… to estimate the protein–ligand interaction scores [89]. A sample … scoring functions, these
methods also need to be trained on … However, more recently “negative” data have also been …

… and regenerate parameters for a specific FF using the drop-… in discriminating bad
protein–ligand interactions from the good … to docking scoring. In addition, we confirmed these …

… equally as bad (or even worse) on the validation set (PCC 0.51, … expected, we aim at using
po-sco for scoring of docked poses, … using maximum likelihood estimation. In addition to the …

… is applied: nonlocal protein–ligand interactions are included with … of our model with other
scoring functions. The numbers of … K i and K d into the negative log form to train the ML models. (…

… to protein–ligand complexes and added an angular parameter … very unlikely to interact with
other groups of negative (partial) … for an exploration of its use for scoring and ligand design. A …

… The essence of DNN models for deep-learning scoring … any physical parameters, wherein
the NC interactions are … for downsizing the protein–ligand structure and efficient training. …

… All affinities were expressed by a negative log scale. … improved the performance of AK-Score,
we therefore integrated the … atoms not critical for protein–ligand interactions are considered …

… of protein-ligand interactions in context of scoring functions 5,… learning scoring functions, the
same training and test set was … mixture of positive and negative relevance values that results …

… from effects of protein–ligand interactions on classification. We … to use pose ranks as input
rather than raw docking scores … As the data set is unbalanced, the overall higher negative …

… ID-Score [40] predicts protein–ligand binding affinity through … the negative protein–ligand
complexes that either interact with … construct the protein and protein–ligand interaction graphs. …