A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV)

Abstract

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes’ activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in β-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance β-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 β-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a β-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.

VTR: an algorithm for identifying analogous contacts on protein structures and their complexes

“…Both enzymes have a similar TIM-barrel folding, belonging to the first family of glycoside hydrolases (GH1) 39 . Moreover, they present a sequence similarity higher than 50% 40 . Thus, we decided to submit to VTR the structures of Bgl1A and Bgl1B to evaluate similar contacts and identify possible differences.…”

Proteus: An algorithm for proposing stabilizing mutation pairs based on interactions observed in known protein 3D structures

“…Also, SDM and mCSM methods were combined in a hybrid approach called DUET, which tries to obtain a more accurate prediction of the free energy change; ΔΔG [14]. SSV is another method that uses graph-based structural signatures and compares Euclidean distances between vectors to predict if mutations introduce similar characteristics to reference proteins [15]. Lastly, MAES-TRO is a web server that combines high-throughput scanning for multi-point mutations, prediction of free energy change, and stabilizing disulfide bonds [6].…”

“…If the RMSD is lower than 0.5 Å, PSE considers that both residues could be exchanged simultaneously without undesirable main chain conformational changes in the structure. Furthermore, PSE uses SSV (structural signature variation) method [15] to reduce computational costs (see implementation section for details).…”

“…For this, Proteus searches for target sites in the protein structure for possible mutations, distancing Proteus from sequence-based methods, such as MODIP and Mustab. Proteus is also different from other structure-based approaches such as SDM, mCSM, DUET, MAESTRO webtool, or other strategies used to propose mutations based on structural signatures (also called fingerprints) like SSV (structural signature [15]. Hence, the main objective of this tools is to predict the free energy difference between mutant and wild type molecules.…”

“…We constructed a user-friendly interface, herein called ProteusWEB, to provide a secure method to run the Proteus algorithm. ProteusWEB was constructed using the PHP, HTML, and JavaScript languages, using a similar architecture to [15,[31][32][33]. 3Dmol.js was used for visualization of protein structures [16].…”