How to Recognize and Workaround Pitfalls in QSAR Studies: A Critical Review
Abstract
Quantitative Structure-Activity Relationships (QSAR) are based on the hypothesis that changes in molecular structure reflect proportional changes in the observed response or biological activity. In order to successfully conduct QSAR studies certain conditions have to be met that are not frequently reported in the literature. This suggests that some authors are not aware of the principle flaws, occasional shortcomings, and circumstantial downsides of QSAR methods. The present paper focuses on prerequisites to set up correct models and on limitations of model applications. Their implications are systematically described and illustrated as pitfalls that have strong implications in QSAR, and possible solutions are suggested. The paper is focused on small scale 2D- and 3D-QSAR studies for lead optimization. The work is enriched with comprehensive comments and non-mathematical explanations for the computer practitioner in Medicinal Chemistry.
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References 8 · Cited by 197
- Authors
- Scior, T., Medina-Franco, J. L., Do, Q.-T., Martinez-Mayorga, K., Yunes Rojas, J. A., & Bernard, P.
- Affiliations
- Benemérita Universidad Autónoma de Puebla (MX)
- Corresponding author
- Bernard, P.
- ORCID
- Scior, T.
- Venue
- Current Medicinal Chemistry
- Publisher
- Bentham Science Publishers Ltd.
- Published
- 2009-11
- Volume
- 16
- Issue
- 32
- Pages
- 4297-4313
- ISSN
- 0929-8673 (ISSN-L)
- OpenAlex
- W2134450203
- Cited by
- 197
- References
- 8
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 5 · 2023: 9 · 2022: 7 · 2021: 13 · 2020: 10 · 2019: 13 · 2018: 11 · 2017: 4 · 2016: 12 · 2015: 14 · 2014: 24 · 2013: 19 · 2012: 22
- FWCI
- 14.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Medicinal Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- QSAR, model validation, 2D-QSAR, 3D-QSAR, lead optimization, molecular descriptors, bioactivity prediction
- MeSH terms
- Algorithms, Models, Molecular, Regression Analysis, Least-Squares Analysis, Quantitative Structure-Activity Relationship, Principal Component Analysis
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