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High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules.
Land, A. H.; Doig, A. G. An Automatic Method of Solving Discrete Programming Problems. Econometrica 1960
1960
Earlier work this paper cites.
Little, J. D. C.; Murty, K. G.; Sweeney, D. W.; Karel, C. An Algorithm for the Traveling Salesman Problem. Operations Research 1963
1963
Earlier work this paper cites.
Nix, D. A.; Weigend, A. S. Estimating the mean and variance of the target probability distribution. Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN’94). 1994; pp 55–60 vol.1
1994
Earlier work this paper cites.
Hudson, B. D.; Hyde, R. M.; Rahr, E.; Wood, J.; Osman, J. Parameter Based Methods for Compound Selection from Chemical Databases. Quantitative Structure-Activity Relationships 1996
1996
Earlier work this paper cites.
Butina, D. Unsupervised Data Base Clustering Based on Daylight’s Fingerprint and Tanimoto Similarity: A Fast and Automated Way To Cluster Small and Large Data Sets. Journal of Chemical Information and Computer Sciences 1999
1999
Earlier work this paper cites.
Gobbi, A.; Lee, M.-L. DISE: Directed Sphere Exclusion. Journal of Chemical Information and Computer Sciences 2003
2003
Earlier work this paper cites.
Srinivas, N.; Krause, A.; Kakade, S. M.; Seeger, M. W. Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting. IEEE Transactions on Information Theory 2012
2012
Earlier work this paper cites.
Czechtizky, W.; Dedio, J.; Desai, B.; Dixon, K.; Farrant, E.; Feng, Q.; Morgan, T.; Parry, D. M.; Ramjee, M. K.; Selway, C. N.; Schmidt, T.; Tarver, G. J.; Wright, A. G. Integrated Synthesis and Testing of Substituted Xanthine Based DPP4 Inhibitors: Application to Drug Discovery. ACS Medicinal Chemistry Letters 2013
2013
Earlier work this paper cites.
Seko, A.; Maekawa, T.; Tsuda, K.; Tanaka, I. Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids. Physical Review B 2014
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Pyzer-Knapp, E. O.; Suh, C.; Gómez-Bombarelli, R.; Aguilera-Iparraguirre, J.; Aspuru-Guzik, A. What Is High-Throughput Virtual Screening? A Perspective from Organic Materials Discovery. Annual Review of Materials Research 2015
2015
Earlier work this paper cites.
Alhossary, A.; Handoko, S. D.; Mu, Y.; Kwoh, C.-K. Fast, accurate, and reliable molecular docking with QuickVina 2. Bioinformatics 2015
2015
Earlier work this paper cites.
Williams, K.; Bilsland, E.; Sparkes, A.; Aubrey, W.; Young, M.; Soldatova, L. N.; De Grave, K.; Ramon, J.; de Clare, M.; Sirawaraporn, W.; Oliver, S. G.; King, R. D. Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases. Journal of The Royal Society Interface 2015
2015
Earlier work this paper cites.
Reker, D.; Schneider, G. Active-learning strategies in computer-assisted drug discovery. Drug Discovery Today 2015
2015
Earlier work this paper cites.
Seko, A.; Togo, A.; Hayashi, H.; Tsuda, K.; Chaput, L.; Tanaka, I. Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization. Physical Review Letters 2015
2015
Earlier work this paper cites.
Xue, D.; Balachandran, P. V.; Hogden, J.; Theiler, J.; Xue, D.; Lookman, T. Accelerated search for materials with targeted properties by adaptive design. Nature Communications 2016
2016
Cited alongside, same era.
Balachandran, P. V.; Xue, D.; Theiler, J.; Hogden, J.; Lookman, T. Adaptive Strategies for Materials Design using Uncertainties. Scientific Reports 2016
2016
Cited alongside, same era.
Svensson, F.; Norinder, U.; Bender, A. Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction. Journal of Chemical Information and Modeling 2017
2017
Cited alongside, same era.
Frazier, P. I. A Tutorial on Bayesian Optimization. arXiv:1807.02811 [cs, math, stat] 2018
2018
Cited alongside, same era.
Pyzer-Knapp, E. O. Bayesian optimization for accelerated drug discovery. IBM Journal of Research and Development 2018
2020
Later among the works it cites.
2020
Later among the works it cites.
2020
Later among the works it cites.
2020
Later among the works it cites.
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2018
Cited alongside, same era.
Yuan, R.; Liu, Z.; Balachandran, P. V.; Xue, D.; Zhou, Y.; Ding, X.; Sun, J.; Xue, D.; Lookman, T. Accelerated Discovery of Large Electrostrains in BaTiO3-Based Piezoelectrics Using Active Learning. Advanced Materials 2018
2018
Cited alongside, same era.
Ahmed, L.; Georgiev, V.; Capuccini, M.; Toor, S.; Schaal, W.; Laure, E.; Spjuth, O. Efficient iterative virtual screening with Apache Spark and conformal prediction. Journal of Cheminformatics 2018
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Lyu, J.; Wang, S.; Balius, T. E.; Singh, I.; Levit, A.; Moroz, Y. S.; O’Meara, M. J.; Che, T.; Algaa, E.; Tolmachova, K.; Tolmachev, A. A.; Shoichet, B. K.; Roth, B. L.; Irwin, J. J. Ultra-large library docking for discovering new chemotypes. Nature 2019
2019
Cited alongside, same era.
Elton, D. C.; Boukouvalas, Z.; Fuge, M. D.; Chung, P. W. Deep learning for molecular design—a review of the state of the art. Molecular Systems Design & Engineering 2019
2019
Cited alongside, same era.
Yang, K.; Swanson, K.; Jin, W.; Coley, C.; Eiden, P.; Gao, H.; Guzman-Perez, A.; Hopper, T.; Kelley, B.; Mathea, M.; Palmer, A.; Settels, V.; Jaakkola, T.; Jensen, K.; Barzilay, R. Analyzing Learned Molecular Representations for Property Prediction. Journal of Chemical Information and Modeling 2019
2019
Cited alongside, same era.
Hirschfeld, L.; Swanson, K.; Yang, K.; Barzilay, R.; Coley, C. W. Uncertainty Quantification Using Neural Networks for Molecular Property Prediction. Journal of Chemical Information and Modeling 2020
2020
Later among the works it cites.
Gentile, F.; Fernandez, M.; Ban, F.; Ton, A.-T.; Mslati, H.; Perez, C. F.; Leblanc, E.; Yaacoub, J. C.; Gleave, J.; Stern, A.; Wong, B.; Jean, F.; Strynadka, N.; Cherkasov, A. Automated discovery of noncovalent inhibitors of SARS-CoV-2 main protease by consensus Deep Docking of 40 billion small molecules. Chemical Science 2021
2021
Later among the works it cites.
Coley, C. W. Defining and Exploring Chemical Spaces. Trends in Chemistry 2021
2021
Later among the works it cites.
Graff, D. E.; Shakhnovich, E. I.; Coley, C. W. Accelerating high-throughput virtual screening through molecular pool-based active learning. Chemical Science 2021
2021
Later among the works it cites.
Yang, Y.; Yao, K.; Repasky, M. P.; Leswing, K.; Abel, R.; Shoichet, B. K.; Jerome, S. V. Efficient Exploration of Chemical Space with Docking and Deep Learning. Journal of Chemical Theory and Computation 2021
2021
Later among the works it cites.
Kalliokoski, T. Machine Learning Boosted Docking (HASTEN): An Open-source Tool To Accelerate Structure-based Virtual Screening Campaigns. Molecular Informatics 2021
2021
Later among the works it cites.
Martin, L. State of the Art Iterative Docking with Logistic Regression and Morgan Fingerprints. ChemRxiv 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
Luttens, A. et al. Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses. Journal of the American Chemical Society 2022
2022
Closest in time.
REAL Space - Enamine. https://enamine.net/compound-collections/real-compounds/real-space-navigator , Accessed 05/03/2022
2022
Closest in time.
Bilodeau, C.; Jin, W.; Jaakkola, T.; Barzilay, R.; Jensen, K. F. Generative models for molecular discovery: Recent advances and challenges. WIREs Computational Molecular Science 2022
2022
Closest in time.