3 papers
cs.LG2025
The impact of conformer quality on learned representations of molecular conformer ensembles
Keir Adams, Connor W. Coley
Training machine learning models to predict properties of molecular conformer ensembles is an increasingly popular strategy to accelerate the conformational analysis of drug-like s…
q-bio.BM2024
ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
Keir Adams, Kento Abeywardane, Jenna Fromer +1
Engineering molecules to exhibit precise 3D intermolecular interactions with their environment forms the basis of chemical design. In ligand-based drug design, bioisosteric analogu…
cs.LG2023
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks
Yanqiao Zhu, Jeehyun Hwang, Keir Adams +10
Molecular Representation Learning (MRL) has proven impactful in numerous biochemical applications such as drug discovery and enzyme design. While Graph Neural Networks (GNNs) are e…