98 citations · 182 across the 7 of their papers we have counts for
5 papers · 1 filter
Pearl: A Foundation Model for Placing Every Atom in the Right Location
Genesis Research Team, Alejandro Dobles, Nina Jovic +37
Accurately predicting the three-dimensional structures of protein-ligand complexes remains a fundamental challenge in computational drug discovery that limits the pace and success…
Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization
Evan N. Feinberg, Robert Sheridan, Elizabeth Joshi +2
The Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) properties of drug candidates are estimated to account for up to 50% of all clinical trial failures. Pre…
PotentialNet for Molecular Property Prediction
Evan N. Feinberg, Debnil Sur, Zhenqin Wu +7
The arc of drug discovery entails a multiparameter optimization problem spanning vast length scales. They key parameters range from solubility (angstroms) to protein-ligand binding…
Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity
Joseph Gomes, Bharath Ramsundar, Evan N. Feinberg +1
Empirical scoring functions based on either molecular force fields or cheminformatics descriptors are widely used, in conjunction with molecular docking, during the early stages of…
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu, Bharath Ramsundar, Evan N. Feinberg +5
Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make…