Quantitative structure retention relationship (QSRR) approach for assessment of chromatographic behavior of antiviral drugs in the development of liquid chromatographic method

Abstract

A quantitative structure-retention relationship (QSRR) model has been developed and experimentally verified for the prediction of retention behavior of antiviral drugs in the reversed-phased liquid chromatography technique. The multiple linear regression (MLR) based QSRR model was derived using molecular descriptors. The molecular descriptors were calculated using HyperChem, ChemAxon, and ACD/labs software, whilst the QSRR-Automator was used to correlate the variables. The cross/external and experimental validations were done for the QSRR model. The model predicted the retention time (t_R) for five antiviral drugs, viz. darunavir, emtricitabine, efavirenz, lamivudine, and tenofovir disoproxil fumarate (TDF), then verified on C₁₈ column. The model significantly correlated (r² > 0.9) the retention time (log10t_R) to hydrophobic fragmental constant, Geary autocorrelation of lag 1, 3 D-MoRSE descriptors (Mor27m and MATS1dv), and JGI4 descriptors. The coefficient of determination value between the predicted and experimental retention time was 0.9782, thus the developed QSRR model was trusty enough for retention simulation of antiviral drugs in RP-HPLC method development. In the end, the QSRR based methods for a single component (emtricitabine) and multicomponent (lamivudine and TDF) analyses were validated as per ICH Q₂ guidelines. Thus, the QSRR approach in chromatographic method development reduces the obscurity of experimental trials, cost, and time.

Graphical Abstract

Keywords:

• Antiviral drugs
• molecular descriptors
• multiple linear regression (MLR)
• quantitative structure retention relationship (QSRR)
• RP-HPLC

Acknowledgments

The authors of thankful to DST-FIST Facility, Raghavendra Institute of Pharmaceutical Education and Research (RIPER)-Autonomous, AP for experimental work, and National Institute of Pharmaceutical Education and Research (NIPER), Hajipur, India for computational work.

Disclosure statement

The authors declare no conflict of interest.

Author contributions

Jagadeesh P. and Ramalingam P. conceptualized the work and designed the protocol. Vinod Kumar K. executed the experimental work and drafted the manuscript. C.V.S. Subrahmanyam and V. Ravichandran derived the interpretation of computational data, correlation to laboratory experiments, and drew the conclusion.