Evolution of tunnels in α/β-hydrolase fold proteins—What can we learn from studying epoxide hydrolases?

Abstract

The evolutionary variability of a protein’s residues is highly dependent on protein region and function. Solvent-exposed residues, excluding those at interaction interfaces, are more variable than buried residues whereas active site residues are considered to be conserved. The abovementioned rules apply also to α/β-hydrolase fold proteins—one of the oldest and the biggest superfamily of enzymes with buried active sites equipped with tunnels linking the reaction site with the exterior. We selected soluble epoxide hydrolases as representative of this family to conduct the first systematic study on the evolution of tunnels. We hypothesised that tunnels are lined by mostly conserved residues, and are equipped with a number of specific variable residues that are able to respond to evolutionary pressure. The hypothesis was confirmed, and we suggested a general and detailed way of the tunnels’ evolution analysis based on entropy values calculated for tunnels’ residues. We also found three different cases of entropy distribution among tunnel-lining residues. These observations can be applied for protein reengineering mimicking the natural evolution process. We propose a ‘perforation’ mechanism for new tunnels design via the merging of internal cavities or protein surface perforation. Based on the literature data, such a strategy of new tunnel design could significantly improve the enzyme’s performance and can be applied widely for enzymes with buried active sites.

Geometry-Based versus Small-Molecule Tracking Method for Tunnel Identification: Benefits and Pitfalls

“…In our study, it identified three (in CH65-EH) to nine (in hsEH) tunnels in the analyzed protein structures with the maximal bottleneck ranging from 0.9 Å in bmEH to 2.4 Å in the TrEH structure (Figure , Table ). We used the same naming for the identified tunnels as in our previous studies, , based on the region in which the tunnel was identified (Tcap, for tunnels found in the cap domain; Tm, for tunnels identified in the main domain; Tc/m, for tunnel identified at the border between both domains). The detailed list of tunnels identified in the crystal structures is in Table .…”

“…However, the geometry-based approach has issues related to the asymmetrical shape of the tunnel: multiple tunnels identified by CAVER during MD simulations may in fact be the same tunnel, as it was shown in the case of the Tc/m tunnel ( Figure S2 ). Part of the tunnels can be seen as short-lasting cavities, which rarely connect with other internal voids, 17 and as such, they are difficult to identify using the geometry-based approach.…”

“…Tunnels were identified in both crystal structures and during MD simulations and then compared with each other to find their corresponding counterparts. First, the tunnels identified during MD simulations and in crystal structures were maintained using the same approach as described elsewhere . In the case of tunnels identified in MD simulations by CAVER 3.02 but for which no corresponding counterpart was found in the crystal structures by CAVER plugin for PyMOL, their tunnel-lining residues were selected based on the cutoff threshold of 0.65.…”

“…Eight unique and complete crystal structures were downloaded from the Protein Data Bank (PDB) representing the same set of structures as used elsewhere: , Homo sapiens (hsEH, PDB ID: 1S8O), Mus musculus (msEH, PDB ID: 1CQZ), Solanum tuberosum (StEH1, PDB ID: 2CJP), Vigna radiata (VrEH2, PDB ID: 5XM6), ( Trichoderma reesei (TrEH, PDB ID: 5URO), Bacillus megaterium (bmEH, PDB ID: 4NZZ), and two structures from an unknown source organism collected from hot springs in Russia and China (Sibe-EH, PDB ID: 5NG7; CH65-EH, PDB ID: 5NFQ).…”

“…First, the tunnels identified during MD simulations and in crystal structures were maintained using the same approach as described elsewhere. 17 In the case of tunnels identified in MD simulations by CAVER 3.02 but for which no corresponding counterpart was found in the crystal structures by CAVER plugin for PyMOL, their tunnel-lining residues were selected based on the cutoff threshold of 0.65. This value was chosen on the basis of quantile computations for the tunnels identified in MD simulation, which had their counterparts in the crystallographic structures.…”