Influence of LC retention data on antitumor acridinones' classification evaluated by factor analysis method

Area of Science:

• Medicinal Chemistry
• Cheminformatics
• Analytical Chemistry

Background:

• Acridinone derivatives are investigated for antitumor properties.
• Understanding structure-activity relationships is crucial for drug development.

Purpose of the Study:

• To apply factor analysis (FA) for classifying antitumor acridinones.
• To correlate chromatographic and physicochemical data with biological activity.

Main Methods:

• 19 acridinone derivatives were analyzed using reversed-phase high-performance liquid chromatography (RP-HPLC) across six systems.
• HPLC retention times, log kw, and molecular descriptors (including log P) were calculated.
• Factor analysis was performed on a combined dataset of 19x32 HPLC and molecular parameters.

Main Results:

• Factor analysis extracted three principal components explaining 93.09% of the data variance.
• Factor 1 was primarily influenced by HPLC retention data, while Factor 2 was influenced by lipophilicity parameters.
• The distribution of compounds based on the principal components correlated well with their chemical structures and antitumor activity.

Conclusions:

• Factor analysis is a viable method for classifying antitumor acridinones.
• HPLC retention and lipophilicity data are key determinants in the classification.
• The study provides insights into the structural basis of antitumor activity in acridinones.