AIMC Topic: Protein Binding

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ProB-Site: Protein Binding Site Prediction Using Local Features.

Cells Jul 5, 2022
Protein-protein interactions (PPIs) are responsible for various essential biological processes. This information can help develop a new drug against diseases. Various experimental methods have been employed for this purpose; however, their applicatio...
Neural Networks, Computer Amino Acids Binding Sites Protein Binding Proteins
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AI-based prediction of new binding site and virtual screening for the discovery of novel P2X3 receptor antagonists.

European journal of medicinal chemistry Jul 1, 2022
Artificial intelligence (AI) has been recognized as a powerful technique that can accelerate drug discovery during the hit compound identification step. However, most simple deep learning models have been used for naive pre-filtering as the predictio...
Molecular Docking Simulation Drug Discovery Protein Binding Molecular Dynamics Simulation Artificial Intelligence Purinergic P2X Receptor Antagonists Ligands Binding Sites
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A Physics-Guided Neural Network for Predicting Protein-Ligand Binding Free Energy: From Host-Guest Systems to the PDBbind Database.

Biomolecules Jun 29, 2022
Calculation of protein-ligand binding affinity is a cornerstone of drug discovery. Classic implicit solvent models, which have been widely used to accomplish this task, lack accuracy compared to experimental references. Emerging data-driven models, o...
Thermodynamics Physics Ligands Solvents Proteins Neural Networks, Computer Protein Binding
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DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites.

BMC bioinformatics Jun 29, 2022
BACKGROUND: Addressing the laborious nature of traditional biological experiments by using an efficient computational approach to analyze RNA-binding proteins (RBPs) binding sites has always been a challenging task. RBPs play a vital role in post-tra...
Neural Networks, Computer Protein Binding Binding Sites RNA-Binding Proteins RNA
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GalaxyWater-CNN: Prediction of Water Positions on the Protein Structure by a 3D-Convolutional Neural Network.

Journal of chemical information and modeling Jun 24, 2022
Proteins interact with numerous water molecules to perform their physiological functions in biological organisms. Most water molecules act as solvent media; hence, their roles may be considered implicitly in theoretical treatments of protein structur...
Software Water Protein Binding Proteins Neural Networks, Computer
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Predicting Protein-Ligand Docking Structure with Graph Neural Network.

Journal of chemical information and modeling Jun 14, 2022
Modern day drug discovery is extremely expensive and time consuming. Although computational approaches help accelerate and decrease the cost of drug discovery, existing computational software packages for docking-based drug discovery suffer from both...
Proteins Ligands Molecular Docking Simulation Protein Binding Neural Networks, Computer
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Sfcnn: a novel scoring function based on 3D convolutional neural network for accurate and stable protein-ligand affinity prediction.

BMC bioinformatics Jun 8, 2022
BACKGROUND: Computer-aided drug design provides an effective method of identifying lead compounds. However, success rates are significantly bottlenecked by the lack of accurate and reliable scoring functions needed to evaluate binding affinities of p...
Neural Networks, Computer Machine Learning Protein Binding Proteins Ligands
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Characterizing collaborative transcription regulation with a graph-based deep learning approach.

PLoS computational biology Jun 6, 2022
Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulat...
Humans Transcription Factors DNA Deep Learning Protein Binding Chromatin Gene Expression Regulation Binding Sites
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ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction.

Nature methods May 30, 2022
Predicting the functional sites of a protein from its structure, such as the binding sites of small molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two classes of methods prevail: machine learning models built...
Binding Sites Deep Learning Protein Binding Spike Glycoprotein, Coronavirus Proteins COVID-19 SARS-CoV-2 Humans
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IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method.

Journal of chemical information and modeling May 24, 2022
The prediction and optimization of pharmacokinetic properties are essential in lead optimization. Traditional strategies mainly depend on the empirical chemical rules from medicinal chemists. However, with the rising amount of data, it is getting mor...
Deep Learning Protein Binding Humans Blood Proteins Chemistry, Pharmaceutical
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