Molecular Complexity: You Know It When You See It.

Area of Science:

• Medicinal Chemistry
• Drug Discovery
• Computational Chemistry

Background:

• Molecular complexity (MC) is crucial in synthetic organic chemistry and pharmaceutical research.
• Quantifying MC in drug discovery is challenging, with existing metrics often correlating to molecular weight.
• A universal definition for MC remains elusive.

Purpose of the Study:

• To evaluate the utility of the spacial score (SPS) and its normalized version (nSPS) as metrics for molecular complexity.
• To analyze trends in nSPS for approved drugs over time.
• To determine if nSPS correlates with drug innovation, bioactivity, or bioavailability.

Main Methods:

• Calculated the spacial score (SPS) and normalized spacial score (nSPS) using factors like atom hybridization and stereoisomerism.
• Analyzed nSPS trends across approved drugs spanning eight decades.
• Correlated nSPS values with drug innovation, target bioactivity, and oral bioavailability.

Main Results:

• The nSPS metric did not show significant changes in molecular complexity for approved drugs over eight decades.
• nSPS failed to capture drug innovation during the analyzed period.
• The majority of approved drugs fall within an nSPS range of 10-20, but this does not correlate with bioactivity or bioavailability.

Conclusions:

• The nSPS metric, while empirically precise, does not effectively capture molecular complexity trends or drug innovation.
• nSPS does not correlate with essential drug properties, limiting its utility in drug discovery.
• Further development of MC metrics is needed to align with chemical intuition and practical applications.