Quantifying Functional-Group-like Structural Fragments in Molecules and Its Applications in Drug Design

Area of Science:

• Computational Chemistry
• Medicinal Chemistry
• Drug Discovery

Background:

• Defining functional groups is essential for predicting molecular properties and reactivity.
• Existing methods lack established reactivity-based definitions for functional groups.

Purpose of the Study:

• To develop a novel approach for defining functional groups based on reactivity parameters.
• To quantify structural fragments and their associated reactivity within organic molecules.

Main Methods:

• Designed predefined structural fragments with reactivity parameters (electron conjugation, ring strain).
• Utilized bond orders and atom connectivities to quantify fragment presence from molecular coordinates.
• Assessed model effectiveness via case studies including COX1/COX2 inhibitor grouping and LD50/aqueous solubility predictions.

Main Results:

• The structural fragment-based model demonstrated competitive performance for predicting rat oral LD50.
• The approach significantly outperformed traditional fingerprint-based models in predicting aqueous solubility (log(S)).

Conclusions:

• This new method provides a robust framework for defining functional groups based on reactivity.
• The fragment-based approach offers advantages over traditional methods for specific chemical property predictions and drug screening.