Olexandr Isayev

37 papers A* 3A 1Journal 33
YearRankTypeTitle / Venue / Authors
2025 J jnl
A practical guide to machine learning interatomic potentials - Status and future.
CoRR
Ryan Jacobs, Dane Morgan, Siamak Attarian, Jun Meng, Chen Shen, Zhenghao Wu, Clare Yijia Xie, Julia H. Yang, Nongnuch Artrith, Ben Blaiszik, Gerbrand Ceder, Kamal Choudhary, Gábor Csányi, Ekin Dogus Cubuk, Bowen Deng, Ralf Drautz, Xiang Fu, Jonathan Godwin, Vasant G. Honavar, Olexandr Isayev, Anders Johansson, Boris Kozinsky, Stefano Martiniani, Shyue Ping Ong, Igor Poltavsky, K. J. Schmidt, So Takamoto, Aidan Thompson, Julia Westermayr, Brandon M. Wood
2025 J jnl
Active Learning-Guided Hit Optimization for the Leucine-Rich Repeat Kinase 2 WDR Domain Based on In Silico Ligand-Binding Affinities.
J. Chem. Inf. Model.
Filipp Gusev, Evgeny Gutkin, Francesco Gentile, Fuqiang Ban, S. Benjamin Koby, Fengling Li, Irene Chau, Suzanne Ackloo, Cheryl H. Arrowsmith, Albina Bolotokova, Pegah Ghiabi, Elisa Gibson, Levon Halabelian, Scott Houliston, Rachel J. Harding, Ashley Hutchinson, Peter Loppnau, Sumera Perveen, Almagul Seitova, Hong Zeng, Matthieu Schapira, Artem Cherkasov, Olexandr Isayev, Maria G. Kurnikova
2025 J jnl
All That Glitters Is Not Gold: Importance of Rigorous Evaluation of Proteochemometric Models.
J. Chem. Inf. Model.
Polina Avdiunina, Shamieraah Jamal, Filipp Gusev, Olexandr Isayev
2025 J jnl
Anticipating the Selectivity of Cyclization Reaction Pathways with Neural Network Potentials.
CoRR
Nicholas Casetti, Dylan Anstine, Olexandr Isayev, Connor W. Coley
2025 J jnl
Applications of Modular Co-Design for De Novo 3D Molecule Generation.
CoRR
Danny Reidenbach, Filipp Nikitin, Olexandr Isayev, Saee Paliwal
2025 J jnl
GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation.
CoRR
Filipp Nikitin, Ian Dunn, David Ryan Koes, Olexandr Isayev
2025 J jnl
Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry.
J. Chem. Inf. Model.
Shuhao Zhang, Michael Chigaev, Olexandr Isayev, Richard A. Messerly, Nicholas Lubbers
2025 J jnl
Machine learning interatomic potentials at the centennial crossroads of quantum mechanics.
Nat. Comput. Sci.
Bhupalee Kalita, Hatice Gokcan, Olexandr Isayev
2025 A* conf
MolErr2Fix: Benchmarking LLM Trustworthiness in Chemistry via Modular Error Detection, Localization, Explanation, and Correction.
EMNLP
Yuyang Wu, Jinhui Ye, Shuhao Zhang, Lu Dai, Yonatan Bisk, Olexandr Isayev
2025 J jnl
MolErr2Fix: Benchmarking LLM Trustworthiness in Chemistry via Modular Error Detection, Localization, Explanation, and Revision.
CoRR
Yuyang Wu, Jinhui Ye, Shuhao Zhang, Lu Dai, Yonatan Bisk, Olexandr Isayev
2025 A conf
Proto-Yield: An Uncertainty-Aware Prototype Network for Yield Prediction in Real-world Chemical Reactions.
CIKM
Kehan Guo, Zhen Liu, Zhichun Guo, Bozhao Nan, Olexandr Isayev, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2025 J jnl
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).
CoRR
Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2024 J jnl
CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson's Disease Associated Protein.
J. Chem. Inf. Model.
Fengling Li, Suzanne Ackloo, Cheryl H. Arrowsmith, Fuqiang Ban, Christopher J. Barden, Hartmut Beck, Jan Beránek, Francois Berenger, Albina Bolotokova, Guillaume Bret, Marko Breznik, Emanuele Carosati, Irene Chau, Yu Chen, Artem Cherkasov, Dennis Della Corte, Katrin Denzinger, Aiping Dong, Sorin Draga, Ian Dunn, Kristina Edfeldt, Aled M. Edwards, Merveille K. I. Eguida, Paul Eisenhuth, Lukas Friedrich, Alexander Fuerll, Spencer S. Gardiner, Francesco Gentile, Pegah Ghiabi, Elisa Gibson, Marta Glavatskikh, Christoph Gorgulla, Judith Guenther, Anders Gunnarsson, Filipp Gusev, Evgeny Gutkin, Levon Halabelian, Rachel J. Harding, Alexander Hillisch, Laurent Hoffer, Anders Hogner, Scott Houliston, John J. Irwin, Olexandr Isayev, Aleksandra Ivanova, Célien Jacquemard, Austin J. Jarrett, Jan H. Jensen, Dmitri Kireev, Julian Kleber, S. Benjamin Koby, David Koes, Ashutosh Kumar, Maria G. Kurnikova, Alina Kutlushina, Uta F. Lessel, Fabian Liessmann, Sijie Liu, Wei Lu, Jens Meiler, Akhila Mettu, Guzel Minibaeva, Rocco Moretti, Connor J. Morris, Chamali Narangoda, Theresa Noonan, Leon Obendorf, Szymon Pach, Amit Pandit, Sumera Perveen, Gennady Poda, Pavel G. Polishchuk, Kristina Puls, Vera Pütter, Didier Rognan, Dylan Roskams-Edris, Christina E. M. Schindler, François Sindt, Vojtech Spiwok, Casper Steinmann, Rick L. Stevens, Valerij Talagayev, Damon Tingey, Oanh Vu, W. Patrick Walters, Xiaowen Wang, Zhenyu Wang, Gerhard Wolber, Clemens Alexander Wolf, Lars Wortmann, Hong Zeng, Carlos A. Zepeda, Kam Y. J. Zhang, Jixian Zhang, Shuangjia Zheng, Matthieu Schapira
2024 J jnl
Editorial: Machine Learning in Materials Science.
J. Chem. Inf. Model.
Kenneth M. Merz Jr., Yee-Siew Choong, Zoe Cournia, Olexandr Isayev, Thereza A. Soares, Guo-Wei Wei, Feng Zhu
2024 A* conf
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.
ICLR
Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
2024 A* conf
Uncertainty-Aware Yield Prediction with Multimodal Molecular Features.
AAAI
Jiayuan Chen, Kehan Guo, Zhen Liu, Olexandr Isayev, Xiangliang Zhang
2023 J jnl
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling.
J. Chem. Inf. Model.
Filipp Gusev, Evgeny Gutkin, Maria G. Kurnikova, Olexandr Isayev
2023 J jnl
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.
CoRR
Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
2023 J jnl
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows.
CoRR
Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
2022 J jnl
Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials.
J. Chem. Inf. Model.
Zhen Liu, Tetiana Zubatiuk, Adrian E. Roitberg, Olexandr Isayev
2022 J jnl
Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function.
J. Chem. Inf. Model.
Hatice Gokcan, Jirair K. Bedoyan, Olexandr Isayev
2022 J jnl
The transformational role of GPU computing and deep learning in drug discovery.
Nat. Mach. Intell.
Mohit Pandey, Michael Fernández, Francesco Gentile, Olexandr Isayev, Alexander Tropsha, Abraham C. Stern, Artem Cherkasov
2021 J jnl
Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures.
Adv. Intell. Syst.
Marco Fronzi, Olexandr Isayev, David A. Winkler, Joseph George Shapter, Amanda V. Ellis, Peter C. Sherrell, Nick A. Shepelin, Alexander Corletto, Michael J. Ford
2021 J jnl
Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World.
IEEE Internet Things J.
Farshad Firouzi, Bahareh J. Farahani, Mahmoud Daneshmand, Kathy Grise, JaeSeung Song, Roberto Saracco, Lucy Lu Wang, Kyle Lo, Plamen Angelov, Eduardo A. Soares, Po-Shen Loh, Zeynab Talebpour, Reza Moradi, Mohsen Goodarzi, Haleh Ashraf, Mohammad Talebpour, Alireza Talebpour, Luca Romeo, Rupam Das, Hadi Heidari, Dana K. Pasquale, James Moody, Chris Woods, Erich S. Huang, Payam M. Barnaghi, Majid Sarrafzadeh, Ron C. Li, Kristen L. Beck, Olexandr Isayev, NakMyoung Sung, Alan Luo
2021 J jnl
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design.
J. Chem. Inf. Model.
Maria Korshunova, Boris Ginsburg, Alexander Tropsha, Olexandr Isayev
2021 J jnl
Simulation Intelligence: Towards a New Generation of Scientific Methods.
CoRR
Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer
2020 J jnl
TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials.
J. Chem. Inf. Model.
Xiang Gao, Farhad Ramezanghorbani, Olexandr Isayev, Justin S. Smith, Adrian E. Roitberg
2019 J jnl
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery.
CoRR
Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A. Winkler, Joe Shapter, Michael J. Ford
2019 J jnl
Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides.
Bioinform.
Sherif Farag, Rachel M. Bleich, Elizabeth A. Shank, Olexandr Isayev, Albert A. Bowers, Alexander Tropsha
2019 J jnl
MolecularRNN: Generating realistic molecular graphs with optimized properties.
CoRR
Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev
2019 J jnl
Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects.
J. Chem. Inf. Model.
Michael Fernández, Fuqiang Ban, Godwin Woo, Olexandr Isayev, Carl Perez, Valery Fokin, Alexander Tropsha, Artem Cherkasov
2018 J jnl
Less is more: sampling chemical space with active learning.
CoRR
Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg
2017 J jnl
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules.
CoRR
Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg
2017 J jnl
Deep Reinforcement Learning for De-Novo Drug Design.
CoRR
Mariya Popova, Olexandr Isayev, Alexander Tropsha
2015 J jnl
Are the reduction and oxidation properties of nitrocompounds dissolved in water different from those produced when adsorbed on a silica surface? A DFT M05-2X computational study.
J. Comput. Chem.
Liudmyla K. Sviatenko, Olexandr Isayev, Leonid Gorb, Frances C. Hill, Danuta Leszczynska, Jerzy Leszczynski
2011 J jnl
Toward robust computational electrochemical predicting the environmental fate of organic pollutants.
J. Comput. Chem.
Liudmyla K. Sviatenko, Olexandr Isayev, Leonid Gorb, Frances Hill, Jerzy Leszczynski
2007 J jnl
Theoretical calculations: Can Gibbs free energy for intermolecular complexes be predicted efficiently and accurately?
J. Comput. Chem.
Olexandr Isayev, Leonid Gorb, Jerzy Leszczynski