Enzyme binding selectivity prediction: alpha-thrombin vs trypsin inhibition

In the present work we explore the possibility of an in-depth computational analysis of available experimental X-ray structures in the specific case of a series of alpha-thrombin and trypsin complexes with their respective inhibitors for the development of a novel scoring function based on molecular electrostatic potential computed at the contact surface in the enzyme-inhibitor molecular complex. We subsequently employ the chemometrical approach to determine which are the interactions in the large volume of data that determine the resulting experimental binding constant between ligand and receptor. The results of the model evaluated with molecules in the independent validation set show that a reasonable average error of 1.30 log units of the difference between experimental and calculated binding constants was achieved in the system thrombin-trypsin, which is comparable with those of methods from the literature. Furthermore, by a careful preparation of the Kohonen top layer in the artificial neural network approach that is normally perceived as a "black box device", we have been able to follow the implications of the structure of the inhibitor-enzyme complex for the inhibitor's binding constant. The method appears to be suitable for evaluation of selectivity in structurally similar enzymatic systems, which is currently an important problem in drug design.