skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

A two-layer mono-objective algorithm based on guided optimization to reduce the computational cost in virtual screening

Scientific reports, 2022-07, Vol.12 (1), p.12769-12769, Article 12769 [Peer Reviewed Journal]

The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-16913-w ;PMID: 35896716

Full text available

Citations Cited by
  • Title:
    A two-layer mono-objective algorithm based on guided optimization to reduce the computational cost in virtual screening
  • Author: Ferrández, Miriam R ; Puertas-Martín, Savíns ; Redondo, Juana L ; Pérez-Sánchez, Horacio ; Ortigosa, Pilar M
  • Subjects: Accuracy ; Algorithms ; Computer applications ; Cost control ; COVID-19 ; Electrostatic properties ; Exploitation ; Ligands ; Optimization ; Population ; Software
  • Is Part Of: Scientific reports, 2022-07, Vol.12 (1), p.12769-12769, Article 12769
  • Description: Abstract Virtual screening methods focus on searching molecules with similar properties to a given compound. Molecule databases are made up of large numbers of compounds and are constantly increasing. Therefore, fast and efficient methodologies and tools have to be designed to explore them quickly. In this context, ligand-based virtual screening methods are a well-known and helpful tool. These methods focus on searching for the most similar molecules in a database to a reference one. In this work, we propose a new tool called 2L-GO-Pharm, which requires less computational effort than OptiPharm, an efficient and robust piece of software recently proposed in the literature. The new-implemented tool maintains or improves the quality of the solutions found by OptiPharm, and achieves it by considerably reducing the number of evaluations needed. Some of the strengths that help 2L-GO-Pharm enhance searchability are the reduction of the search space dimension and the introduction of some circular limits for the angular variables. Furthermore, to ensure a trade-off between exploration and exploitation of the search space, it implements a two-layer strategy and a guided search procedure combined with a convergence test on the rotation axis. The performance of 2L-GO-Pharm has been tested by considering two different descriptors, i.e. shape similarity and electrostatic potential. The results show that it saves up to 87.5 million evaluations per query molecule.
  • Publisher: London: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 2045-2322
    EISSN: 2045-2322
    DOI: 10.1038/s41598-022-16913-w
    PMID: 35896716
  • Source: ProQuest Databases
    PubMed Central
    DOAJ: Directory of Open Access Journals
    Coronavirus Research Database
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait