ArticleMolecules (Basel, Switzerland)2020
VAE-Sim: A Novel Molecular Similarity Measure Based on a Variational Autoencoder.
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Reliable Apparent Permeability Prediction Through Benchmarking, Stability, Uncertainty Quantification, and Explainable Machine Learning.CPT: pharmacometrics & systems pharmacology · 2026Article
- Quantum computing and the implementation of precision medicine.NPJ genomic medicine · 2025Review
- Hamiltonian diversity: effectively measuring molecular diversity by shortest Hamiltonian circuits.Journal of cheminformatics · 2024Article
- Evidence for the Role of the Mitochondrial ABC Transporter MDL1 in the Uptake of Clozapine and Related Molecules into the YeastPharmaceuticals (Basel, Switzerland) · 2024Article
- A Perspective on How Fibrinaloid Microclots and Platelet Pathology May be Applied in Clinical Investigations.Seminars in thrombosis and hemostasis · 2024Review
- Feature Reduction for Molecular Similarity Searching Based on Autoencoder Deep Learning.Biomolecules · 2022Article
- Strategies for structure elucidation of small molecules based on LC-MS/MS data from complex biological samples.Computational and structural biotechnology journal · 2022Review
- The use of deep learning technology in dance movement generation.Frontiers in neurorobotics · 2022Article
- MassGenie: A Transformer-Based Deep Learning Method for Identifying Small Molecules from Their Mass Spectra.Biomolecules · 2021Article
- Intelligent host engineering for metabolic flux optimisation in biotechnology.The Biochemical journal · 2021Review
- The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes.Molecules (Basel, Switzerland) · 2021Review
- Prediction of Chromatography Conditions for Purification in Organic Synthesis Using Deep Learning.Molecules (Basel, Switzerland) · 2021Article
- FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space.Molecules (Basel, Switzerland) · 2021Article
- Semi-supervised Hierarchical Drug Embedding in Hyperbolic Space.Journal of chemical information and modeling · 2020Article
- Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently.The Biochemical journal · 2020Review
- Structural Similarities between Some Common Fluorophores Used in Biology, Marketed Drugs, Endogenous Metabolites, and Natural Products.Marine drugs · 2020Article
- VAE-Sim: A Novel Molecular Similarity Measure Based on a Variational Autoencoder.Molecules (Basel, Switzerland) · 2020Article
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Authors and funding
5 authors.
Funding
Abstract
Molecular similarity is an elusive but core "unsupervised" cheminformatics concept, yet different "fingerprint" encodings of molecular structures return very different similarity values, even when using the same similarity metric. Each encoding may be of value when applied to other problems with objective or target functions, implying that a priori none are "better" than the others, nor than encoding-free metrics such as maximum common substructure (MCSS). We here introduce a novel approach to molecular similarity, in the form of a variational autoencoder (VAE). This learns the joint distribution p(z|x) where z is a latent vector and x are the (same) input/output data. It takes the form of a "bowtie"-shaped artificial neural network. In the middle is a "bottleneck layer" or latent vector in which inputs are transformed into, and represented as, a vector of numbers (encoding), with a reverse process (decoding) seeking to return the SMILES string that was the input. We train a VAE on over six million druglike molecules and natural products (including over one million in the final holdout set). The VAE vector distances provide a rapid and novel metric for molecular similarity that is both easily and rapidly calculated. We describe the method and its application to a typical similarity problem in cheminformatics.
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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.