IUPHAR Database is the official database of the IUPHAR Committee on Receptor Nomenclature and Drug Classification. The paper is: Sharman JL, Benson HE, Pawson AJ, Lukito V, Mpamhanga CP, Bombail V, Davenport AP, Peters JA, Spedding M, Harmar AJ, and NC-IUPHAR. (2013) IUPHAR-DB: updated database content and new features. Nucl. Acids Res. 41 (Database Issue): D1083-8. We are grateful to the authors for curating and curating this resource, and thank them for allowing us to incorporate its structures in ZINC.
We assess the chemical diversity of a subset by clustering the molecules. First, we sort ligands by increasing molecular weight. Then, we use the SUBSET 1.0 algorithm ( Voigt JH, Bienfait B, Wang S, Nicklaus MC. JCICS, 2001, 41, 702-12) to progressively select compounds that differ from those previously selected by at least the Tanimoto cutoff, using ChemAxon default fingerprints. The resulting representatives have two interesting properties:
Tanimoto Cutoff Level | 60% | 70% | 80% | 90% | 100% |
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Number of Representatives | 823 | 1,075 | 1,280 | 1,514 | 2,344 |
We compute the physical properties of each molecule in the subset, and graph them below.
Download Calculated Physical Properties
Format | Reference(pH 7) | Mid(pH 6-8) | High(pH 8-9.5) | Low(pH 4.5-6) | Download Unix |
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SMILES | All | All | All | All | ||
MOL2 | All | All | All | All | Single Usual Metals All | Single Usual Metals All |
SDF | All | All | All | All | Single Usual Metals All | Single Usual Metals All |
Flexibase | 0 1 | All | All | All | Single Usual Metals All | Single Usual Metals All |