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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
Published on: June 4, 2021
Quantifying structure and performance diversity for sets of small molecules comprising small-molecule screening
Paul A Clemons1, J Anthony Wilson, Vlado Dančík
1Broad Institute of Harvard and MIT, 7 Cambridge Center, Cambridge, MA 02142, USA. pclemons@broadinstitute.org
Summary
Compound sets from various sources exhibit distinct protein-binding behaviors linked to stereochemical complexity. A new measure quantifies performance diversity, aiding synthetic chemists in building effective screening collections.
Area of Science:
- Medicinal Chemistry
- Chemical Biology
- Drug Discovery
Background:
- Compound libraries from commercial, academic, and natural sources display varied protein-binding profiles.
- These binding behaviors correlate with the stereochemical complexity of the small molecules.
Purpose of the Study:
- To characterize structural properties and biological performance diversity across different compound sets.
- To develop a quantitative framework for assessing and optimizing screening collection design.
Main Methods:
- Extensive characterization of physicochemical properties and 3D shapes of predicted conformers.
- Introduction of an information-theoretic measure to assess performance diversity with specificity constraints.
- Application of the measure to protein-binding and functional assay data (ChemBank).
Main Results:
- Differences in compound sets' properties and biological performance were observed, dependent on molecular descriptors.
- The developed measure provides a group-based assessment of compound subsets, moving beyond individual active compounds.
- Performance diversity of compound sets remained stable across various property values in both protein-binding and functional assays.
Conclusions:
- The study provides a quantitative framework for prioritizing compound selection in screening library synthesis.
- Understanding structure-activity relationships and performance diversity is crucial for efficient synthetic chemistry resource allocation.
- This approach aids in rationally designing more effective screening collections for biological discovery.
