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Ualign: pushing the limit of template-free retrosynthesis prediction with unsupervised SMILES alignment
MotivationRetrosynthesis planning poses a formidable challenge in the organic chemical industry, particularly in pharmaceuticals. Single-step...
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RetroRanker: leveraging reaction changes to improve retrosynthesis prediction through re-ranking
Retrosynthesis is an important task in organic chemistry. Recently, numerous data-driven approaches have achieved promising results in this task....
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G 2Retro as a two-step graph generative models for retrosynthesis predictionRetrosynthesis is a procedure where a target molecule is transformed into potential reactants and thus the synthesis routes can be identified....
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Improving the performance of models for one-step retrosynthesis through re-ranking
AbstractRetrosynthesis is at the core of organic chemistry. Recently, the rapid growth of artificial intelligence (AI) has spurred a variety of novel...
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AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application
We present an updated overview of the AiZynthFinder package for retrosynthesis planning. Since the first version was released in 2020, we have added...
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Critical assessment of synthetic accessibility scores in computer-assisted synthesis planning
Modern computer-assisted synthesis planning tools provide strong support for this problem. However, they are still limited by computational...
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Efficient retrosynthetic planning with MCTS exploration enhanced A* search
Retrosynthetic planning, which aims to identify synthetic pathways for target molecules from starting materials, is a fundamental problem in...
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Machine learning-enabled retrobiosynthesis of molecules
Retrobiosynthesis provides an effective and sustainable approach to producing functional molecules. The past few decades have witnessed a rapid...
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From theory to experiment: transformer-based generation enables rapid discovery of novel reactions
Deep learning methods, such as reaction prediction and retrosynthesis analysis, have demonstrated their significance in the chemical field. However,...
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AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry
AbstractThis paper presents AutoTemplate, an innovative data preprocessing protocol, addressing the crucial need for high-quality chemical reaction...
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Reaction intermediates in the synthesis of colloidal nanocrystals
Over the past 40 years, scientists have developed routes to synthesize colloidal nanocrystals of different compositions and with tunable size and...
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Total Synthesis of Marine Macrolides
Recent progress (2002–2005) of total syntheses of bioactive marine macrolides, lasonolide A, zampanolide, dactylolide, and leucascandrolide A, was...
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Integrating synthetic accessibility with AI-based generative drug design
Generative models are frequently used for de novo design in drug discovery projects to propose new molecules. However, the question of whether or not...
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Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization
Tokenization is an important preprocessing step in natural language processing that may have a significant influence on prediction quality. This...
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Bringing Photosynthesis 2.0 to Life
Can we redesign the central operating system of the global carbon cycle? Natural photosynthesis provides the blueprint for the sustainable capture...
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Total Synthesis of Avenaol
Avenaol is a terpene with a unique all-cis cyclopropane in which all bulky substituents are oriented in the same direction. It is categorized into a...
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DeepSA: a deep-learning driven predictor of compound synthesis accessibility
With the continuous development of artificial intelligence technology, more and more computational models for generating new molecules are being...
