Boosting protein–ligand binding pose prediction and virtual screening based on residue–atom distance likelihood potential and graph transformer
… of all pairwise statistical potentials between proteins and ligands. The … for capturing
protein–ligand interactions. However, the … The models retrained in this study are in bold font. All of …
protein–ligand interactions. However, the … The models retrained in this study are in bold font. All of …
CANDOCK: Chemical atomic network-based hierarchical flexible docking algorithm using generalized statistical potentials
… of ligands and rank the activity of these ligands in such poses using a generalized statistically
derived force field, demonstrating the potential … of metal–ligand interaction potentials at the …
derived force field, demonstrating the potential … of metal–ligand interaction potentials at the …
Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions
… protein–ligand interactions from the known structures of protein–ligand complex pairs to derive
statistical models for … The final step of all these methods involves clustering and a ranking …
statistical models for … The final step of all these methods involves clustering and a ranking …
ProteinsPlus: interactive analysis of protein–ligand binding interfaces
K Schöning-Stierand, K Diedrich… - Nucleic acids …, 2020 - academic.oup.com
… a large variety of molecular modelling tasks covering the following … collection focusing on
protein–ligand interactions has been … geometry and provides statistical information about the …
protein–ligand interactions has been … geometry and provides statistical information about the …
Computationally predicting binding affinity in protein–ligand complexes: free energy-based simulations and machine learning-based scoring functions
… uses expert knowledge or statistical inference to define rules … , deep-learning models learn
a hierarchy of feature … relevant to protein-ligand interactions and employing SVR models for …
a hierarchy of feature … relevant to protein-ligand interactions and employing SVR models for …
Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions
… -based models on protein–ligand interaction predictions and listed the corresponding statistics
to … For the core set of PDBBind V2016, our model ranks second (R p = 0.837 and RMSE = …
to … For the core set of PDBBind V2016, our model ranks second (R p = 0.837 and RMSE = …
Quantum computational quantification of protein–ligand interactions
… blocks of 6000) to reduce statistical error in the energy to that … The ranking we obtained on
the quantum computer is not … the simplicity of our model of the protein-ligand interaction, which …
the quantum computer is not … the simplicity of our model of the protein-ligand interaction, which …
Protein–ligand docking in the machine-learning era
… in SBDD for fast evaluation of protein–ligand interactions [30,31]. … statistical potentials derived
from experimentally determined … , DL models were also applied in protein–ligand scoring …
from experimentally determined … , DL models were also applied in protein–ligand scoring …
Analysis of protein-ligand interactions of SARS-Cov-2 against selective drug using deep neural networks
N Yuvaraj, K Srihari, S Chandragandhi… - Big Data Mining and …, 2021 - ieeexplore.ieee.org
… enough to prevent traditional statistical and numerical approaches. … The compounds are
then ranked and the one with high … In this paper, we design a DNN model for the potential …
then ranked and the one with high … In this paper, we design a DNN model for the potential …
DeepRank: a deep learning framework for data mining 3D protein-protein interfaces
… ranked the docking models … and statistics across the different cases (median, 1 st and 3 rd
quartile) were calculated. As the total number of models varies between cases, these statistical …
quartile) were calculated. As the total number of models varies between cases, these statistical …