All Stories

  1. From VAEs to Diffusion and LLMs: Modern Generative Models for Molecular Discovery

    Article • August 2026, ACM (Association for Computing Machinery)

    Dr Olexandr Isayev

  2. Label-Free, Quantum-Mechanically Informed Scoring of Protein–Ligand Complexes with Machine-Learned Interatomic Potentials

    Article • July 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  3. Label-Free, Quantum-Mechanically Informed Scoring of Protein–Ligand Complexes with Machine-Learned Interatomic Potentials

    Article • July 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  4. Efficient and Accurate Ligand Strain Calculations in Solution with the AIMNet2 Neural Network Potential

    Article • July 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  5. Scalable Low-Energy Molecular Conformer Generation with Quantum Mechanical Accuracy

    Article • July 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  6. Electron Alchemy with Machine-Learned Interatomic Potentials: Case Studies of Local Charge in Bond Dissociation Curves

    Article • Journal of Chemical Theory and Computation, July 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  7. Scalable Low-Energy Molecular Conformer Generation with Quantum Mechanical Accuracy

    Article • June 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  8. Democratizing Reaction Kinetics through Machine Vision and Learning

    Article • April 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  9. Benchmarking Universal Machine-learned Interatomic Potentials for Intermolecular and Noncovalent Interactions

    Article • February 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  10. AIQM3: Targeting Coupled-Cluster Accuracy with Semi-Empirical Speed across Seven Main-Group Elements

    Article • Journal of Chemical Theory and Computation, February 2026, American Chemical Society (ACS)

    Dr Olexandr Isayev

  11. Exploring celecoxib polymorph landscape using AIMNet2 machine learning interatomic potential

    Article • Chemical Science, January 2026, Royal Society of Chemistry

    Dr Olexandr Isayev

  12. Machine learning-accelerated screening of hydroquinone analogs for proton-coupled electron transfer

    Article • Chemical Science, January 2026, Royal Society of Chemistry

    Dr Olexandr Isayev

  13. Machine learning interatomic potentials at the centennial crossroads of quantum mechanics

    Article • Nature Computational Science, December 2025, Springer Science + Business Media

    Dr Olexandr Isayev

  14. Discovery of Novel Celecoxib Polymorphs Using AIMNet2 Machine Learning Interatomic Potential

    Article • December 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  15. AIMNet2‐NSE: A Transferable Reactive Neural Network Potential for Open‐Shell Chemistry

    Article • Angewandte Chemie, December 2025, Wiley

    Dr Olexandr Isayev

  16. AIMNet2‐NSE: A Transferable Reactive Neural Network Potential for Open‐Shell Chemistry

    Article • Angewandte Chemie, December 2025, Wiley

    Dr Olexandr Isayev

  17. Democratizing Reaction Kinetics through Machine Vision and Learning

    Article • November 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  18. Proto-Yield: An Uncertainty-Aware Prototype Network for Yield Prediction in Real-world Chemical Reactions

    Article • November 2025, ACM (Association for Computing Machinery)

    Nitesh Chawla, Dr Olexandr Isayev

  19. Machine Learning-Accelerated Screening of Hydroquinone Analogs for Proton-Coupled Electron Transfer

    Article • November 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  20. AIQM3: Targeting Coupled-Cluster Accuracy with Semi-Empirical Speed Across Seven Main Group Elements

    Article • October 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  21. Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network Potentials

    Article • Crystal Growth & Design, October 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  22. Fast and Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted Reactions

    Article • JACS Au, October 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  23. Anticipating the Selectivity of Intramolecular Cyclization Reaction Pathways with Neural Network Potentials

    Article • Journal of Chemical Theory and Computation, October 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  24. All That Glitters Is Not Gold: Importance of Rigorous Evaluation of Proteochemometric Models

    Article • Journal of Chemical Information and Modeling, September 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  25. Scalable Low-Energy Molecular Conformer Generation with Quantum Mechanical Accuracy

    Article • August 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  26. Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning

    Article • Angewandte Chemie, July 2025, Wiley

    Dr Olexandr Isayev

  27. Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning

    Article • Angewandte Chemie, July 2025, Wiley

    Dr Olexandr Isayev

  28. AIMNet2-rxn: A Machine Learned Potential for Generalized Reaction Modeling on a Millions-of-Pathways Scale

    Article • June 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  29. Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

    Article • Journal of Chemical Information and Modeling, April 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  30. ANI-1xBB: An ANI-Based Reactive Potential for Small Organic Molecules

    Article • Journal of Chemical Theory and Computation, April 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  31. Machine Learning anomaly detection of automated HPLC experiments in the Cloud Laboratory

    Article • March 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  32. Transferable Machine Learning Interatomic Potential for Pd-Catalyzed Cross-Coupling Reactions

    Article • March 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

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

    Article • January 2025, American Chemical Society (ACS)

    Dr Olexandr Isayev

  34. AIMNet2: a neural network potential to meet your neutral, charged, organic, and elemental-organic needs

    Article • Chemical Science, January 2025, Royal Society of Chemistry

    Dr Olexandr Isayev

  35. High-throughput electronic property prediction of cyclic molecules with 3D-enhanced machine learning

    Article • Chemical Science, January 2025, Royal Society of Chemistry

    Dr Olexandr Isayev

  36. GEOM-drugs revisited: toward more chemically accurate benchmarks for 3D molecule generation

    Article • Digital Discovery, January 2025, Royal Society of Chemistry

    Dr Olexandr Isayev

  37. Machine learning anomaly detection of automated HPLC experiments in the cloud laboratory

    Article • Digital Discovery, January 2025, Royal Society of Chemistry

    Dr Olexandr Isayev

  38. Applications of Modular Co-Design for De Novo 3D Molecule Generation

    Article • Digital Discovery, January 2025, Royal Society of Chemistry

    Dr Olexandr Isayev

  39. AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs

    Article • December 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  40. Accurate Ring Strain Energy Predictions with Machine Learning and Application in Strain-Promoted Reactions

    Article • November 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  41. ANI/EFP: Modeling Long-Range Interactions in ANI Neural Network with Effective Fragment Potentials

    Article • Journal of Chemical Theory and Computation, October 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  42. Discovery of Crystallizable Organic Semiconductors with Machine Learning

    Article • Journal of the American Chemical Society, July 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  43. Discovery of Crystallizable Organic Semiconductors with Machine Learning

    Article • June 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  44. AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs

    Article • April 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  45. Discovery of Crystallizable Organic Semiconductors with Machine Learning

    Article • April 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  46. In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations

    Article • March 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev

  47. Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

    Article • Nature Chemistry, March 2024, Springer Science + Business Media

    Dr Olexandr Isayev

  48. MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows

    Article • Journal of Chemical Theory and Computation, January 2024, American Chemical Society (ACS)

    Dr Olexandr Isayev, Professor Mario Barbatti

  49. In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations

    Article • Chemical Science, January 2024, Royal Society of Chemistry

    Dr Olexandr Isayev

  50. In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations

    Article • December 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  51. AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs

    Article • October 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  52. Synergy of semiempirical models and machine learning in computational chemistry

    Article • The Journal of Chemical Physics, September 2023, American Institute of Physics

    Dr Olexandr Isayev

  53. The Challenge of Balancing Model Sensitivity and Robustness in Predicting Yields: A Benchmarking Study of Amide Coupling Reactions

    Article • July 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  54. Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

    Article • June 2023, Research Square

    Dr Olexandr Isayev

  55. Structure Prediction of Epitaxial Organic Interfaces with Ogre, Demonstrated for Tetracyanoquinodimethane (TCNQ) on Tetrathiafulvalene (TTF)

    Article • The Journal of Physical Chemistry C, May 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  56. Generative Models as an Emerging Paradigm in the Chemical Sciences

    Article • Journal of the American Chemical Society, April 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  57. Machine Learning Interatomic Potentials and Long-Range Physics

    Article • The Journal of Physical Chemistry A, February 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  58. Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling

    Article • Journal of Chemical Information and Modeling, January 2023, American Chemical Society (ACS)

    Dr Olexandr Isayev

  59. Scalable hybrid deep neural networks/polarizable potentials biomolecular simulations including long-range effects

    Article • Chemical Science, January 2023, Royal Society of Chemistry

    Dr Olexandr Isayev

  60. The challenge of balancing model sensitivity and robustness in predicting yields: a benchmarking study of amide coupling reactions

    Article • Chemical Science, January 2023, Royal Society of Chemistry

    Dr Olexandr Isayev

  61. Themed collection on Insightful Machine Learning for Physical Chemistry

    Article • Physical Chemistry Chemical Physics, January 2023, Royal Society of Chemistry

    Dr Olexandr Isayev

  62. Δ2 machine learning for reaction property prediction

    Article • Chemical Science, January 2023, Royal Society of Chemistry

    Dr Olexandr Isayev

  63. Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds

    Article • Communications Chemistry, October 2022, Springer Science + Business Media

    Dr Olexandr Isayev

  64. Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials

    Article • Journal of Chemical Information and Modeling, September 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  65. Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials

    Article • September 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  66. Extending machine learning beyond interatomic potentials for predicting molecular properties

    Article • Nature Reviews Chemistry, August 2022, Springer Science + Business Media

    Dr Olexandr Isayev

  67. Active learning guided drug design lead optimization based on relative binding free energy modeling

    Article • July 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  68. Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function

    Article • Journal of Chemical Information and Modeling, July 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  69. Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials

    Article • June 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  70. Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods

    Article • The Journal of Physical Chemistry Letters, April 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

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

    Article • Nature Machine Intelligence, March 2022, Springer Science + Business Media

    Dr Olexandr Isayev

  72. Prediction of Protein pKa with Representation Learning

    Article • January 2022, Cambridge University Press

    Dr Olexandr Isayev

  73. Prediction of Protein pKa with Representation Learning

    Article • January 2022, American Chemical Society (ACS)

    Dr Olexandr Isayev

  74. Prediction of protein pKa with representation learning

    Article • Chemical Science, January 2022, Royal Society of Chemistry

    Dr Olexandr Isayev

  75. Artificial intelligence-enhanced quantum chemical method with broad applicability

    Article • Nature Communications, December 2021, Springer Science + Business Media

    Dr Olexandr Isayev

  76. Prediction of Protein pKa with Representation Learning

    Article • October 2021, Cambridge University Press

    Dr Olexandr Isayev

  77. Prediction of Protein pKa with Representation Learning

    Article • October 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  78. Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis

    Article • Journal of the American Chemical Society, October 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  79. Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures

    Article • Advanced Intelligent Systems, August 2021, Wiley

    Professor Dave A Winkler, Dr Marco Fronzi, Dr Olexandr Isayev, Dr Peter C Sherrell

  80. Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World

    Article • IEEE Internet of Things Journal, August 2021, Institute of Electrical & Electronics Engineers (IEEE)

    Dr Olexandr Isayev

  81. Teaching a neural network to attach and detach electrons from molecules

    Article • Nature Communications, August 2021, Springer Science + Business Media

    Dr Olexandr Isayev

  82. Learning molecular potentials with neural networks

    Article • Wiley Interdisciplinary Reviews Computational Molecular Science, July 2021, Wiley

    Dr Olexandr Isayev

  83. Machine learned Hückel theory: Interfacing physics and deep neural networks

    Article • The Journal of Chemical Physics, June 2021, American Institute of Physics

    Dr Olexandr Isayev

  84. Crowdsourced mapping of unexplored target space of kinase inhibitors

    Article • Nature Communications, June 2021, Springer Science + Business Media

    Dr Olexandr Isayev, Dr Tunca Dogan

  85. Best practices in machine learning for chemistry

    Article • Nature Chemistry, May 2021, Springer Science + Business Media

    Dr Olexandr Isayev

  86. Teaching a Neural Network to Attach and Detach Electrons from Molecules

    Article • April 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  87. Development of Multimodal Machine Learning Potentials: Toward a Physics-Aware Artificial Intelligence

    Article • Accounts of Chemical Research, March 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  88. A Bag of Tricks for Automated De Novo Design of Molecules with the Desired Properties: Application to EGFR Inhibitor Discovery

    Article • February 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  89. A Bag of Tricks for Automated De Novo Design of Molecules with the Desired Properties: Application to EGFR Inhibitor Discovery

    Article • February 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

  90. OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design

    Article • Journal of Chemical Information and Modeling, January 2021, American Chemical Society (ACS)

    Dr Olexandr Isayev

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

    Article • Chemical Society Reviews, January 2021, Royal Society of Chemistry

    Professor Dave A Winkler, Dr Olexandr Isayev

  92. High Throughput Screening of Millions of van der Waals Heterostructures for Superlubricant Applications

    Article • Advanced Theory and Simulations, September 2020, Wiley

    Dr Marco Fronzi, Professor Dave A Winkler, Dr Olexandr Isayev

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

    Article • July 2020, Cold Spring Harbor Laboratory Press

    Dr Olexandr Isayev

  94. Teaching a Neural Network to Attach and Detach Electrons from Molecules

    Article • July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  95. OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design

    Article • July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  96. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions

    Article • July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  97. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions

    Article • July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  98. TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials

    Article • Journal of Chemical Information and Modeling, July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  99. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions

    Article • July 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  100. Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens

    Article • Journal of Chemical Theory and Computation, June 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  101. Review for: Assessing Conformer Energies using Electronic Structure and Machine Learning Methods

    Article • June 2020, Authorea, Inc.

    Dr Olexandr Isayev

  102. TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials

    Article • May 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  103. The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

    Article • Scientific Data, May 2020, Springer Science + Business Media

    Dr Olexandr Isayev

  104. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

    Article • April 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  105. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

    Article • April 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  106. Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens

    Article • February 2020, American Chemical Society (ACS)

    Dr Olexandr Isayev

  107. Crowdsourced mapping of unexplored target space of kinase inhibitors

    Article • January 2020, Cold Spring Harbor Laboratory Press

    Dr Olexandr Isayev

  108. Correction: QSAR without borders

    Article • Chemical Society Reviews, January 2020, Royal Society of Chemistry

    Dr Olexandr Isayev, Professor Dave A Winkler

  109. QSAR without borders

    Article • Chemical Society Reviews, January 2020, Royal Society of Chemistry

    Dr Olexandr Isayev, Professor Dave A Winkler

  110. DRACON: disconnected graph neural network for atom mapping in chemical reactions

    Article • Physical Chemistry Chemical Physics, January 2020, Royal Society of Chemistry

    Dr Olexandr Isayev

  111. Predicting Thermal Properties of Crystals Using Machine Learning

    Article • Advanced Theory and Simulations, December 2019, Wiley

    Dr Olexandr Isayev, Professor Dave A Winkler

  112. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

    Article • October 2019, American Chemical Society (ACS)

    Dr Olexandr Isayev

  113. Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network

    Article • Science Advances, August 2019, American Association for the Advancement of Science

    Dr Olexandr Isayev

  114. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

    Article • Nature Communications, July 2019, Springer Science + Business Media

    Dr Olexandr Isayev

  115. Text mining facilitates materials discovery

    Article • Nature, July 2019, Springer Science + Business Media

    Dr Olexandr Isayev

  116. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

    Article • Nature Communications, June 2019, Springer Science + Business Media

    Dr Olexandr Isayev, Dr Mahmoud M ElHefnawi, Professor Chris Evelo

  117. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

    Article • June 2019, American Chemical Society (ACS)

    Dr Olexandr Isayev

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

    Article • Journal of Chemical Information and Modeling, February 2019, American Chemical Society (ACS)

    Dr Olexandr Isayev

  119. Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides

    Article • Bioinformatics, February 2019, Oxford University Press (OUP)

    Dr Olexandr Isayev

  120. Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfaces

    Article • RSC Advances, January 2019, Royal Society of Chemistry

    Dr Olexandr Isayev

  121. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches

    Article • Advanced Theory and Simulations, October 2018, Wiley

    Dr Olexandr Isayev, Professor Dave A Winkler

  122. Transforming Computational Drug Discovery with Machine Learning and AI

    Article • ACS Medicinal Chemistry Letters, October 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  123. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network

    Article • October 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  124. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network

    Article • October 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  125. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network

    Article • October 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  126. AFLOW-ML: A RESTful API for machine-learning predictions of materials properties

    Article • Computational Materials Science, September 2018, Elsevier

    Dr Olexandr Isayev

  127. Efficient prediction of structural and electronic properties of hybrid 2D materials using complementary DFT and machine learning approaches

    Article • August 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  128. Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks

    Article • Journal of Chemical Theory and Computation, August 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  129. Efficient prediction of structural and electronic properties of hybrid 2D materials using complementary DFT and machine learning approaches

    Article • August 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  130. Discovering a Transferable Charge Assignment Model Using Machine Learning

    Article • The Journal of Physical Chemistry Letters, July 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  131. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

    Article • July 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  132. Deep reinforcement learning for de novo drug design

    Article • Science Advances, July 2018, American Association for the Advancement of Science

    Dr Olexandr Isayev

  133. Machine learning for molecular and materials science

    Article • Nature, July 2018, Springer Science + Business Media

    Dr Olexandr Isayev

  134. Less is more: Sampling chemical space with active learning

    Article • The Journal of Chemical Physics, June 2018, American Institute of Physics

    Dr Olexandr Isayev

  135. Discovering a Transferable Charge Assignment Model Using Machine Learning

    Article • June 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  136. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

    Article • May 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  137. Diffusion of energetic compounds through biological membrane: application of classical MD and COSMOmic approximations

    Article • Journal of Biomolecular Structure and Dynamics, January 2018, Taylor & Francis

    Dr Olexandr Isayev

  138. Materials discovery by chemical analogy: role of oxidation states in structure prediction

    Article • Faraday Discussions, January 2018, Royal Society of Chemistry

    Dr Olexandr Isayev

  139. Outsmarting Quantum Chemistry Through Transfer Learning

    Article • January 2018, American Chemical Society (ACS)

    Dr Olexandr Isayev

  140. ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules

    Article • Scientific Data, December 2017, Springer Science + Business Media

    Dr Olexandr Isayev

  141. Universal fragment descriptors for predicting properties of inorganic crystals

    Article • Nature Communications, June 2017, Nature

    Dr Olexandr Isayev

  142. Material informatics driven design and experimental validation of lead titanate as an aqueous solar photocathode

    Article • Materials Discovery, May 2017, Elsevier

    Dr Olexandr Isayev

  143. ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

    Article • Chemical Science, January 2017, Royal Society of Chemistry

    Dr Olexandr Isayev

  144. Atlas Regeneration Company, Inc.

    Article • Regenerative Medicine, March 2016, Future Medicine

    Dr Olexandr Isayev

  145. QSAR Modeling of Tox21 Challenge Stress Response and Nuclear Receptor Signaling Toxicity Assays

    Article • Frontiers in Environmental Science, February 2016, Frontiers

    Dr Olexandr Isayev

  146. 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

    Article • Journal of Computational Chemistry, March 2015, Wiley

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  147. Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

    Article • Chemistry of Materials, January 2015, American Chemical Society (ACS)

    Dr Olexandr Isayev

  148. In silico structure-function analysis of E. cloacae nitroreductase

    Article • Proteins Structure Function and Bioinformatics, September 2012, Wiley

    Professor Jerzy Leszczynski, Prof. Carlos E Crespo-Hernández, Dr Olexandr Isayev

  149. Mechanical properties of silicon nanowires

    Article • Wiley Interdisciplinary Reviews Computational Molecular Science, June 2012, Wiley

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  150. Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modeling

    Article • Journal of Molecular Modeling, May 2012, Springer Science + Business Media

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  151. Evaluation of natural and nitramine binding energies to 3-D models of the S1S2 domains in the N-methyl-D-aspartate receptor

    Article • Journal of Molecular Modeling, July 2011, Springer Science + Business Media

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  152. Car–Parrinello Molecular Dynamics Simulations of Tensile Tests on Si⟨001⟩ Nanowires

    Article • The Journal of Physical Chemistry C, June 2011, American Chemical Society (ACS)

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  153. Effect of Solvation on the Vertical Ionization Energy of Thymine: From Microhydration to Bulk

    Article • The Journal of Physical Chemistry A, June 2011, American Chemical Society (ACS)

    Dr Olexandr Isayev

  154. Toward robust computational electrochemical predicting the environmental fate of organic pollutants

    Article • Journal of Computational Chemistry, May 2011, Wiley

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  155. Novel view on the mechanism of water-assisted proton transfer in the DNA bases: bulk water hydration

    Article • Physical Chemistry Chemical Physics, January 2011, Royal Society of Chemistry

    Professor Jerzy Leszczynski, Professor Dmytro Mykolayovych Hovorun, Dr Olexandr Isayev

  156. Reaction of bicyclo[2.2.1]hept-5-ene-endo-2-ylmethylamine and nitrophenyl glycidyl ethers

    Article • Journal of Physical Organic Chemistry, December 2010, Wiley

    Dr Olexandr Isayev

  157. One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives

    Article • Environmental Pollution, October 2010, Elsevier

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  158. Hydration of nucleic acid bases: a Car–Parrinello molecular dynamics approach

    Article • Physical Chemistry Chemical Physics, January 2010, Royal Society of Chemistry

    Oleg Shishkin, Professor Jerzy Leszczynski, Dr Olexandr Isayev

  159. New insight on structural properties of hydrated nucleic acid bases from ab initio molecular dynamics

    Article • Physical Chemistry Chemical Physics, January 2010, Royal Society of Chemistry

    Oleg Shishkin, Professor Jerzy Leszczynski, Dr Olexandr Isayev

  160. Ab Initio Molecular Dynamics Study on the Initial Chemical Events in Nitramines: Thermal Decomposition of CL-20

    Article • The Journal of Physical Chemistry, September 2008, American Chemical Society (ACS)

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  161. Efficient and accurate ab initio prediction of thermodynamic parameters for intermolecular complexes

    Article • Chemical Physics Letters, January 2008, Elsevier

    Dr Olexandr Isayev

  162. Carboxamides and amines having two and three adamantane fragments

    Article • Russian Journal of Organic Chemistry, November 2007, Pleiades Publishing Ltd

    Dr Olexandr Isayev

  163. Electronic Structure and Bonding of {Fe(PhNO2)}6 Complexes:  A Density Functional Theory Study

    Article • The Journal of Physical Chemistry A, April 2007, American Chemical Society (ACS)

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  164. Are Isolated Nucleic Acid Bases Really Planar? A Car−Parrinello Molecular Dynamics Study

    Article • The Journal of Physical Chemistry, March 2007, American Chemical Society (ACS)

    Oleg Shishkin, Professor Jerzy Leszczynski, Dr Olexandr Isayev

  165. Theoretical calculations: Can Gibbs free energy for intermolecular complexes be predicted efficiently and accurately?

    Article • Journal of Computational Chemistry, March 2007, Wiley

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  166. Structure-toxicity relationships of nitroaromatic compounds

    Article • Molecular Diversity, May 2006, Springer Science + Business Media

    Professor Bakhtiyor Rasulev, Professor Jerzy Leszczynski, Dr Olexandr Isayev

  167. Acylation of Aminopyridines and Related Compounds with Endic Anhydride

    Article • Russian Journal of Organic Chemistry, October 2005, Springer Science + Business Media

    Dr Olexandr Isayev

  168. Synthesis and Reactivity of Amines Containing Several Cage-like Fragments

    Article • Russian Journal of Organic Chemistry, May 2005, Springer Science + Business Media

    Dr Olexandr Isayev

  169. Amides containing two norbornene fragments. Synthesis and chemical transformations

    Article • Russian Journal of Organic Chemistry, October 2004, Springer Science + Business Media

    Dr Olexandr Isayev

  170. Reaction of Endic Anhydride with Hydrazines and Acylhydrazines

    Article • Russian Journal of Organic Chemistry, August 2004, Springer Science + Business Media

    Dr Olexandr Isayev

  171. Modeling the Gas-Phase Reduction of Nitrobenzene to Nitrosobenzene by Iron Monoxide:  A Density Functional Theory Study

    Article • The Journal of Physical Chemistry A, May 2004, American Chemical Society (ACS)

    Professor Jerzy Leszczynski, Dr Olexandr Isayev

  172. Amino Alcohols with Bicyclic Carbon Skeleton. Alternative Functionalization of Nucleophilic Reaction Centers

    Article • Russian Journal of Organic Chemistry, October 2003, Springer Science + Business Media

    Dr Olexandr Isayev

  173. Article • Russian Journal of Organic Chemistry, January 2002, Springer Science + Business Media

    Dr Olexandr Isayev