AIMC Topic: Ligands

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A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening.

Journal of chemical information and modeling May 11, 2023
Over the past few years, many machine learning-based scoring functions for predicting the binding of small molecules to proteins have been developed. Their objective is to approximate the distribution which takes two molecules as input and outputs th...
Machine Learning Proteins Databases, Protein Ligands Molecular Docking Simulation Protein Binding
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Exploiting conformational dynamics to modulate the function of designed proteins.

Proceedings of the National Academy of Sciences of the United States of America Apr 24, 2023
With the recent success in calculating protein structures from amino acid sequences using artificial intelligence-based algorithms, an important next step is to decipher how dynamics is encoded by the primary protein sequence so as to better predict ...
Ligands Protein Conformation Artificial Intelligence Peptides Proteins Amino Acid Sequence
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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 Databases, Factual Supervised Machine Learning Ligands Molecular Docking Simulation Drug Discovery
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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 ...
Humans Protein Aggregates Protein Binding Ligands Molecular Dynamics Simulation tau Proteins Drug Evaluation, Preclinical Alzheimer Disease Molecular Docking Simulation Drug Discovery Artificial Intelligence Computer Simulation
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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...
Ligands Protein Binding Neural Networks, Computer Proteins Software
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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...
Proteins Ligands Binding Sites Drug Discovery Deep Learning Machine Learning
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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 COVID-19 Protease Inhibitors Humans Ligands 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...
Software Proteins Ligands Deep Learning Protein Binding Algorithms Molecular Docking Simulation
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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...
Ligands Protein Conformation Protein Binding Proteins Molecular Docking Simulation Deep Learning Algorithms
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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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