Cruz, N.C., Puertas-Martín, S., Redondo, J.L. et al. (1 more author) (2023) An effective solution for drug discovery based on the Tangram meta-heuristic and compound filtering. Informatica, 34 (4). pp. 743-769. ISSN 0868-4952
Abstract
Ligand-Based Virtual Screening accelerates and cheapens the design of new drugs. However, it needs efficient optimizers because of the size of compound databases. This work proposes a new method called Tangram CW. The proposal also encloses a knowledge-based filter of compounds. Tangram CW achieves comparable results to the state-of-the-art tools OptiPharm and 2L-GO-Pharm using about a tenth of their computational budget without filtering. Activating it discards more than two thirds of the database while keeping the desired compounds. Thus, it is possible to consider molecular flexibility despite increasing the options. The implemented software package is public.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Vilnius University. Open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
Keywords: | virtual screening; shape similarity; meta-heuristic; knowledge-based filtering; parallel computing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Feb 2025 09:15 |
Last Modified: | 20 Feb 2025 09:15 |
Status: | Published |
Publisher: | Vilnius University Press |
Refereed: | Yes |
Identification Number: | 10.15388/23-infor535 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:223442 |