking Simulation Protein Conformation Proteins Ligands
View on PubMed DOI

Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Molecules (Basel, Switzerland) Dec 24, 2024
The src-homology 2 domain-containing phosphatase 2 (SHP2) is a human cytoplasmic protein tyrosine phosphatase that plays a crucial role in cellular signal transduction. Aberrant activation and mutations of SHP2 are associated with tumor growth and im...
Protein Tyrosine Phosphatase, Non-Receptor Type 11 Enzyme Inhibitors Protein Conformation Allosteric Regulation Protein Binding Molecular Dynamics Simulation Humans Machine Learning
View on PubMed DOI

Identification of STAT3 phosphorylation inhibitors using generative deep learning, virtual screening, molecular dynamics simulations, and biological evaluation for non-small cell lung cancer therapy.

Molecular diversity Dec 23, 2024
The development of phosphorylation-suppressing inhibitors targeting Signal Transducer and Activator of Transcription 3 (STAT3) represents a promising therapeutic strategy for non-small cell lung cancer (NSCLC). In this study, a generative model was d...
Binding Sites Molecular Dynamics Simulation Cell Line, Tumor STAT3 Transcription Factor Carcinoma, Non-Small-Cell Lung Humans Protein Binding Antineoplastic Agents Lung Neoplasms Molecular Docking Simulation Phosphorylation Deep Learning
View on PubMed DOI

A 4D tensor-enhanced multi-dimensional convolutional neural network for accurate prediction of protein-ligand binding affinity.

Molecular diversity Dec 23, 2024
Protein-ligand interactions are the molecular basis of many important cellular activities, such as gene regulation, cell metabolism, and signal transduction. Protein-ligand binding affinity is a crucial metric of the strength of the interaction betwe...
Neural Networks, Computer Deep Learning Models, Molecular Ligands Protein Binding Binding Sites Convolutional Neural Networks Proteins
View on PubMed DOI

Geometric deep learning improves generalizability of MHC-bound peptide predictions.

Communications biology Dec 19, 2024
The interaction between peptides and major histocompatibility complex (MHC) molecules is pivotal in autoimmunity, pathogen recognition and tumor immunity. Recent advances in cancer immunotherapies demand for more accurate computational prediction of ...
Deep Learning Humans Protein Binding Major Histocompatibility Complex Computational Biology Peptides
View on PubMed DOI

An integrated machine learning approach delineates an entropic expansion mechanism for the binding of a small molecule to α-synuclein.

eLife Dec 18, 2024
The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as α-synuclein (αS) underlie the pathogenesis of various neurodegenerative disorders. However, targeting αS with small molecules faces challenges due to the lack of defi...
Thermodynamics Entropy 1-(5-Isoquinolinesulfonyl)-2-Methylpiperazine alpha-Synuclein Intrinsically Disordered Proteins Machine Learning Protein Conformation Protein Binding Humans
View on PubMed DOI

Improving binding affinity prediction by emphasizing local features of drug and protein.

Computational biology and chemistry Dec 11, 2024
Binding affinity prediction has been considered as a fundamental task in drug discovery. Despite much effort to improve accuracy of binding affinity prediction, the prior work considered only macro-level features that can represent the characteristic...
Pharmaceutical Preparations Protein Binding Proteins Drug Discovery Deep Learning
View on PubMed DOI

Docking-Informed Machine Learning for Kinome-wide Affinity Prediction.

Journal of chemical information and modeling Dec 10, 2024
Kinase inhibitors are an important class of anticancer drugs, with 80 inhibitors clinically approved and >100 in active clinical testing. Most bind competitively in the ATP-binding site, leading to challenges with selectivity for a specific kinase, r...
Humans Machine Learning Protein Kinases Protein Conformation Protein Kinase Inhibitors Molecular Docking Simulation Protein Binding Binding Sites
View on PubMed DOI

MMD-DTA: A Multi-Modal Deep Learning Framework for Drug-Target Binding Affinity and Binding Region Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The prediction of drug-target affinity (DTA) plays a crucial role in drug development and the identification of potential drug targets. In recent years, computer-assisted DTA prediction has emerged as a significant approach in this field. In this stu...
Computational Biology Proteins Pharmaceutical Preparations Binding Sites Humans Deep Learning Drug Discovery Neural Networks, Computer Protein Binding
View on PubMed DOI

Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Protein Binding Binding Sites Databases, Protein Machine Learning Computational Biology Neural Networks, Computer Ligands Algorithms Proteins
View on PubMed DOI
Popular Topics
Recent Journals