Rationalizing Three-Dimensional Activity Landscapes and the Influence of Molecular Representations on Landscape Topology and the Formation of Activity Cliffs
Abstract
Activity landscapes are defined by potency and similarity distributions of active compounds and reflect the nature of structure-activity relationships (SARs). Three-dimensional (3D) activity landscapes are reminiscent of topographical maps and particularly intuitive representations of compound similarity and potency distributions. From their topologies, SAR characteristics can be deduced. Accordingly, idealized theoretical landscape models have been utilized to rationalize SAR features, but "true" 3D activity landscapes have not yet been described in detail. Herein we present a computational approach to derive approximate 3D activity landscapes for actual compound data sets and to analyze exemplary landscape representations. These activity landscapes are generated within a consistent reference frame so that they can be compared across different activity classes. We show that SAR features of compound data sets can be derived from the topology of landscape models. A notable correlation is observed between global SAR phenotypes, assigned on the basis of SAR discontinuity scoring, and characteristic landscape topologies. We also show that different molecular representations can substantially alter the topology of activity landscapes for a given data set and modulate the formation of activity cliffs, which represent the most prominent landscape features. Depending on the choice of molecular representations, compounds forming a steep activity cliff in a given landscape might be separated in another and no longer form a cliff. However, comparison of alternative activity landscapes makes it possible to focus on compound subsets having high SAR information content.
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- Authors
- Peltason, L., Iyer, P., & Bajorath, J.
- Affiliations
- University of Bonn (DE)
- Corresponding author
- Bajorath, Jürgen
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-05-05
- Volume
- 50
- Issue
- 6
- Pages
- 1021-1033
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2032733199
- Cited by
- 85
- References
- 26
- Citations by year
- 2026: 1 · 2023: 1 · 2022: 5 · 2021: 1 · 2020: 8 · 2019: 3 · 2018: 4 · 2017: 3 · 2016: 1 · 2015: 4 · 2014: 7 · 2013: 16 · 2012: 13
- FWCI
- 15.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Chemical Information and Modeling (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
- Keywords
- activity landscape, structure-activity relationship, activity cliffs, molecular representation, landscape topology, molecular similarity, landscape models
- MeSH terms
- Computer Graphics, Drug Evaluation, Preclinical, Humans, Quality Control, Structure-Activity Relationship
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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