Application of Rational Design and Molecular Metadynamics for the Estimation of Changes in Trans-Splicing Efficiency during the Mutagenesis of Ssp DnaE Intein.

应用理性设计和分子元动力学来估计 Ssp DnaE 内含肽诱变过程中反式剪接效率的变化

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作者:Sabantsev Matvei O, Brovin Andrew N, Gureev Maxim A, Porozov Yuri B, Chuvpilo Sergey A, Karabelsky Alexander V
Currently, inteins are some of the most popular multifunctional tools in the fields of molecular biology and biotechnology. In this study, we used the surface analysis method to identify the sites of intermolecular interactions between the N and C-parts of the Ssp DnaE intein. The obtained results were used to determine the key amino acids that define the binding energy and type of contact between intein subunits. In silico substitution of five neutral amino acids in the C-part of Ssp DnaE with methionine was validated by using oligomutagenesis of a previously assembled plasmid, which was then used for in vitro tests with HEK293 cells. GFP reconstruction assays were used to estimate changes in trans-splicing efficiency using quantitative metrics such as the number of GFP+ cells and median fluorescence intensity as well as qualitative metrics such as microphotography and fluorescence curve analysis using live-cell microscopy. The results of the in vitro tests revealed significantly decreased splicing efficiency in four out of six mutant variants, with no significant differences in the other two cases. Additionally, we performed metadynamics modeling to explain how these mutations affect the molecular mechanisms of intein-intein interactions. Finally, we found a positive correlation between the structural and free energy changes in the local minima distribution and the decrease in splicing efficiency in the I151M and A162M+A165M cases. The resulting method was used with control mutations that had an experimentally confirmed positive (A168H) or negative (T198A) effect on the splicing reaction. In summary, we propose a method of free energy surface analysis in collective variables for quick and visual evaluation of mutation effects. This approach could be applied for the development of new biotechnological and gene therapy products to overcome AAV capacity limitations.

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