Combining Multi-objective Evolutionary Algorithms with Deep Generative Models Towards Focused Molecular Design

[1]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.

[2]  Koji Tsuda,et al.  Population-based de novo molecule generation, using grammatical evolution , 2018, 1804.02134.

[3]  Dragos Horvath,et al.  De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping , 2019, J. Chem. Inf. Model..

[4]  S. Siva Sathya,et al.  Evolutionary algorithms for de novo drug design - A survey , 2015, Appl. Soft Comput..

[5]  Alán Aspuru-Guzik,et al.  Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules , 2016, ACS central science.

[6]  Frank Noé,et al.  Efficient multi-objective molecular optimization in a continuous latent space† †Electronic supplementary information (ESI) available: Details of the desirability scaling functions, high resolution figures and detailed results of the GuacaMol benchmark. See DOI: 10.1039/c9sc01928f , 2019, Chemical science.

[7]  Ryan-Rhys Griffiths,et al.  Constrained Bayesian optimization for automatic chemical design using variational autoencoders , 2019, Chemical science.

[8]  Jacob D. Durrant,et al.  AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization , 2020, Journal of Cheminformatics.

[9]  Thierry Kogej,et al.  Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks , 2017, ACS central science.

[10]  Johann Gasteiger,et al.  A Graph-Based Genetic Algorithm and Its Application to the Multiobjective Evolution of Median Molecules , 2004, J. Chem. Inf. Model..

[11]  David Rogers,et al.  Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..

[12]  M. Withnall,et al.  Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction , 2020, Journal of Cheminformatics.

[13]  Dmitry Vetrov,et al.  Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery. , 2018, Molecular pharmaceutics.

[14]  R. W. Hansen,et al.  Journal of Health Economics , 2016 .

[15]  Alexandre Varnek,et al.  Estimation of the size of drug-like chemical space based on GDB-17 data , 2013, Journal of Computer-Aided Molecular Design.

[16]  Alán Aspuru-Guzik,et al.  Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models , 2018, Frontiers in Pharmacology.

[17]  Ruili Huang,et al.  Tox21Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Chemicals and Drugs , 2016, Front. Environ. Sci..

[18]  Javier Del Ser,et al.  jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics , 2019, Swarm Evol. Comput..

[19]  G. V. Paolini,et al.  Quantifying the chemical beauty of drugs. , 2012, Nature chemistry.

[20]  Marjan Mernik,et al.  The impact of Quality Indicators on the rating of Multi-objective Evolutionary Algorithms , 2017, Appl. Soft Comput..