325 citations · 386 across the 6 of their papers we have counts for
6 papers
Pareto Optimization to Accelerate Multi-Objective Virtual Screening
Jenna C. Fromer, David E. Graff, Connor W. Coley
The discovery of therapeutic molecules is fundamentally a multi-objective optimization problem. One formulation of the problem is to identify molecules that simultaneously exhibit…
Evaluating the roughness of structure-property relationships using pretrained molecular representations
David E. Graff, Edward O. Pyzer-Knapp, Kirk E. Jordan +2
Quantitative structure-property relationships (QSPRs) aid in understanding molecular properties as a function of molecular structure. When the correlation between structure and pro…
Roughness of molecular property landscapes and its impact on modellability
Matteo Aldeghi, David E. Graff, Nathan Frey +4
In molecular discovery and drug design, structure-property relationships and activity landscapes are often qualitatively or quantitatively analyzed to guide the navigation of chemi…
Self-focusing virtual screening with active design space pruning
David E. Graff, Matteo Aldeghi, Joseph A. Morrone +3
High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules. In cases where the library of molecules is exceedingly large, the cost…
pyscreener: A Python Wrapper for Computational Docking Software
David E. Graff, Connor W. Coley
pyscreener is a Python library that seeks to alleviate the challenges of large-scale structure-based design using computational docking. It provides a simple and uniform interface…
Accelerating high-throughput virtual screening through molecular pool-based active learning
David E. Graff, Eugene I. Shakhnovich, Connor W. Coley
Structure-based virtual screening is an important tool in early stage drug discovery that scores the interactions between a target protein and candidate ligands. As virtual librari…