Prospective performance evaluation of selected common virtual screening tools, case study: cyclooxygenase (COX) 1 and 2.
Open accessAbstract
Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors.
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In prospective VS studies against cyclooxygenases 1 and 2, the chance of a compound being truly active increases when more tools predicted it as active.
“For instance, Kaserer et al. (2015) applied CS on prospective VS studies against cyclooxygenases 1 and 2 and found that the chance of a compound to be truly active increases when more tools predicted it as active.”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Kaserer et al., 2015
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- Authors
- Kaserer, T., Temml, V., Kutil, Z., Vanek, T., Landa, P., & Schuster, D.
- Affiliations
- Universität Innsbruck (AT)
- Corresponding author
- Schuster, Daniela
- Venue
- European Journal of Medicinal Chemistry
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 96
- Pages
- 445-457
- ISSN
- 0223-5234 (ISSN-L)
- PMC
- PMC4444576
- OpenAlex
- W2077527914
- Cited by
- 23
- References
- 73
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2019: 3 · 2018: 4 · 2017: 2 · 2016: 6 · 2015: 2 · 2014: 1
- FWCI
- 5.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- European Journal of Medicinal Chemistry (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ASEP (submittedVersion, public-domain)
- Funders
- University of Innsbruck
- OeAD WTZ (CZ11/2011, CZ14/2013)
- Austrian Science Fund (P26782)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
- Health Sciences › Medicine › Pharmacology › Cholinesterase and Neurodegenerative Diseases
- Keywords
- virtual screening, cyclooxygenase, cyclooxygenase-1, cyclooxygenase-2, pharmacophore modeling, molecular docking, hit prediction, hit rate, cyclooxygenase inhibitors, lead candidate identification
- MeSH terms
- Dose-Response Relationship, Drug, Drug Evaluation, Preclinical, Humans, Models, Molecular, Structure-Activity Relationship, Molecular Structure, Cyclooxygenase Inhibitors, Cyclooxygenase 1, Cyclooxygenase 2
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