2022
DOI: 10.1021/acs.jcim.2c00735
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QM/MM Well-Tempered Metadynamics Study of the Mechanism of XBP1 mRNA Cleavage by Inositol Requiring Enzyme 1α RNase

Abstract: A range of in silico methodologies were herein employed to study the unconventional XBP1 mRNA cleavage mechanism performed by the unfolded protein response (UPR) mediator Inositol Requiring Enzyme 1α (IRE1). Using Protein–RNA molecular docking along with a series of extensive restrained/unrestrained atomistic molecular dynamics (MD) simulations, the dynamical behavior of the system was evaluated and a reliable model of the IRE1/XBP1 mRNA complex was constructed. From a series of well-con… Show more

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Cited by 6 publications
(6 citation statements)
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“…Since DFT-based QM/MM-MetaD simulation is very demanding, the limited number of atoms in the QM region (64 atoms here) could be considered a potential limitation in our methodology. One might opt to employ the semiempirical-based QM/MM-MetaD simulation methodology as an effective means to accommodate a larger number of QM atoms and expedite computational throughput . However, the utilization of either DFT-based or semiempirical-based computations represents a substantial trade-off, necessitating a rigorous and deliberate assessment between precision and computational efficiency.…”
Section: Discussionmentioning
confidence: 99%
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“…Since DFT-based QM/MM-MetaD simulation is very demanding, the limited number of atoms in the QM region (64 atoms here) could be considered a potential limitation in our methodology. One might opt to employ the semiempirical-based QM/MM-MetaD simulation methodology as an effective means to accommodate a larger number of QM atoms and expedite computational throughput . However, the utilization of either DFT-based or semiempirical-based computations represents a substantial trade-off, necessitating a rigorous and deliberate assessment between precision and computational efficiency.…”
Section: Discussionmentioning
confidence: 99%
“…One might opt to employ the semiempirical-based QM/MM-MetaD simulation methodology as an effective means to accommodate a larger number of QM atoms and expedite computational throughput. 20 However, the utilization of either DFT-based or semiempirical-based computations represents a substantial trade-off, necessitating a rigorous and deliberate assessment between precision and computational efficiency. The reasonable assumption of a “single initial reactant state”, where the most representative form of the reactant comes from the atomistic models of protein–protein docking, clustering, and relaxation, might affect the minimum energy pathway.…”
Section: Discussionmentioning
confidence: 99%
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“…The development of enhanced sampling methods, such as QM/MM MetD, allows the exploration of the free energy surface (FES) of (bio)chemical reactions with numerous minima, separated by barriers much higher than thermal energies. By implementing collective variables (CVs), this approach explores chemical changes at real temperatures, incorporating dynamical and entropic effects for the entire system. ,− Understanding the origin of enzyme catalytic power often involves comparing the enzyme-catalyzed reactions with their corresponding counterparts in a solution. This comparison dissects structural and energetic effects leading to TS stabilization and decreasing the activation energy of the catalyzed reaction in the enzyme, as well as the role of solvent molecules in catalysis. The water solvent influences the structure, dynamics, and kinetics of the enzymes. Quantifying the contributions of crucial enzyme residues and explicit water molecules to the kinetics of enzyme-catalyzed reactions is critical to understanding catalytic mechanisms and the origin of the enzyme catalytic effect properly. An insertion of a water molecule into the active site can accelerate the reaction by influencing its dielectric properties .…”
Section: Introductionmentioning
confidence: 99%
“…However, even more drastic effects may be expected over simulation time, as artifacts and quirks in trajectories arise. Recent development of QM/MM interfaces with fast and reasonably accurate semiempirical QM methods allow researchers to go beyond single-point calculations and study processes as they are, in dynamics. These approaches are becoming more and more popular. Coupling fast semiempirical QM potentials with machine learning corrections was shown to dramatically improve its accuracy making it comparable with more sophisticated density functional theory (DFT) methods . Thus, we speculate that a field will witness a rise in popularity of such approaches.…”
Section: Introductionmentioning
confidence: 99%