AIMC Topic: Ligands

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DeepLPI: a novel deep learning-based model for protein-ligand interaction prediction for drug repurposing.

Scientific reports Oct 28, 2022
The substantial cost of new drug research and development has consistently posed a huge burden for both pharmaceutical companies and patients. In order to lower the expenditure and development failure rate, repurposing existing and approved drugs by ...
Ligands COVID-19 Drug Treatment Humans Neural Networks, Computer Deep Learning Drug Repositioning
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Computational model of the full-length TSH receptor.

eLife Oct 28, 2022
(GPCR)The receptor for TSH receptor (TSHR), a G protein coupled receptor (GPCR), is of particular interest as the primary antigen in autoimmune hyperthyroidism (Graves' disease) caused by stimulating TSHR antibodies. To date, only one domain of the e...
Artificial Intelligence Receptors, G-Protein-Coupled Ligands Leucine Thyrotropin Autoantibodies Receptors, Thyrotropin
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Assessment of the Generalization Abilities of Machine-Learning Scoring Functions for Structure-Based Virtual Screening.

Journal of chemical information and modeling Oct 21, 2022
In structure-based virtual screening (SBVS), it is critical that scoring functions capture protein-ligand atomic interactions. By focusing on the local domains of ligand binding pockets, a standardized pocket Pfam-based clustering (Pfam-cluster) appr...
Cluster Analysis Machine Learning Proteins Protein Binding Ligands
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Predicting Regioselectivity of AO, CYP, FMO, and UGT Metabolism Using Quantum Mechanical Simulations and Machine Learning.

Journal of medicinal chemistry Oct 14, 2022
Unexpected metabolism in modification and conjugation phases can lead to the failure of many late-stage drug candidates or even withdrawal of approved drugs. Thus, it is critical to predict the sites of metabolism (SoM) for enzymes, which interact wi...
Machine Learning Ligands Humans
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Premexotac: Machine learning bitterants predictor for advancing pharmaceutical development.

International journal of pharmaceutics Oct 5, 2022
Bitter taste receptors were recently found to be involved in numerous physiological and pathological conditions other than taste and are suggested as potential drug targets. In vivo and in vitro techniques for screening bitterants as ligands come wit...
Machine Learning Algorithms Taste Aversive Agents Drug Development Ligands
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Ligand Unbinding Pathway and Mechanism Analysis Assisted by Machine Learning and Graph Methods.

Journal of chemical information and modeling Sep 29, 2022
We present two methods to reveal protein-ligand unbinding mechanisms in biased unbinding simulations by clustering trajectories into ensembles representing unbinding paths. The first approach is based on a contact principal component analysis for red...
Kinetics Protein Binding Machine Learning Ligands Proteins
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DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features.

Journal of chemical information and modeling Sep 26, 2022
Computational methods for virtual screening can dramatically accelerate early-stage drug discovery by identifying potential hits for a specified target. Docking algorithms traditionally use physics-based simulations to address this challenge by estim...
Molecular Docking Simulation Protein Binding Algorithms High-Throughput Screening Assays Membrane Proteins Neural Networks, Computer Ligands Machine Learning
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EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling Sep 15, 2022
Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the conventional surface-area-based methods fail to deliver a competitive pe...
Machine Learning Ligands Protein Binding Algorithms Proteins
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Are Deep Learning Structural Models Sufficiently Accurate for Free-Energy Calculations? Application of FEP+ to AlphaFold2-Predicted Structures.

Journal of chemical information and modeling Sep 13, 2022
The availability of AlphaFold2 has led to great excitement in the scientific community─particularly among drug hunters─due to the ability of the algorithm to predict protein structures with high accuracy. However, beyond globally accurate protein str...
Thermodynamics Models, Structural Ligands Deep Learning Protein Binding Proteins Molecular Dynamics Simulation Prospective Studies
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Effects of data quality and quantity on deep learning for protein-ligand binding affinity prediction.

Bioorganic & medicinal chemistry Sep 9, 2022
Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of t...
Machine Learning Deep Learning Protein Binding Data Accuracy Proteins Ligands
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