Identification and evaluation of tunnels in proteins with buried active sites
Abstract
In proteins with buried active sites, understanding how ligands migrate through the tunnels that connect the exterior of the protein to the active site can shed light on substrate recognition and enzyme function. Computational prediction of ligand entry and egress tunnels in proteins has become an emerging topic in computational biology and has proven useful in fields such as protein engineering and drug design. Two main techniques have evolved for predicting tunnels in proteins with buried active sites; those based on geometric principles and those based on explicit ligand migration calculations. Geometric tunnel prediction employs computationally efficient algorithms to identify tunnels in input structure; however, the increasingly recognized importance of protein flexibility in tunnel formation and behavior has led to the more widespread use of protein ensembles in tunnel prediction. The influence of using a single input structure versus a structural ensemble in geometric tunnel prediction was analyzed. The findings highlight the importance of including protein flexibility in geometric tunnel prediction, but also suggested that the evaluation of tunnels could be influenced by the input structure(s) selected. There are several limitations of geometric tunnel prediction, most notably that ligand migration and protein flexibility in response to ligand migration cannot be directly incorporated into tunnel prediction. The increasingly recognized importance of both inherent protein flexibility and flexibility introduced by ligand migration has made this an important consideration in tunnel prediction. We have developed a novel tunnel prediction and evaluation method named IterTunnel, which includes the influence of ligand-induced protein flexibility, guarantees ligand egress, and provides detailed free energy information as the ligand proceeds along the egress route. IterTunnel combines geometric tunnel prediction with steered MD in an iterative process to identify tunnels that open as a result of ligand migration and calculates the potential of mean force (PMF) of ligand egress through a given tunnel. Application of IterTunnel to CYP2B6 shows that by incorporating protein flexibility due to ligand migration, new more energetically favorable ligand egress tunnels are identified.
Degree
Ph.D.
Advisors
Lill, Purdue University.
Subject Area
Molecular chemistry|Theoretical physics
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