Analysis of ligand binding effect on enzyme dynamics using elastic network models

Abstract

The objective of this thesis was to investigate the e ect of ligand binding on global vibrational modes of an enzyme, triosphosphate isomerase (TIM). For this aim, mixed coarse-grained elastic network model ENM (MCG ENM) was used to observe the frequency shifts in the most collective modes due to the presence of the ligand. In MCG ENM, the ligand is taken in atomistic detail and the protein is in low-resolution. First analysis was performed on previous blind docking results, which comprise a total of 1496 poses of ve benzothiazoles, three of which are inhibitors of catalytic activity, docked on three di erent TIM conformers. Several di erent binding sites/poses were detected including the tunnel region, catalytic site and others. The inhibitors bound to the previously identi ed tunnel region could be di erentiated based on their impact on global vibrational modes of the enzyme. Later, six independent MD runs (three apo and three complex with inhibitor bt10) were analyzed by performing MCG ENM on a total of 54,000 MD snapshots of TIM. Through this computationally e cient technique, altered collective modes and positive shifts in eigenvalues were detected in the complex runs due to the constraining e ect of inhibitor binding at the tunnel region. Lastly, a new computational technique was introduced for scanning protein side chains in terms of their constraining e ect on ENM modes. In this methodology, the ligand binding e ect in the vicinity of a speci c residue is mimicked by adding extra nodes to its side chain atoms. ENM-based scanning of TIM also pinpointed to the tunnel region as a key binding site that can alter global dynamics of the enzyme. Scanning of other enzymes indicated marked constraining e ect around the ligand positions observed in crystal structures.