… the proposed SIGN model for proteinligand binding affinity … Statistical and machine learning
approaches to predicting … for protein- ligand interactions: a simplified potential approach. …

… Most scoring functions can be classified into physical energy-based, statistical potential-…
The DeepRank-GNN model that we present here ranks second in terms of accuracy (82%) …

… In summary, a function to score protein–ligand docking … the energy landscape of protein–ligand
interactions, and second… in modeling, we also evaluated the pose ranking performance (…

… especially when the ligand interaction and receptor structure … (Statistical Assessment of
Modeling of Proteins and Ligands) … ’s top ranked docking model possessing a ligand RMSD of …

… networks and rationally engineering protein–ligand interactions. … -seq peak classification task
used to quantify model performance in … The core of the algorithm is a statistical model of the …

… structures from the protein–ligand interactions, we consider … For PDBbind-v2013 and
PDBbind-v2016, our model rank as … , we consider a set of persistent attributes using statistical and …

… In our protein–ligand interaction model, 36 types of bipartite … models for the classification of
decoy and real docking poses. … a set of persistent attributes from statistical and combinatorial …

… simulation package to automate the calculation of binding free energies for a protein with
a series of ligands… We report encouraging initial test applications of this software both to re-rank …

… reliability is also required to allow a more consistent classification… RSCC is a statistical
measurement which is publicly … new protein ligand interactions but to improve the ligand solubility …

… as homology modeling, molecular dynamics, protein docking, … Instead of using partial
sequence and statistical features of … the binding energy of protein–ligand interactions in docking …