ArticleJournal of cheminformatics2017
ChemSAR: an online pipelining platform for molecular SAR modeling.
Article in Journal of cheminformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Integrated QSAR, Molecular Docking, ADMET Profiling, and Antioxidant Evaluation of Substituted Chromone and Aryloxyalkanoic Acid Derivatives as Potential CysLTPharmaceuticals (Basel, Switzerland) · 2026Article
- A case study of the application of AI to early stage drug discovery.Scientific reports · 2025Article
- From molecules to data: the emerging impact of chemoinformatics in chemistry.Journal of cheminformatics · 2025Review
- In Silico and In Vitro Studies of Terpenes from the Fabaceae Family Using the Phenotypic Screening Model against the SARS-CoV-2 Virus.Pharmaceutics · 2024Article
- ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization.Briefings in bioinformatics · 2024Article
- Bioactive Molecules from the Innate Immunity of Ascidians and Innovative Methods of Drug Discovery: A Computational Approach Based on Artificial Intelligence.Marine drugs · 2023Review
- From intuition to AI: evolution of small molecule representations in drug discovery.Briefings in bioinformatics · 2023Article
- Recent Advances in Machine-Learning-Based Chemoinformatics: A Comprehensive Review.International journal of molecular sciences · 2023Review
- Selene-Ethylenelacticamides andPathogens (Basel, Switzerland) · 2023Article
- Drug Discovery forInternational journal of molecular sciences · 2021Review
- Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.Molecular diversity · 2021Review
- Artificial intelligence to deep learning: machine intelligence approach for drug discovery.Molecular diversity · 2021Review
- Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace.Briefings in bioinformatics · 2021Review
- A review on machine learning approaches and trends in drug discovery.Computational and structural biotechnology journal · 2021Review
- Review
- Towards reproducible computational drug discovery.Journal of cheminformatics · 2020Review
- Methodology of aiQSAR: a group-specific approach to QSAR modelling.Journal of cheminformatics · 2019Article
- DeepScreening: a deep learning-based screening web server for accelerating drug discovery.Database : the journal of biological databases and curation · 2019Article
- ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database.Journal of cheminformatics · 2018Article
- PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.Journal of cheminformatics · 2018Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years, predictive models based on machine learning techniques have proven to be feasible and effective in drug discovery. However, to develop such a model, researchers usually have to combine multiple tools and undergo several different steps (e.g., RDKit or ChemoPy package for molecular descriptor calculation, ChemAxon Standardizer for structure preprocessing, scikit-learn package for model building, and ggplot2 package for statistical analysis and visualization, etc.). In addition, it may require strong programming skills to accomplish these jobs, which poses severe challenges for users without advanced training in computer programming. Therefore, an online pipelining platform that integrates a number of selected tools is a valuable and efficient solution that can meet the needs of related researchers.
resultsThis work presents a web-based pipelining platform, called ChemSAR, for generating SAR classification models of small molecules. The capabilities of ChemSAR include the validation and standardization of chemical structure representation, the computation of 783 1D/2D molecular descriptors and ten types of widely-used fingerprints for small molecules, the filtering methods for feature selection, the generation of predictive models via a step-by-step job submission process, model interpretation in terms of feature importance and tree visualization, as well as a helpful report generation system. The results can be visualized as high-quality plots and downloaded as local files.
conclusionChemSAR provides an integrated web-based platform for generating SAR classification models that will benefit cheminformatics and other biomedical users. It is freely available at: http://chemsar.scbdd.com . Graphical abstract .
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