Application and Assessment of Deep Learning for the Generation of Potential NMDA Receptor Antagonists. - Katherine J. Schultz; Sean M. Colby; Yasemin Yesiltepe; Jamie R. Nuñez; Monee Y. McGrady; Ryan S. Renslow (CoRR, 2020)

Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists. - Katherine J. Schultz; Sean M. Colby; Vivian S. Lin; Aaron T. Wright; Ryan S. Renslow (J. Chem. Inf. Model., 2021)

AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. - Rajendra P. Joshi; Katherine J. Schultz; Jesse William Wilson; Agustin Kruel; Rohith Anand Varikoti; Chathuri J. Kombala; Daniel W. Kneller; Stephanie Galanie; Gwyndalyn Phillips; Qiu Zhang; Leighton Coates; Jyothi Parvathareddy; et al. (J. Chem. Inf. Model., 2023)

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV-2 main protease. - Rohith Anand Varikoti; Katherine J. Schultz; Chathuri J. Kombala; Agustin Kruel; Kristoffer R. Brandvold; Mowei Zhou; Neeraj Kumar (J. Comput. Aided Mol. Des., 2023)