NovoFLAP: A ligand-based de novo design approach for the generation of medicinally relevant ideas
| Autor: | Charles L. Lerman, Brian B. Masek, James R. Damewood |
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| Rok vydání: | 2010 |
| Předmět: |
Computer science
General Chemical Engineering media_common.quotation_subject Evolutionary algorithm Context (language use) Library and Information Sciences Machine learning computer.software_genre Ligands Drug Delivery Systems Computer Simulation Function (engineering) media_common Serotonin Plasma Membrane Transport Proteins Molecular Structure business.industry Design tool General Chemistry Ligand (biochemistry) Combinatorial chemistry Computer Science Applications Pyrimidines Biological target Drug Design Pyrazoles Artificial intelligence Pharmacophore business computer Algorithms |
| Zdroj: | Journal of chemical information and modeling. 50(7) |
| ISSN: | 1549-960X |
| Popis: | NovoFLAP is a computer-aided de novo design tool that generates medicinally relevant ideas for ligand-based projects. The approach combines an evolutionary algorithm (EA-Inventor) with a powerful ligand-based scoring function that uses both molecular shape and pharmacophore features in a multiconformational context (FLAP). We demonstrate that NovoFLAP can generate novel ideas that are not only appealing to design scientists but are also validated by comparison to compounds known to demonstrate activity at the desired biological target. NovoFLAP provides a novel computer-aided design technique that can be used to generate ideas that maintain desirable molecular attributes, such as activity at the primary biological target, while offering opportunities to surmount additional design challenges. Application to the design of the first nonbasic 5HT(1B) antagonist is presented. |
| Databáze: | OpenAIRE |
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