ArticleMolecular diversity2019
Quasi-SMILES: quantitative structure-activity relationships to predict anticancer activity.
Article in Molecular diversity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.International journal of molecular sciences · 2021Article
- Predictive QSAR modeling for the antioxidant activity of natural compounds derivatives based on Monte Carlo method.Molecular diversity · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Reliable prediction of anticancer potential of different substances for different cells using unambiguous algorithms is attractive alternative of experimental investigation of impacts of various anticancer agents to various cells. Quasi-SMILES is a sequence of symbols, which represents all available eclectic data, i.e. not only molecular structure, but also different conditions, which can have influence on examined endpoint (e.g. kinds of cells: human breast; human colon; human liver; human lung). In this work, quasi-SMILES have been used to establish predictive models for anticancer activity isoquinoline quinones related to different cells. Descriptor calculated with optimal correlation weights of different fragments of quasi-SMILES defined by the Monte Carlo technique is used to predict pIC50 as a mathematical function of molecular structure and kinds of cells. The using of the so-called index of ideality of correlation for optimization by the Monte Carlo method improves predictive potential of the model. The statistical quality of the models based on correlation weights of fragments of quasi-SMILES is good. The range of correlation coefficient between experimental and calculated pIC50 for external validation set is 0.76-0.89. The statistical stable promoters for increase and for decrease in pIC50 are established. These models can be used to improve quality of pharmaceutical agents. These computational experiments can be reproduced with available on the Internet software ( http://www.insilico.eu/coral ).
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