Periodic Reporting for period 1 - DeciphGYG (Deciphering the Molecular Mechanism of an Enzymatic Machinery for Glycogen Biosynthesis)
Reporting period: 2022-05-02 to 2024-05-01
The project “Deciphering the Molecular Mechanism of an Enzymatic Machinery for Glycogen Biosynthesis” focuses on addressing the mechanism of the enzymatic machinery of human glycogenin 1 for glycogen biosynthesis. How is the substrate-induced conformational change coupled with the chemical reactions? What is the mechanism of chemical reactions at different lengths of the glucose chain as an acceptor? How does the mutation T83M lead to enzymatically inactive, causing glycogen storage diseases? A new protocol is planned to be developed to answer these questions, which is transferable to other glycosyltransferases.
The research idea of this work was that many mutations of enzymes could lead to diseases, and the mechanism behind the mutations is still not well understood in most cases due to limited capacity and technical caveats of the available research tools. We aimed to combine both multiscale computational modeling methods and experimental tools to uncover the deep mechanism. Such a combined approach has not yet been very common in this field. Working on this project might increase understanding of how enzymes function and how mutations lead to the malfunction of enzymes. Deeper knowledge will facilitate drug design against mutation-associated diseases with more confidence, which will improve the biotechnology development in the pharmaceutical industry.
The objectives of this MSCA project are (1) to identify the Michaelis complexes of hGYG1 with different lengths of sugar chains as acceptors and study their recognition. (2) to address the catalytic mechanism of glucosyl transfer within hGYG1 (3) to investigate the effects of mutation T83M on the catalysis and dynamics of hGYG1. How a single mutation on the lid could lead to an inactive hGYG1, causing glycogen storage disease.
The research idea of this work was that many mutations of enzymes could lead to diseases, and the mechanism behind the mutations is still not well understood in most cases due to limited capacity and technical caveats of the available research tools. We aimed to combine both multiscale computational modeling methods and experimental tools to uncover the deep mechanism. Such a combined approach has not yet been very common in this field. Working on this project might increase understanding of how enzymes function and how mutations lead to the malfunction of enzymes. Deeper knowledge will facilitate drug design against mutation-associated diseases with more confidence, which will improve the biotechnology development in the pharmaceutical industry.
The objectives of this MSCA project are (1) to identify the Michaelis complexes of hGYG1 with different lengths of sugar chains as acceptors and study their recognition. (2) to address the catalytic mechanism of glucosyl transfer within hGYG1 (3) to investigate the effects of mutation T83M on the catalysis and dynamics of hGYG1. How a single mutation on the lid could lead to an inactive hGYG1, causing glycogen storage disease.
The research project was done in three work packages (WP1-WP3). WP1 was to elucidate the molecular details of the recognition of the glucose donor and acceptors by hGYG1. We developed force field parameters of Tyr-Glc using QM calculations, and we also built 10 Michaelis complexes of human glycogenin 1 with different number of glucose units as acceptors (n=0-3 for intra-mode and n=0-5 for inter-mode). For each of the 10 complexes, we performed extensive MD simulations, and we found that the first step of the reaction (adding glucose to Y195) is most likely to be an inter-model, as the intra-mode complex (n=0) is not stable even after 1000 ns MD simulations with distance restraints. WP2 was designed to decipher the catalytic mechanisms of glucosyl transfer catalyzed by hGYG1 and proposed mutants. Taking snapshots from the classical MD simulations in WP1 (n=0-5 of inter-mode, and n=2,3 of intra-mode), we performed QM/MM OPES-explore (metadynamics-like) simulations to study the chemical reactions catalyzed by hGYG1. The computed free energy barriers range from 20.0 to 25.0 kcal/mol, which falls in the same range as most glycosyltransferases. The mechanism of the reaction we observed is SNi-like, typical for retaining glycosyltransferases, an intermediate was captured during the QM/MM simulations. We developed a new protocol for modeling enzymatic reactions, which combines OPES-explore and path collective variables with QM/MM. OPES-explore is powerful, and faster crossing and recrossing could be observed than with metadynamics, while setting a restraint on a Z-path of a path collective variable could prevent sampling at high energy regions and ensure more samplings in relevant phase space. WP3 aimed to investigate the influence of the T83M mutation on the catalysis and dynamics of the lid of hGYG1. We used thermodynamics integration to compute the binding free energy difference caused by the mutation T83M, and we found out that the mutation caused a decrease in binding affinity due to clashes with the substrate. We also built a path collective variable (PCV) to study the effects on the dynamics of the lid, where T83 is located. We performed OPES-explore (metadynamics-like) simulations over the PCV of both the wild type and the T83M mutants. Compared to the WT, the mutation T83M makes the lid more prone to open conformation.
The esults of our research will be reported in 4 papers underway (two manuscripts in preparation, and two need more supporting data). Our publications would be posted at our group page (https://sites.google.com/site/roviralab/(opens in new window)) department page (https://www.iqtc.ub.edu/(opens in new window)) and X (former Twitter, my personal account and the supervisor’s) and LinkedIn (my personal account and the supervisor’s).
The esults of our research will be reported in 4 papers underway (two manuscripts in preparation, and two need more supporting data). Our publications would be posted at our group page (https://sites.google.com/site/roviralab/(opens in new window)) department page (https://www.iqtc.ub.edu/(opens in new window)) and X (former Twitter, my personal account and the supervisor’s) and LinkedIn (my personal account and the supervisor’s).
This MSCA project aimed to carry out multidisciplinary research for a better understanding of the initialization of glycogen biosynthesis within enzymatic machinery of human glycogenin 1. Innovative aspects included: 1) we use a set of computational methods including classical molecular dynamics (with enhanced sampling skills) and QM/MM simulations, to study both the substrate-induced conformational changes and catalyzed chemical reactions. From the computational results, we proposed possible mutations that would improve the enzymatic activities of hGYG1, including the ones that could possibly reactivate an inactive T83M variant. This newly proposed protocol could be easily transferred to study other enzymes. II, we implemented experimental methods (X-ray crystallography, enzymatic activity tests) to verify the proposed mutations of hGYG1.
The final outcome of the project will have the potential to draw attention from any scientific group or company interested in understanding how enzymes work and designing therapeutical molecules. It will also bring some awareness to rare diseases (glycogen storage disease XV). We will publicly release protocols, in line with Open Science best practices, and for maximum impact of our approach. The study and understanding of enzymes is an increasingly important field, especially in drug discovery, it is also of increasing interest in enzyme engineering and synthetic biology.
The final outcome of the project will have the potential to draw attention from any scientific group or company interested in understanding how enzymes work and designing therapeutical molecules. It will also bring some awareness to rare diseases (glycogen storage disease XV). We will publicly release protocols, in line with Open Science best practices, and for maximum impact of our approach. The study and understanding of enzymes is an increasingly important field, especially in drug discovery, it is also of increasing interest in enzyme engineering and synthetic biology.