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Published on: March 3, 2021
Design and evaluation of bonded atom pair descriptors
Hany E A Ahmed1, Martin Vogt, Jürgen Bajorath
1Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universitat Bonn, Dahlmannstrasse 2, D-53113 Bonn, Germany.
Journal of Chemical Information and Modeling
|March 18, 2010
Summary
Researchers developed new bonded atom pairs, a type of molecular descriptor, to capture short-range chemical environment information. These descriptors enhance similarity searching performance, complementing existing methods for drug discovery.
Area of Science:
- Computational chemistry
- Cheminformatics
- Medicinal chemistry
Background:
- Atom pairs are established topological descriptors used in 2D fingerprint searching.
- These descriptors are widely utilized for molecular similarity assessment.
Purpose of the Study:
- Introduce a novel type of atom pair descriptor: bonded atom pairs.
- Evaluate the performance of bonded atom pairs in capturing molecular structural information and enhancing similarity searching.
Main Methods:
- Designed bonded atom pairs incorporating element type, hybridization, and aromaticity.
- Systematically generated sets of 117 and 159 bonded atom pair descriptors.
- Analyzed atom pair distribution and frequency in relation to compound selectivity.
- Compared the performance of bonded atom pairs against standard atom pairs and fragment fingerprints in similarity searches.
Main Results:
- Bonded atom pairs exclusively capture short-range atom environment information.
- Both conventional and bonded atom pairs provide complementary structural insights.
- Bonded atom pairs demonstrate equal or superior performance compared to standard atom pairs and fragment fingerprints in similarity searching.
Conclusions:
- Bonded atom pairs represent a valuable extension to the existing toolkit of topological molecular descriptors.
- The new descriptors offer complementary information, improving molecular similarity assessments.
- This advancement has implications for optimizing virtual screening and drug design processes.
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