The relation between molecular connectivity and gas chromatographic retention data

Area of Science:

• Quantitative Structure-Property Relationships (QSPR)
• Cheminformatics
• Chromatography

Background:

• Gas chromatographic retention time (Rt) is a crucial parameter in chemical analysis.
• Predictive models for Rt can streamline compound identification and separation.
• Topological indices offer a way to quantify molecular structure for predictive modeling.

Purpose of the Study:

• To evaluate the utility of the molecular connectivity (chi) index for predicting gas chromatographic retention times (Rt).
• To establish correlations between molecular connectivity indices and Rt for diverse chemical compound classes.

Main Methods:

• Multiple regression analysis was employed to correlate molecular connectivity indices with log Rt.
• The first-order connectivity index (1chi) and valence connectivity index (vchi) were utilized.
• Data from aliphatic hydrocarbons, aldehydes, alcohols, and drug molecules (amphetamines, barbiturates, phenothiazines) were analyzed.

Main Results:

• One-parameter linear equations using 1chi showed good correlation with log Rt for hydrocarbons and aldehydes.
• Aliphatic alcohols required the addition of the vchi parameter for satisfactory correlation.
• One-parameter 1chi equations also yielded good correlations for amphetamines, barbiturates, and phenothiazines.

Conclusions:

• The molecular connectivity (chi) index is a valuable tool for predicting gas chromatographic retention times.
• The predictive power of chi indices can be enhanced by incorporating additional parameters like vchi when necessary.
• These findings support the application of topological indices in chromatographic data analysis and QSPR studies.