A Simple, Yet Rapid and Effective Method for LogP Prediction of Dipeptides Based on Theoretical Descriptors (HMLP)

Abstract

The hydrophobicity of peptide is an important factor that affects the dissolution behavior of proteins and peptides, also affect the physical and chemical properties. In this study, each amino acid side chain was characterized using three structure parameters (heuristic molecular lipophilicity potential, HMLP). The HMLP parameters, total surface area(S), lipophilic indices (L), and hydrophilic indices (H) of amino acid side chains are derived from theoretical computation. Based on HMLP descriptors, QSAR models of the logP were constructed for blocked and unblocked dipeptides by multiple linear regression (MLR) and support vector regression (SVR). All the results showed that the logP relates to the total surface area(S) and hydrophilic indices (H), and the prediction results of SVR are better than that of MLR. The prediction results are in agreement with the experimental values. The result shows HMLP parameters (S,L,H) could preferably describe the structure features of the peptides responsible for their octanol to water partition behavior.