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Ligands

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The Impact of Supervised Learning Methods in Ultralarge High-Throughput Docking.

Journal of chemical information and modeling Apr 10, 2023
Structure-based virtual screening methods are, nowadays, one of the key pillars of computational drug discovery. In recent years, a series of studies have reported docking-based virtual screening campaigns of large databases ranging from hundreds to ...
Machine Learning Ligands Drug Discovery Databases, Factual Supervised Machine Learning Molecular Docking Simulation
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Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Molecular diversity Apr 6, 2023
Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and neurodegeneration. The accumulation of tau protein into paired helical filaments is one of the major ...
Protein Binding Molecular Dynamics Simulation Humans Molecular Docking Simulation Ligands Drug Discovery Artificial Intelligence tau Proteins Computer Simulation Protein Aggregates Drug Evaluation, Preclinical Alzheimer Disease
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HAC-Net: A Hybrid Attention-Based Convolutional Neural Network for Highly Accurate Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Mar 29, 2023
Applying deep learning concepts from image detection and graph theory has greatly advanced protein-ligand binding affinity prediction, a challenge with enormous ramifications for both drug discovery and protein engineering. We build upon these advanc...
Neural Networks, Computer Proteins Software Ligands Protein Binding
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Deep Learning-Based Modeling of Drug-Target Interaction Prediction Incorporating Binding Site Information of Proteins.

Interdisciplinary sciences, computational life sciences Mar 26, 2023
Chemogenomics, also known as proteochemometrics, covers various computational methods for predicting interactions between related drugs and targets on large-scale data. Chemogenomics is used in the early stages of drug discovery to predict the off-ta...
Binding Sites Machine Learning Drug Discovery Proteins Deep Learning Ligands
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Artificial intelligence based virtual screening study for competitive and allosteric inhibitors of the SARS-CoV-2 main protease.

Journal of biomolecular structure & dynamics Mar 21, 2023
SARS-CoV-2 is a highly contagious and dangerous coronavirus that first appeared in late 2019 causing COVID-19, a pandemic of acute respiratory illnesses that is still a threat to health and the general public safety. We performed deep docking studies...
Molecular Docking Simulation Ligands Protease Inhibitors COVID-19 Humans SARS-CoV-2 Artificial Intelligence
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Deep Learning Model for Efficient Protein-Ligand Docking with Implicit Side-Chain Flexibility.

Journal of chemical information and modeling Mar 14, 2023
Protein-ligand docking is an essential tool in structure-based drug design with applications ranging from virtual high-throughput screening to pose prediction for lead optimization. Most docking programs for pose prediction are optimized for redockin...
Deep Learning Protein Binding Proteins Ligands Algorithms Molecular Docking Simulation Software
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Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures.

Journal of chemical information and modeling Mar 9, 2023
Machine learning-based protein structure prediction algorithms, such as RosettaFold and AlphaFold2, have greatly impacted the structural biology field, arousing a fair amount of discussion around their potential role in drug discovery. While there ar...
Deep Learning Protein Binding Algorithms Molecular Docking Simulation Protein Conformation Proteins Ligands
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GPCRLigNet: rapid screening for GPCR active ligands using machine learning.

Journal of computer-aided molecular design Feb 25, 2023
Molecules with bioactivity towards G protein-coupled receptors represent a subset of the vast space of small drug-like molecules. Here, we compare machine learning models, including dilated graph convolutional networks, that conduct binary classifica...
Ligands High-Throughput Screening Assays Molecular Docking Simulation Receptors, G-Protein-Coupled Machine Learning
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Structure-based drug design with geometric deep learning.

Current opinion in structural biology Feb 24, 2023
Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric deep learning, an emerging concept of neural-network-based machine learning, has be...
Drug Discovery Deep Learning Machine Learning Drug Design Ligands Neural Networks, Computer
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Geometric Interaction Graph Neural Network for Predicting Protein-Ligand Binding Affinities from 3D Structures (GIGN).

The journal of physical chemistry letters Feb 16, 2023
Predicting protein-ligand binding affinities (PLAs) is a core problem in drug discovery. Recent advances have shown great potential in applying machine learning (ML) for PLA prediction. However, most of them omit the 3D structures of complexes and ph...
Protein Binding Proteins Ligands Neural Networks, Computer Machine Learning
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