Quantitative structure-activity relationship (QSAR) studies on 104 flavonoid derivatives as p56lck protein tyrosine kinase (PTK) inhibitors were performed, using a large number of molecular descriptors calculated by CODESSA software. Multiple linear regression and orthogonalization of descriptors were applied to generate models for the prediction of biological activities for binding flavonoids to PTK. The obtained results demonstrate in detail the importance of electrostatic and quantum chemical descriptors for the interaction of flavonoids with the specific p56lck enzymatic active site environment. In particular, the maximal total interaction for a C-O bond is the most important factor in regression. Use of orthogonalization in regression models provides a valuable improvement for the interpretative and predictive capacity of structure-activity relationships found.