qrci 0.1.3

Quantitative Ring Complexity Index

QRCI

A Quantitative Ring Complexity Index for Profiling Ring Topology and Chemical Diversity

Requirements

Python==3.13.2
rdkit==2025.03.2
scipy==1.15.1

QRCI calculation

from QRCI.QRCI import QRCICalculator, get_QRCIproperties
from QRCI.RCI import RCICalculator

qrci_calc = QRCICalculator(weights='mean')
score_mean = qrci_calc('C1=CCOCc2cc(ccc2OCCN2CCCC2)Nc2nccc(n2)-c2cccc(c2)COC1')
print(f"QRCI(default/mean weights): {score_mean:.4f}")
#QRCI(default/mean weights): 4.0330

***************************************************************************************
mol = Chem.MolFromSmiles('C1=CCOCc2cc(ccc2OCCN2CCCC2)Nc2nccc(n2)-c2cccc(c2)COC1')
props = get_qrci_properties(mol)
print(props)
#QRCIproperties(nAromHetero=1, nAromCarbo=2, nAliHetero=2, nAliCarbo=0, nSatHetero=1, nSatCarbo=0, nMacrocycles=1, TRS=41, nRingAtom=32, nFusedRing=4, SF=1.0857142857142856)

License

Code is released under MIT LICENSE.

Cite

• Gasteiger, J. and Jochum, C., 1979. An algorithm for the perception of synthetically important rings. Journal of Chemical Information and Computer Sciences, 19(1), pp.43-48.
• Ertl, P., Schuffenhauer, A. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. J Cheminform 1, 8 (2009). https://doi.org/10.1186/1758-2946-1-8
• Krzyzanowski, A., Pahl, A., Grigalunas, M., & Waldmann, H. (2023). Spacial Score─A Comprehensive Topological Indicator for Small-Molecule Complexity. Journal of medicinal chemistry, 66(18), 12739–12750. https://doi.org/10.1021/acs.jmedchem.3c00689
• Wang J, Xu K, Ma T, Zhang X, Ma P, Li C, et al. A Quantitative Ring Complexity Index for Profiling Ring Topology and Chemical Diversity. ChemRxiv. 2025; doi:10.26434/chemrxiv-2025-mlqwl-v2 This content is a preprint and has not been peer-reviewed.