Inspired by the seminal work of Waller, Segler & Preuss published in Nature in 2018 (1), Iktos decided to develop an AI-based retrosynthetic analysis technology as a complementary offer to its generative AI de novo drug design core business.
Initially designed following a comparable architecture, Spaya has been developed by combining state-of-the-art techniques reported in the literature (see below) and our own R&D endeavors.
References:
1) Segler, M. H. S., Preuss, M. and Waller, M. P. Planning chemical syntheses with deep neural networks and symbolic AI. Nature, 2018, 555, 604–610.
2) Coley, C. W., Jin, W., Rogers, L., Jamison, T. F., Jaakkola, T. S., Green, W. H., Barzilay, R., Jensen, K. F. A graph-convolutional neural network model for the prediction of chemical reactivity. Chem. Sci. 2019, 10, 370-377.
3) Coley, C. W., Rogers, L., Green, W. H., Jensen, K. F. Computer-assisted retrosynthesis based on molecular similarity. ACS Cent. Sci. 2017, 3, 12, 1237-1245.
4) Schwaller, P., Laino, T., Gaudin, T., Bolgar, P., Hunter, C. A., Bekas, C. and Lee A. A. Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction. ACS Cent. Sci. 2019, 5, 1572-1583.
5) Schneider, N., Stiefl, N. & Landrum, G. A. What’s what: The (nearly) definitive guide to reaction role assignment. Journal of chemical information and modeling. J. Chem. Inf. Model. 2016, 56, 2336-2346.
6) Smith, L. N. A disciplined approach to neural network hyper-parameters: Part 1–learning rate, batch size, momentum, and weight decay. arXiv 2018, DOI : arXiv:1803.09820v2.
7) Coley, C. W., Green W. H. & Jensen, K. F. Machine Learning in Computer-Aided Synthesis Planning. Acc. Chem. Res. 2018, 51, 1281-1289.
8) Ishida, S., Terayama, K., Kojima R., Takasu K. & Okuno, Y. Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional Networks. J. Chem. Inf. Model. 2019, 59, 5026-5033.
9) Schreck, J. S., Coley, C. W., Bishop, K. J. M. Learning Retrosynthetic Planning through Simulated Experience. ACS Cent. Sci. 2019, 5, 970-981.
10) Baylon, J. L., Cilfone N. A., Gulcher, J. R. & Chittenden, T. W. Enhancing Retrosynthetic Reaction Prediction with Deep Learning Using Multiscale Reaction Classification. J. Chem. Inf. Model. 2019, 59, 673-688.
11) Schwaller, P. & Laino, T. Data-Driven Learning Systems for Chemical Reaction Prediction: An Analysis of Recent Approaches. ACS Symposium Series, 2019, 1326, DOI : 10.1021/bk-2019-1326.ch004, ISBN13 : 9780841235052.
Data:
Spaya is currently running with Pistachio data, a database provided by NextMove Softwares. John Mayfield et al., [CINF:13] Pistachio: Search and faceting of large reaction databases. ACS Fall 2017.
Mcule, Chemspace, Chemspace, Key Organics, Otava/Chemtellect, eMolecules, MolPort, ChemDiv Apollo, Scientific, 1PlusChemical, Spirochem, A2B Chem, TCI chemicals, Life chemicals and Chembridge provide their libraries of commercial starting materials and updated data related to their commercial availability and pricing.
Packages:
Use of RDKit:
Landrum, G. RDKit: Open-source cheminformatics. 2006
Use of retrosim under MIT License:
Copyright (c) 2017 Connor Coley
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
Use of Indigo:
Copyright © 2009-2019 LifeSciences unit of EPAM Systems, Inc.
Indigo version 1.0.0 was released under GNU General Public License v3.0 Indigo version 1.4.0 was re-licensed under Apache License, Version 2.
This program is free software: You can redistribute it and/or modify it under the terms of the Apache License, Version 2.0.
Detailed license terms can be found at https://github.com/epam/Indigo/blob/master/LICENSE
Use of Smiles Drawer:
Current Version: 1.1.20 (Ballroom Blitz)under MIT license.
https://pubs.acs.org/doi/10.1021/acs.jcim.7b00425