… SE(3) denoising score matching (DSM) and interpret its log-… matching (DSM) [33, 15] as
maximum likelihood estimation is … K perturbed protein-ligand complexes X1, ··· , XK as negative …

… scoring function on the structure-based drug design with data… any physical parameters,
wherein the NC interactions are … downsizing the protein-ligand structure and efficient training. …

… scores used in our analysis is also described in STAR Methods. To maintain an adequate
amount of training data … the probability scores of all the potential positive and negative samples…

… These include analyzing protein-ligand interaction … (PharmRF score bears positive sign and
Vina score carries negative … training on pharmacophoric feature counts in a large dataset as …

… terms without considering specific protein–ligand interaction. The … Note that the scoring
function of Vina was trained on a set of … larger than 2 Å as negative pose. Kumar and coworkers …

… that a model trained on protein–ligand interactions (I model) … the PDBbind training set
on the scoring power of MPNN … parameter, notably for models trained only on protein–ligand …

… model learn how protein–ligand interactions affect the node … positive, and PDBbind negative
samples with the fixed ratio … In terms of the RE score, our method shows 9–10 times better …

… of this data set for benchmarking protein–ligand binding … parameters estimated from
experimental and simulated data … its own representation of the protein–ligand interaction in order …

… RASPD method and traditional scoring functions on a range … of non-covalent protein-ligand
interactions with a resolution … energy has the strongest negative correlation with the ligand …

… and scoring/ranking a set of ligands for well-defined targets [5, 8,9,10,11,12,13,14]. … parameters
to the IShape similarity score [15] parametrized on a training set of 1800 protein–ligand X-…