Background: It has been demonstrated a variety of condenced phase macroscopic properties that reflect non-covalent interactions can be expressed analytically in terms of statistically defined quantities that characterize molecular surface electrostatic potentials [1]. Methods: In this investigation, based on the general interaction properties function (GIPF) family descriptors computed at the density function theory (DFT) with quantum-mechanical B3LYP/6-31G* level using the Gaussian98 software [2,3], we creat QSPR models for prediction a large number of physicochemical properties or thermodynamic functions of acyclic alkanes [4,5] (straight-chain and branched chain) have extensively constructed by using multiple linear regression (MLR) analysis [3]., following the guidelines for development and validation of regression models. The regression models were interpreted in terms of selected descriptors and demonstrated these properties depend on forces that are electrostatic in nature. Results: The result shows that these QSPRs have quite good predictive abilities (R2 between 0.814 and 0.997). All models validated by internal validation tests (leave-one-out (LOO) cross validation test and Y-randomization test) and R2 for these test (R2CV and R2max), respectively are between 0.706-0.997 and 0.2620-0.0044, respectively. Conclusion: Resulted models demonstrated some of these properties depend on interactions that are electrostatic in nature.
