Estimation of Physical Properties of Amino Acids by Group-Contribution Method

In this paper, we present group-contribution (GC) based property models for estimation of physical properties of amino acids using their molecular structural information. The physical properties modelled in this work are normal melting point (T_m), aqueous solubility (W_s), and octanol/water partition coefficient (K_ow) of amino acids. The developed GC-models are based on the published GC-method by Marrero and Gani (J. Marrero, R. Gani, Fluid Phase Equilib. 2001, 183-184, 183-208) with inclusion of new structural parameters (groups and molecular weight of compounds). The main objective of introducing these new structural parameters in the GC-model is to provide additional structural information for amino acids having large and complex structures and thereby improve predictions of physical properties of amino acids. The group-contribution values were calculated by regression analysis using a data-set of 239 values for T_m, 211 values for W_s, and 335 values for K_ow. Compared to other currently used GC-models, the developed models make significant improvements in accuracy with average absolute error of 10.8 K for Tm and logarithm-unit average absolute errors of 0.16 for K_ow and 0.19 for W_s.