ArticleJournal of cheminformatics2021
Molecular generation by Fast Assembly of (Deep)SMILES fragments.
Article in Journal of cheminformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- ChemBang: Expanding the Chemical Space Around Small Molecules.Molecular informatics · 2026Article
- Molecular Design with Artificial Intelligence: Progress and Perspectives for Small Molecules.Chemical reviews · 2026Review
- Generative Multiobjective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Design.Industrial & engineering chemistry research · 2026Article
- Artificial intelligence in drug discovery from advanced molecular representation to pipeline applications.Frontiers in bioinformatics · 2026Review
- Crossover operators for molecular graphs with an application to virtual drug screening.Journal of cheminformatics · 2025Article
- Article
- FOCUS on NOD2: Advancing IBD Drug Discovery with a User-Informed Machine Learning Framework.ACS medicinal chemistry letters · 2024Article
- MolPLA: a molecular pretraining framework for learning cores, R-groups and their linker joints.Bioinformatics (Oxford, England) · 2024Article
- t-SMILES: a fragment-based molecular representation framework for de novo ligand design.Nature communications · 2024Article
- Molecular fragmentation as a crucial step in the AI-based drug development pathway.Communications chemistry · 2024Review
- Harnessing Shannon entropy-based descriptors in machine learning models to enhance the prediction accuracy of molecular properties.Journal of cheminformatics · 2023Article
- 67 million natural product-like compound database generated via molecular language processing.Scientific data · 2023Article
- Advancing Rare-Earth Separation by Machine Learning.JACS Au · 2022Article
- Strategies for structure elucidation of small molecules based on LC-MS/MS data from complex biological samples.Computational and structural biotechnology journal · 2022Review
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2 authors.
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Abstract
backgroundIn recent years, in silico molecular design is regaining interest. To generate on a computer molecules with optimized properties, scoring functions can be coupled with a molecular generator to design novel molecules with a desired property profile.
resultsIn this article, a simple method is described to generate only valid molecules at high frequency ([Formula: see text] molecule/s using a single CPU core), given a molecular training set. The proposed method generates diverse SMILES (or DeepSMILES) encoded molecules while also showing some propensity at training set distribution matching. When working with DeepSMILES, the method reaches peak performance ([Formula: see text] molecule/s) because it relies almost exclusively on string operations. The "Fast Assembly of SMILES Fragments" software is released as open-source at https://github.com/UnixJunkie/FASMIFRA . Experiments regarding speed, training set distribution matching, molecular diversity and benchmark against several other methods are also shown.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.