drug discovery

All that glitters is not gold: Importance of rigorous evaluation of proteochemometric models

Avdiunina P., Jamal S., Gusev F., Isayev O.

(2025)

Proteochemometric models (PCM) are used in computational drug discovery to leverage both protein and ligand representations for bioactivity prediction.

Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR

Tropsha A., Isayev O., Varnek A., Schneider G., Cherkasov A.

Nat. Rev. Drug Discov., 23, 141–155 (2024)

The transformational role of GPU computing and deep learning in drug discovery

Pandey M., Fernandez M., Gentile F., Isayev O., Tropsha A., Stern A. C., Cherkasov A.

Nature Machine Intelligence, 4, 211–221 (2022)

The transformational role of GPU computing and deep learning in drug discovery.

A critical overview of computational approaches employed for COVID-19 drug discovery

Muratov E. N., Amaro R., Andrade C. H., Brown N., Ekins S., Fourches D., Isayev O., Kozakov D., Medina-Franco J. L., Merz K. M., Oprea T. I., Poroikov V., Schneider G., Todd M. H., Varnek A., Winkler D. A., Zakharov A. V., Cherkasov A., Tropsha A.

Chemical Society Reviews, 50, 9121–9151 (2021)

We cover diverse methodologies, computational approaches, and case studies illustrating the ongoing efforts to develop viable drug candidates for treatment of COVID-19.

Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials

Rufa D. A., Bruce Macdonald H. E., Fass J., Wieder M., Grinaway P. B., Roitberg A. E., Isayev O., Chodera J. D.

(2020)

Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials.

Quantitative Structure–Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects

Fernandez M., Ban F., Woo G., Isaev O., Perez C., Fokin V., Tropsha A., Cherkasov A.

Journal of Chemical Information and Modeling, 59, 1306–1313 (2019)

Quantitative Structure–Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects.

Transforming Computational Drug Discovery with Machine Learning and AI

Smith J. S., Roitberg A. E., Isayev O.

ACS Medicinal Chemistry Letters, 9, 1065–1069 (2018)

Transforming Computational Drug Discovery with Machine Learning and AI.