Oleksandr Isaev (O Isayev, Olexandr Isayev)

Scopus Author ID ResearcherID Loop profile ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 53

Top Venues

Journal of chemical information and modeling

Chemical science

Journal of chemical theory and computation

Journal of the American Chemical Society

Carnegie Mellon University

This page only lists publications with an associated author ORCID identifier.

Affiliation History

Carnegie Mellon University

United States

Assistant Professor :: Department of Chemistry

University of North Carolina at Chapel Hill

United States

Assistant professor :: UNC Eshelman School of Pharmacy

Publications

Pavlo O Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Oleksandr Isaev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Júnior, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. Journal of chemical theory and computation (2024)
Pavlo O Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Oleksandr Isaev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Júnior, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. Journal of chemical theory and computation 20 (3) (2024)
Pavlo O Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Oleksandr Isaev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Júnior, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. Journal of chemical theory and computation (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Holly M Johnson, Filipp Gusev, Jordan T Dull, Yejoon Seo, Rodney D Priestley, Oleksandr Isaev, Barry P Rand
Discovery of Crystallizable Organic Semiconductors with Machine Learning. Journal of the American Chemical Society 146 (31) (2024)
Holly M Johnson, Filipp Gusev, Jordan T Dull, Yejoon Seo, Rodney D Priestley, Oleksandr Isaev, Barry P Rand
Discovery of Crystallizable Organic Semiconductors with Machine Learning. Journal of the American Chemical Society (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Evgeny Gutkin, Filipp Gusev, Francesco Gentile, Fuqiang Ban, S Benjamin Koby, Chamali Narangoda, Oleksandr Isaev, Artem Cherkasov, Maria G Kurnikova
In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations. Chemical science 15 (23) (2024)
Evgeny Gutkin, Filipp Gusev, Francesco Gentile, Fuqiang Ban, S Benjamin Koby, Chamali Narangoda, Oleksandr Isaev, Artem Cherkasov, Maria G Kurnikova
In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations. Chemical science 15 (23) (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Pavlo O Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Oleksandr Isaev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Júnior, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. Journal of chemical theory and computation 20 (3) (2024)
Holly M Johnson, Filipp Gusev, Jordan T Dull, Yejoon Seo, Rodney D Priestley, Oleksandr Isaev, Barry P Rand
Discovery of Crystallizable Organic Semiconductors with Machine Learning. Journal of the American Chemical Society 146 (31) (2024)
Pavlo O Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Oleksandr Isaev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Júnior, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou
MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows. Journal of chemical theory and computation 20 (3) (2024)
Holly M Johnson, Filipp Gusev, Jordan T Dull, Yejoon Seo, Rodney D Priestley, Oleksandr Isaev, Barry P Rand
Discovery of Crystallizable Organic Semiconductors with Machine Learning. Journal of the American Chemical Society 146 (31) (2024)
Zhen Liu, Yurii S Moroz, Oleksandr Isaev
The challenge of balancing model sensitivity and robustness in predicting yields: a benchmarking study of amide coupling reactions. Chemical science 14 (39) (2023)
Qiyuan Zhao, Dylan M Anstine, Oleksandr Isaev, Brett M Savoie
Δ 2 machine learning for reaction property prediction. Chemical science 14 (46) (2023)
Théo Jaffrelot Inizan, Thomas Plé, Olivier Adjoua, Pengyu Ren, Hatice Gokcan, Oleksandr Isaev, Louis Lagardère, Jean-Philip Piquemal
Scalable hybrid deep neural networks/polarizable potentials biomolecular simulations including long-range effects. Chemical science 14 (20) (2023)
Aurora E Clark, Pavlo O Dral, Isaac Tamblyn, Oleksandr Isaev
Themed collection on Insightful Machine Learning for Physical Chemistry. Physical chemistry chemical physics : PCCP (2023)
Dylan M Anstine, Oleksandr Isaev
Machine Learning Interatomic Potentials and Long-Range Physics. The journal of physical chemistry. A (2023)
Filipp Gusev, Evgeny Gutkin, Maria G Kurnikova, Oleksandr Isaev
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. Journal of chemical information and modeling 63 (2) (2023)
Filipp Gusev, Evgeny Gutkin, Maria G Kurnikova, Oleksandr Isaev
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. Journal of chemical information and modeling (2023)
Filipp Gusev, Evgeny Gutkin, Maria G Kurnikova, Oleksandr Isaev
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. Journal of chemical information and modeling 63 (2) (2023)
Filipp Gusev, Evgeny Gutkin, Maria G Kurnikova, Oleksandr Isaev
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. Journal of chemical information and modeling (2023)
Dylan M Anstine, Oleksandr Isaev
Generative Models as an Emerging Paradigm in the Chemical Sciences. Journal of the American Chemical Society (2023)
Dylan M Anstine, Oleksandr Isaev
Machine Learning Interatomic Potentials and Long-Range Physics. The journal of physical chemistry. A 127 (11) (2023)
Hatice Gokcan, Jirair K Bedoyan, Oleksandr Isaev
Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function. Journal of chemical information and modeling 62 (14) (2022)
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S Smith, Benjamin T Nebgen, Richard A Messerly, Ying Wai Li, Alexander I Boldyrev, Kipton Barros, Oleksandr Isaev, Sergei Tretiak
Extending machine learning beyond interatomic potentials for predicting molecular properties. Nature reviews. Chemistry 6 (9) (2022)
Maria Korshunova, Niles Huang, Stephen Capuzzi, Dmytro S Radchenko, Olena Savych, Yuriy S Moroz, Carrow I Wells, Timothy M Willson, Alexander Trospsha, Oleksandr Isaev
Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds. Communications chemistry 5 (1) (2022)
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S Smith, Benjamin T Nebgen, Richard A Messerly, Ying Wai Li, Alexander I Boldyrev, Kipton Barros, Oleksandr Isaev, Sergei Tretiak
Extending machine learning beyond interatomic potentials for predicting molecular properties. Nature reviews. Chemistry 6 (9) (2022)
Hatice Gokcan, Oleksandr Isaev
Prediction of protein p K a with representation learning. Chemical science 13 (8) (2022)
Maria Korshunova, Niles Huang, Stephen Capuzzi, Dmytro S Radchenko, Olena Savych, Yuriy S Moroz, Carrow I Wells, Timothy M Willson, Alexander Trospsha, Oleksandr Isaev
Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds. Communications chemistry 5 (1) (2022)
Peikun Zheng, Wudi Yang, Wei Wu, Oleksandr Isaev, Pavlo O Dral
Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods. The journal of physical chemistry letters 13 (15) (2022)
Zhen Liu, Tetiana Zubatiuk, Adrian E Roitberg, Oleksandr Isaev
Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. Journal of chemical information and modeling 62 (22) (2022)
Anna Cichońska, Balaguru Ravikumar, Robert J Allaway, Fangping Wan, Sungjoon Park, Oleksandr Isaev, Shuya Li, Michael Mason, Andrew Lamb, Ziaurrehman Tanoli, Minji Jeon, Sunkyu Kim, Mariya Popova, Stephen J Capuzzi, Jianyang Zeng, Kristen Dang, Gregory Koytiger, Jaewoo Kang, Carrow I Wells, Timothy M Willson, null null, Tudor I Oprea, Avner Schlessinger, David Harold Drewry, Gustavo Stolovitzky, Krister Wennerberg, Justin Guinney, Tero Aittokallio
Crowdsourced mapping of unexplored target space of kinase inhibitors. Nature communications 12 (1) (2021)
Tetiana Zubatiuk, Benjamin T Nebgen, Nicholas Lubbers, Justin S Smith, Roman Zubatyuk, Guoqing Zhou, Christopher Koh, Kipton Barros, Oleksandr Isaev, Sergei Tretiak
Machine learned Hückel theory: Interfacing physics and deep neural networks. The Journal of chemical physics 154 (24) (2021)
Nongnuch Artrith, Keith T Butler, François-Xavier Coudert, Seungwu Han, Oleksandr Isaev, Evan Walter Clark Spotte-Smith, Aron Walsh
Best practices in machine learning for chemistry. Nature chemistry 13 (6) (2021)
Marcus Reis, Filipp Gusev, Nicholas G Taylor, Sang Hun Chung, Matthew D Verber, Yueh Z Lee, Oleksandr Isaev, Frank A Leibfarth
Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis. Journal of the American Chemical Society 143 (42) (2021)
Maria Korshunova, Boris Ginsburg, Alexander Trospsha, Oleksandr Isaev
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design. Journal of chemical information and modeling 61 (1) (2021)
Tetiana Zubatiuk, Oleksandr Isaev
Development of Multimodal Machine Learning Potentials: Toward a Physics-Aware Artificial Intelligence. Accounts of chemical research 54 (7) (2021)
Peikun Zheng, Roman Zubatyuk, Wei Wu, Oleksandr Isaev, Pavlo O Dral
Artificial intelligence-enhanced quantum chemical method with broad applicability. Nature communications 12 (1) (2021)
Roman Zubatyuk, Justin S Smith, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev
Teaching a neural network to attach and detach electrons from molecules. Nature communications 12 (1) (2021)
Xiang Gao, Farhad Ramezanghorbani, Oleksandr Isaev, Justin S Smith, Adrian E Roitberg
TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials. Journal of chemical information and modeling 60 (7) (2020)
Justin S Smith, Roman Zubatyuk, Benjamin Nebgen, Nicholas Lubbers, Kipton Barros, Adrian E Roitberg, Oleksandr Isaev, Sergei Tretiak
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules. Scientific data 7 (1) (2020)
Christian Devereux, Justin S Smith, Kate K Huddleston, Kipton Barros, Roman Zubatyuk, Oleksandr Isaev, Adrian E Roitberg
Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens. Journal of chemical theory and computation 16 (7) (2020)
Justin S Smith, Benjamin T Nebgen, Roman Zubatyuk, Nicholas Lubbers, Christian Devereux, Kipton Barros, Sergei Tretiak, Oleksandr Isaev, Adrian E Roitberg
Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning. Nature communications 10 (1) (2019)
Roman Zubatyuk, Justin S Smith, Jerzy Leszczynski, Oleksandr Isaev
Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network. Science advances 5 (8) (2019)
Michael Fernandez, Fuqiang Ban, Godwin Woo, Oleksandr Isaev, Carl Perez, Valery V Fokin, Alexander Trospsha, Artem Cherkasov
Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects. Journal of chemical information and modeling 59 (4) (2019)
Justin S Smith, Ben Nebgen, Nicholas Lubbers, Oleksandr Isaev, Adrian E Roitberg
Less is more: Sampling chemical space with active learning. The Journal of chemical physics 148 (24) (2018)
Benjamin Nebgen, Nicholas Lubbers, Justin S Smith, Andrew E Sifain, Andrey Lokhov, Oleksandr Isaev, Adrian E Roitberg, Kipton Barros, Sergei Tretiak
Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks. Journal of chemical theory and computation 14 (9) (2018)
Mariya Popova, Oleksandr Isaev, Alexander Trospsha
Deep reinforcement learning for de novo drug design. Science advances 4 (7) (2018)
Justin S Smith, Oleksandr Isaev, Adrian E Roitberg
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost. Chemical science 8 (4) (2017)
Oleksandr Isaev, Corey Oses, Cormac Toher, Eric Gossett, Stefano Curtarolo, Alexander Tropsha
Universal fragment descriptors for predicting properties of inorganic crystals. Nature communications 8 (2017)

Oleksandr Isaev.css-eqlu8i{font-size:small;padding-left:4px;} (O Isayev, Olexandr Isayev)

Publication Activity (10 Years)

Top Topics

Top Venues

Oleksandr Isaev (O Isayev, Olexandr Isayev)