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Machine learning (ML) outperforms traditional approaches in many molecular design tasks.
Analyzing Learned Molecular Representations for Property Prediction
Yang, K. et al · 1904
Earlier work this paper cites.
Molecular Geometry Prediction using a Deep Generative Graph Neural Network
Mansimov, E., Mahmood, O., Kang, S. & Cho, K · 1904
Earlier work this paper cites.
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Gebauer, N. W. A., Gastegger, M. & Schütt, K. T · 1906
Earlier work this paper cites.
Generative Models for Automatic Chemical Design
Schwalbe-Koda, D. & Gómez-Bombarelli, R · 1907
Earlier work this paper cites.
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
Weininger, D · 1988
Earlier work this paper cites.
Uff, a full periodic table force field for molecular mechanics and molecular dynamics simulations
Rappé, A. K., Casewit, C. J., Colwell, K., Goddard III, W. A. & Skiff, W. M · 1992
Earlier work this paper cites.
Conductor-like screening model for real solvents: a new approach to the quantitative calculation of solvation phenomena
Klamt, A · 1995
Earlier work this paper cites.
Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94
Halgren, T. A · 1996
Earlier work this paper cites.
Conformational analysis using distance geometry methods
Spellmeyer, D. C., Wong, A. K., Bower, M. J. & Blaney, J. M · 1997
Earlier work this paper cites.
Refinement and parametrization of COSMO-RS
Klamt, A., Jonas, V., Bürger, T. & Lohrenz, J. C · 1998
Earlier work this paper cites.
Quantum calculation of molecular energies and energy gradients in solution by a conductor solvent model
Barone, V. & Cossi, M · 1998
Earlier work this paper cites.
Random forests
Breiman, L · 2001
Earlier work this paper cites.
ESOL: Estimating aqueous solubility directly from molecular structure
Delaney, J. S · 2004
Earlier work this paper cites.
The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structures
Wang, R., Fang, X., Lu, Y. & Wang, S · 2004
Earlier work this paper cites.
Development and testing of a general amber force field
Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A. & Case, D. A · 2004
Earlier work this paper cites.
ESOL: estimating aqueous solubility directly from molecular structure
Delaney, J. S · 2004
Earlier work this paper cites.
Discrimination between modes of toxic action of phenols using rule based methods
Norinder, U., Lidén, P. & Boström, H · 2006
Earlier work this paper cites.
Generating conformer ensembles using a multiobjective genetic algorithm
Vainio, M. J. & Johnson, M. S · 2007
Earlier work this paper cites.
Conformational entropy in molecular recognition by proteins
Frederick, K. K., Marlow, M. S., Valentine, K. G. & Wand, A. J · 2007
Earlier work this paper cites.
Crystallography Open Database–an open-access collection of crystal structures
Gražulis, S. et al · 2009
Earlier work this paper cites.
Accurate conformation-dependent molecular electrostatic potentials for high-throughput in silico drug discovery
Puranen, J. S., Vainio, M. J. & Johnson, M. S · 2010
Earlier work this paper cites.
Frog2: Efficient 3D conformation ensemble generator for small compounds
Miteva, M. A., Guyon, F. & Pierre, T · 2010
Earlier work this paper cites.
Conformer generation with OMEGA: algorithm and validation using high quality structures from the Protein Databank and Cambridge Structural Database
Hawkins, P. C., Skillman, A. G., Warren, G. L., Ellingson, B. A. & Stahl, M. T · 2010
Earlier work this paper cites.
Conformations and 3D pharmacophore searching, 10.1016/j.ddtec.2010.10.003 (2010)
Schwab, C. H · 2010
Earlier work this paper cites.
Extended-connectivity fingerprints
Rogers, D. & Hahn, M · 2010
Earlier work this paper cites.
Molecular dynamics simulations and drug discovery
Durrant, J. D. & McCammon, J. A · 2011
Earlier work this paper cites.
PubChem3D: conformer generation
Bolton, E. E., Kim, S. & Bryant, S. H · 2011
Earlier work this paper cites.
Confab-Systematic generation of diverse low-energy conformers
O’Boyle, N. M., Vandermeersch, T., Flynn, C. J., Maguire, A. R. & Hutchison, G. R · 2011
Earlier work this paper cites.
Confab - Systematic generation of diverse low-energy conformers
O’Boyle, N. M., Vandermeersch, T., Flynn, C. J., Maguire, A. R. & Hutchison, G. R · 2011
Earlier work this paper cites.
Supramolecular binding thermodynamics by dispersion-corrected density functional theory
Grimme, S · 2012
Earlier work this paper cites.
The ORCA program system
Neese, F · 2012
Earlier work this paper cites.
Machine learning: a probabilistic perspective (MIT press, 2012)
Murphy, K. P · 2012
Earlier work this paper cites.
A Bayesian approach to in silico blood-brain barrier penetration modeling
Martins, I. F., Teixeira, A. L., Pinheiro, L. & Falcao, A. O · 2012
Earlier work this paper cites.
Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters
Stewart, J. J · 2013
Earlier work this paper cites.
SWEETLEAD: an in silico database of approved drugs, regulated chemicals, and herbal isolates for computer-aided drug discovery
Novick, P. A., Ortiz, O. F., Poelman, J., Abdulhay, A. Y. & Pande, V. S · 2013
Earlier work this paper cites.
FreeSolv: A database of experimental and calculated hydration free energies, with input files
Mobley, D. L. & Guthrie, J. P · 2014
Earlier work this paper cites.
Quantum chemistry structures and properties of 134 kilo molecules
Ramakrishnan, R., Dral, P. O., Rupp, M. & von Lilienfeld, O. A · 2014
Earlier work this paper cites.
FreeSolv: a database of experimental and calculated hydration free energies, with input files
Mobley, D. L. & Guthrie, J. P · 2014
Earlier work this paper cites.
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Duvenaud, D. K. et al · 2015
Earlier work this paper cites.
ZINC 15–Ligand Discovery for Everyone
Sterling, T. & Irwin, J. J · 2015
Earlier work this paper cites.
InChI, the IUPAC International Chemical Identifier
Heller, S. R., McNaught, A., Pletnev, I., Stein, S. & Tchekhovskoi, D · 2015
Earlier work this paper cites.
Universal structure conversion method for organic molecules: from atomic connectivity to three-dimensional geometry
Kim, Y. & Kim, W. Y · 2015
Cited alongside, same era.
Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach
Gómez-Bombarelli, R. et al · 2016
Cited alongside, same era.
Molecular graph convolutions: moving beyond fingerprints
Kearnes, S., McCloskey, K., Berndl, M., Pande, V. & Riley, P · 2016
Cited alongside, same era.
A real-world perspective on molecular design: Miniperspective
Kuhn, B. et al · 2016
Cited alongside, same era.
Computational modeling of β \beta -secretase 1 (BACE-1) inhibitors using ligand based approaches
Subramanian, G., Ramsundar, B., Pande, V. & Denny, R. A · 2016
Cited alongside, same era.
The Cambridge structural database
End-to-End Differentiable Learning of Protein Structure
AlQuraishi, M · 2019
Later among the works it cites.
Learning Protein Structure with a Differentiable Simulator
Ingraham, J., Riesselman, A., Sander, C. & Marks, D · 2019
Later among the works it cites.
Cormorant: Covariant molecular neural networks
Anderson, B., Hy, T. S. & Kondor, R · 2019
Later among the works it cites.
Directional message passing for molecular graphs
Klicpera, J., Groß, J. & Günnemann, S · 2019
Later among the works it cites.
Deep Learning for the Life Sciences (O’Reilly Media, 2019)
Ramsundar, B. et al · 2019
Later among the works it cites.
{GuacaMol}: Benchmarking Models for de Novo Molecular Design
Brown, N., Fiscato, M., Segler, M. H. S. & Vaucher, A. C · 2019
Later among the works it cites.
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Groom, C. R., Bruno, I. J., Lightfoot, M. P. & Ward, S. C · 2016
Cited alongside, same era.
Flexibility unleashed in acyclic monoterpenes: Conformational space of citronellal revealed by broadband rotational spectroscopy
Domingos, S. R., Pérez, C., Medcraft, C., Pinacho, P. & Schnell, M · 2016
Cited alongside, same era.
ToxCast chemical landscape: paving the road to 21st century toxicology
Richard, A. M. et al · 2016
Cited alongside, same era.
The SIDER database of drugs and side effects
Kuhn, M., Letunic, I., Jensen, L. J. & Bork, P · 2016
Cited alongside, same era.
Molecular De Novo Design through Deep Reinforcement Learning
Olivecrona, M., Blaschke, T., Engkvist, O. & Chen, H · 2017
Cited alongside, same era.
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models
Guimaraes, G. L., Sanchez-Lengeling, B., Outeiral, C., Farias, P. L. C. & Aspuru-Guzik, A · 2017
Cited alongside, same era.
Prediction of Organic Reaction Outcomes Using Machine Learning
Coley, C. W., Barzilay, R., Jaakkola, T. S., Green, W. H. & Jensen, K. F · 2017
Cited alongside, same era.
GFN2-xTB—An accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions
Bannwarth, C., Ehlert, S. & Grimme, S · 2019
Later among the works it cites.
A generative model for molecular distance geometry
Simm, G. N. & Hernández-Lobato, J. M · 2019
Later among the works it cites.
Data-driven approach to encoding and decoding 3-d crystal structures
Hoffmann, J. et al · 2019
Later among the works it cites.
Generating valid Euclidean distance matrices
Hoffmann, M. & Noé, F · 2019
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Bayesian optimization for conformer generation
Chan, L., Hutchison, G. R. & Morris, G. M · 2019
Later among the works it cites.
Coarse-graining auto-encoders for molecular dynamics
Wang, W. & Gómez-Bombarelli, R · 2019
Later among the works it cites.
Bayesian optimization for conformer generation
Chan, L., Hutchison, G. R. & Morris, G. M · 2019
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Exploration of chemical compound, conformer, and reaction space with meta-dynamics simulations based on tight-binding quantum chemical calculations
Grimme, S · 2019
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Exploration of chemical compound, conformer, and reaction space with meta-dynamics simulations based on tight-binding quantum chemical calculations
Grimme, S · 2019
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Analyzing learned molecular representations for property prediction
Yang, K. et al · 2019
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ChEMBL: towards direct deposition of bioassay data
Mendez, D. et al · 2019
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A deep learning approach to antibiotic discovery
Stokes, J. M. et al · 2020
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Differentiable molecular simulations for control and learning
Wang, W., Axelrod, S. & Gómez-Bombarelli, R · 2020
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Learning to navigate the synthetically accessible chemical space using reinforcement learning
Gottipati, S. K. et al · 2020
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Automated exploration of the low-energy chemical space with fast quantum chemical methods
Pracht, P., Bohle, F. & Grimme, S · 2020
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Reinforcement learning for molecular design guided by quantum mechanics
Simm, G. N., Pinsler, R. & Hernández-Lobato, J. M · 2020
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Adversarial reverse mapping of equilibrated condensed-phase molecular structures
Stieffenhofer, M., Wand, M. & Bereau, T · 2020
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Deep Generative Models for 3D Linker Design
Imrie, F., Bradley, A. R., van der Schaar, M. & Deane, C. M · 2020
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Nelfinavir was predicted to be a potential inhibitor of 2019-nCov main protease by an integrative approach combining homology modelling, molecular docking and binding free energy calculation
Xu, Z. et al · 2020
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Accessed: 2020-07-06
https://github.com/yangkevin2/coronavirus_data/tree/master/data · 2020
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Accessed: 2020-05-22
https://www.aicures.mit.edu/data (2020) · 2020
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Identification of inhibitors of SARS-CoV-2 in-vitro cellular toxicity in human (Caco-2) cells using a large scale drug repurposing collection
Ellinger, B. et al · 2020
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In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication
Touret, F. et al · 2020
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https://github.com/jensengroup/xyz2mol
Converts and [sic] xyz file to an RDKit mol object · 2020
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The ORCA quantum chemistry program package
Neese, F., Wennmohs, F., Becker, U. & Riplinger, C · 2020
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Molecular machine learning with conformer ensembles
Axelrod, S. & Gomez-Bombarelli, R · 2020
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https://github.com/hyperopt/hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python · 2020
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MessagePack serializer implementation for Python · 2020
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Efficient quantum chemical calculation of structure ensembles and free energies for nonrigid molecules
Grimme, S. et al · 2021
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r2SCAN-3c: A “Swiss army knife” composite electronic-structure method
Grimme, S., Hansen, A., Ehlert, S. & Mewes, J.-M · 2021
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Single-point Hessian calculations for improved vibrational frequencies and rigid-rotor-harmonic-oscillator thermodynamics
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A robust and efficient implicit solvation model for fast semiempirical methods
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Learning neural generative dynamics for molecular conformation generation
Xu, M., Luo, S., Bengio, Y., Peng, J. & Tang, J · 2021
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Conformer models and training datasets
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