All Stories

  1. Generative Models as an Emerging Paradigm in the Chemical Sciences
  2. Machine Learning Interatomic Potentials and Long-Range Physics
  3. Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling
  4. Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds
  5. Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials
  6. Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials
  7. Extending machine learning beyond interatomic potentials for predicting molecular properties
  8. Active learning guided drug design lead optimization based on relative binding free energy modeling
  9. Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function
  10. Auto3D: Automatic Generation of the Low-energy 3D Structures with ANI Neural Network Potentials
  11. Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods
  12. The transformational role of GPU computing and deep learning in drug discovery
  13. Prediction of Protein pKa with Representation Learning
  14. Prediction of Protein pKa with Representation Learning
  15. Prediction of protein pKa with representation learning
  16. Artificial intelligence-enhanced quantum chemical method with broad applicability
  17. Prediction of Protein pKa with Representation Learning
  18. Prediction of Protein pKa with Representation Learning
  19. Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis
  20. Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures
  21. Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World
  22. Teaching a neural network to attach and detach electrons from molecules
  23. Learning molecular potentials with neural networks
  24. Machine learned Hückel theory: Interfacing physics and deep neural networks
  25. Crowdsourced mapping of unexplored target space of kinase inhibitors
  26. Best practices in machine learning for chemistry
  27. Teaching a Neural Network to Attach and Detach Electrons from Molecules
  28. Development of Multimodal Machine Learning Potentials: Toward a Physics-Aware Artificial Intelligence
  29. A Bag of Tricks for Automated De Novo Design of Molecules with the Desired Properties: Application to EGFR Inhibitor Discovery
  30. A Bag of Tricks for Automated De Novo Design of Molecules with the Desired Properties: Application to EGFR Inhibitor Discovery
  31. OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design
  32. A critical overview of computational approaches employed for COVID-19 drug discovery
  33. High Throughput Screening of Millions of van der Waals Heterostructures for Superlubricant Applications
  34. Towards chemical accuracy for alchemical free energy calculations with hybrid physics-based machine learning / molecular mechanics potentials
  35. Teaching a Neural Network to Attach and Detach Electrons from Molecules
  36. OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design
  37. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions
  38. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions
  39. TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials
  40. DRACON: Disconnected Graph Neural Network for Atom Mapping in Chemical Reactions
  41. Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens
  42. Review for: Assessing Conformer Energies using Electronic Structure and Machine Learning Methods
  43. TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials
  44. The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules
  45. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules
  46. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules
  47. Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens
  48. Crowdsourced mapping of unexplored target space of kinase inhibitors
  49. Correction: QSAR without borders
  50. QSAR without borders
  51. DRACON: disconnected graph neural network for atom mapping in chemical reactions
  52. Predicting Thermal Properties of Crystals Using Machine Learning
  53. The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules
  54. Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network
  55. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning
  56. Text mining facilitates materials discovery
  57. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
  58. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning
  59. Quantitative Structure–Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects
  60. Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides
  61. Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfaces
  62. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using Complementary DFT and Machine Learning Approaches
  63. Transforming Computational Drug Discovery with Machine Learning and AI
  64. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network
  65. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network
  66. Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network
  67. AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
  68. Efficient prediction of structural and electronic properties of hybrid 2D materials using complementary DFT and machine learning approaches
  69. Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks
  70. Efficient prediction of structural and electronic properties of hybrid 2D materials using complementary DFT and machine learning approaches
  71. Discovering a Transferable Charge Assignment Model Using Machine Learning
  72. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning
  73. Deep reinforcement learning for de novo drug design
  74. Machine learning for molecular and materials science
  75. Less is more: Sampling chemical space with active learning
  76. Discovering a Transferable Charge Assignment Model Using Machine Learning
  77. Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning
  78. Diffusion of energetic compounds through biological membrane: application of classical MD and COSMOmic approximations
  79. Materials discovery by chemical analogy: role of oxidation states in structure prediction
  80. Outsmarting Quantum Chemistry Through Transfer Learning
  81. ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules
  82. Universal fragment descriptors for predicting properties of inorganic crystals
  83. Material informatics driven design and experimental validation of lead titanate as an aqueous solar photocathode
  84. ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
  85. Atlas Regeneration Company, Inc.
  86. QSAR Modeling of Tox21 Challenge Stress Response and Nuclear Receptor Signaling Toxicity Assays
  87. 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
  88. Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints
  89. In silico structure-function analysis of E. cloacae nitroreductase
  90. Mechanical properties of silicon nanowires
  91. Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modeling
  92. Evaluation of natural and nitramine binding energies to 3-D models of the S1S2 domains in the N-methyl-D-aspartate receptor
  93. Car–Parrinello Molecular Dynamics Simulations of Tensile Tests on Si⟨001⟩ Nanowires
  94. Effect of Solvation on the Vertical Ionization Energy of Thymine: From Microhydration to Bulk
  95. Toward robust computational electrochemical predicting the environmental fate of organic pollutants
  96. Novel view on the mechanism of water-assisted proton transfer in the DNA bases: bulk water hydration
  97. Reaction of bicyclo[2.2.1]hept-5-ene-endo-2-ylmethylamine and nitrophenyl glycidyl ethers
  98. One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives
  99. Hydration of nucleic acid bases: a Car–Parrinello molecular dynamics approach
  100. New insight on structural properties of hydrated nucleic acid bases from ab initio molecular dynamics
  101. Ab Initio Molecular Dynamics Study on the Initial Chemical Events in Nitramines: Thermal Decomposition of CL-20
  102. Efficient and accurate ab initio prediction of thermodynamic parameters for intermolecular complexes
  103. Carboxamides and amines having two and three adamantane fragments
  104. Electronic Structure and Bonding of {Fe(PhNO2)}6 Complexes:  A Density Functional Theory Study
  105. Are Isolated Nucleic Acid Bases Really Planar? A Car−Parrinello Molecular Dynamics Study
  106. Theoretical calculations: Can Gibbs free energy for intermolecular complexes be predicted efficiently and accurately?
  107. Structure-toxicity relationships of nitroaromatic compounds
  108. Acylation of Aminopyridines and Related Compounds with Endic Anhydride
  109. Synthesis and Reactivity of Amines Containing Several Cage-like Fragments
  110. Amides containing two norbornene fragments. Synthesis and chemical transformations
  111. Reaction of Endic Anhydride with Hydrazines and Acylhydrazines
  112. Modeling the Gas-Phase Reduction of Nitrobenzene to Nitrosobenzene by Iron Monoxide:  A Density Functional Theory Study
  113. Amino Alcohols with Bicyclic Carbon Skeleton. Alternative Functionalization of Nucleophilic Reaction Centers