330 citations · 2.7k across the 74 of their papers we have counts for
9 papers · 1 filter
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…
Message Passing Networks for Molecules with Tetrahedral Chirality
Lagnajit Pattanaik, Octavian-Eugen Ganea, Ian Coley +3
Molecules with identical graph connectivity can exhibit different physical and biological properties if they exhibit stereochemistry-a spatial structural characteristic. However, m…
Learning Graph Models for Retrosynthesis Prediction
Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley +2
Retrosynthesis prediction is a fundamental problem in organic synthesis, where the task is to identify precursor molecules that can be used to synthesize a target molecule. A key c…
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Lior Hirschfeld, Kyle Swanson, Kevin Yang +2
Uncertainty quantification (UQ) is an important component of molecular property prediction, particularly for drug discovery applications where model predictions direct experimental…
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu +9
Over the last decade, there has been significant progress in the field of machine learning for de novo drug design, particularly in deep generative models. However, current generat…
Autonomous discovery in the chemical sciences part II: Outlook
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
This two-part review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this second part, we reflect on a selection of exemplary…
Autonomous discovery in the chemical sciences part I: Progress
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
This two-part review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this first part, we describe a classification for discov…
The Synthesizability of Molecules Proposed by Generative Models
Wenhao Gao, Connor W. Coley
The discovery of functional molecules is an expensive and time-consuming process, exemplified by the rising costs of small molecule therapeutic discovery. One class of techniques o…
Retrosynthesis Prediction with Conditional Graph Logic Network
Hanjun Dai, Chengtao Li, Connor W. Coley +2
Retrosynthesis is one of the fundamental problems in organic chemistry. The task is to identify reactants that can be used to synthesize a specified product molecule. Recently, com…