Artificial Intelligence in Drug Design
Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep neural networks or recurrent networks drive this area. Numerous applications in property or activity predictions like physicochemical and ADMET properties have recently appeared...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Molecules |
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| Online Access: | http://www.mdpi.com/1420-3049/23/10/2520 |
| _version_ | 1818535767348084736 |
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| author | Gerhard Hessler Karl-Heinz Baringhaus |
| author_facet | Gerhard Hessler Karl-Heinz Baringhaus |
| author_sort | Gerhard Hessler |
| collection | DOAJ |
| description | Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep neural networks or recurrent networks drive this area. Numerous applications in property or activity predictions like physicochemical and ADMET properties have recently appeared and underpin the strength of this technology in quantitative structure-property relationships (QSPR) or quantitative structure-activity relationships (QSAR). Artificial intelligence in de novo design drives the generation of meaningful new biologically active molecules towards desired properties. Several examples establish the strength of artificial intelligence in this field. Combination with synthesis planning and ease of synthesis is feasible and more and more automated drug discovery by computers is expected in the near future. |
| first_indexed | 2024-12-11T18:29:18Z |
| format | Article |
| id | doaj.art-faffc5971b304774ac8a7c501f19a709 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-12-11T18:29:18Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-faffc5971b304774ac8a7c501f19a7092022-12-22T00:54:58ZengMDPI AGMolecules1420-30492018-10-012310252010.3390/molecules23102520molecules23102520Artificial Intelligence in Drug DesignGerhard Hessler0Karl-Heinz Baringhaus1R&D, Integrated Drug Discovery, Industriepark Hoechst, 65926 Frankfurt am Main, GermanyR&D, Industriepark Hoechst, 65926 Frankfurt am Main, GermanyArtificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep neural networks or recurrent networks drive this area. Numerous applications in property or activity predictions like physicochemical and ADMET properties have recently appeared and underpin the strength of this technology in quantitative structure-property relationships (QSPR) or quantitative structure-activity relationships (QSAR). Artificial intelligence in de novo design drives the generation of meaningful new biologically active molecules towards desired properties. Several examples establish the strength of artificial intelligence in this field. Combination with synthesis planning and ease of synthesis is feasible and more and more automated drug discovery by computers is expected in the near future.http://www.mdpi.com/1420-3049/23/10/2520artificial intelligencedeep learningneural networksproperty predictionquantitative structure-activity relationship (QSAR)quantitative structure-property prediction (QSPR)de novo design |
| spellingShingle | Gerhard Hessler Karl-Heinz Baringhaus Artificial Intelligence in Drug Design Molecules artificial intelligence deep learning neural networks property prediction quantitative structure-activity relationship (QSAR) quantitative structure-property prediction (QSPR) de novo design |
| title | Artificial Intelligence in Drug Design |
| title_full | Artificial Intelligence in Drug Design |
| title_fullStr | Artificial Intelligence in Drug Design |
| title_full_unstemmed | Artificial Intelligence in Drug Design |
| title_short | Artificial Intelligence in Drug Design |
| title_sort | artificial intelligence in drug design |
| topic | artificial intelligence deep learning neural networks property prediction quantitative structure-activity relationship (QSAR) quantitative structure-property prediction (QSPR) de novo design |
| url | http://www.mdpi.com/1420-3049/23/10/2520 |
| work_keys_str_mv | AT gerhardhessler artificialintelligenceindrugdesign AT karlheinzbaringhaus artificialintelligenceindrugdesign |