Reengineering of the human pyruvate dehydrogenase complex: from disintegration to highly active agglomerates

Signaling and Regulation Through the NAD+ and NADP+ Networks

SIGNIFICANCE

NAD⁺ and NADP⁺ are important cosubstrates in redox reactions and participate in regulatory networks operating in adjustment of metabolic pathways. Moreover, NAD⁺ is a cosubstrate in post-translational modification of proteins and is involved in DNA repair. NADPH is indispensable for reductive syntheses and the redox chemistry involved in attaining and maintaining correct protein conformation. Recent Advances: Within a couple of decades, a wealth of information has been gathered on NAD(H)⁺/NADP(H) redox imaging, regulatory role of redox potential in assembly of spatial protein structures, and the role of ADP-ribosylation of regulatory proteins affecting both gene expression and metabolism. All these have a bearing also on disease, healthy aging, and longevity.

CRITICAL ISSUES

Knowledge of the signal propagation pathways of NAD⁺-dependent post-translational modifications is still fragmentary for explaining the mechanism of cellular stress effects and nutritional state on these actions. Evaluation of the cosubstrate and regulator roles of NAD(H) and NADP(H) still suffers from some controversies in experimental data.

FUTURE DIRECTIONS

Activating or inhibiting interventions in NAD⁺-dependent protein modifications for medical purposes has shown promise, but restraining tumor growth by inhibiting DNA repair in tumors by means of interference in sirtuins is still in the early stage. The same is true for the use of this technology in improving health and healthy aging. New genetically encoded specific NAD and NADP probes are expected to modernize the research on redox biology.

Toward Multiscale Modeling of Proteins and Bioagglomerates: An Orientation-Sensitive Diffusion Model for the Integration of Molecular Dynamics and the Discrete Element Method

Most processes involved in biological and biotechnological systems spread over many scales in space and time. For example, the interaction of multiple enzymes in heterogeneous enzymatic agglomerates or clusters, necessary for efficient enzymatic conversion, is of high interest for research and enzyme engineering. In order to understand and predict their overall behavior and performance, it is important to describe these scales as completely as possible, known as multiscale modeling. While many different approaches have been presented in recent years, knowledge about protein formation and bioagglomeration at the micro scale is still very limited. In an attempt to address such systems, we propose a bottom- up multiscale modeling methodology, bridging the gaps between molecular dynamics (MD) with an explicit solvent and the larger scale discrete element method (DEM) using an implicit solvent and abstracting macromolecules (e.g., proteins) as objects with anisotropic properties. We term this approach the molecular discrete element method (MDEM). For this, we present an orientation-sensitive diffusion model for DEM, which describes the dynamics of anisotropic translational and rotational diffusion, while implicitly considering solvent molecules and enforcing a canonical ensemble. A general-purpose model and parametrization approach is presented, which can be used to simulate any process involving diffusion of discrete particles. Effects of temperature and viscosity changes can be considered, and guidance is provided concerning time step selection. This model is generally applicable and serves as a precondition to enforce the proper dynamics (i.e., diffusion characteristics and canonical ensemble, similar to a thermostat in MD) for the proposed multiscale modeling methodology with anisotropic properties. Thereby, it presents a first step toward modeling at the micro scale and is integral to enforcing dynamics of such systems and therefore extensively validated. As a next step, interaction models are to be defined and added to the presented model. In comparison to atomistic and coarse-grained (CG) MD, a speedup of 5-7 orders of magnitude can be achieved. The approach is demonstrated on multiple components of the pyruvate dehydrogenase enzyme complex, a multienzymatic machinery that involves very different types of enzymes and is of high value to further elucidate the mechanisms of bioagglomeration and metabolic channeling.

Full Enzyme Complex Simulation: Interactions in Human Pyruvate Dehydrogenase Complex

The pyruvate dehydrogenase complex (PDC) is a large macromolecular machine consisting of dozens of interacting enzymes that are connected and regulated by highly flexible domains, also called swinging arms. The overall structure and function of these domains and how they organize the complex function have not been elucidated in detail to date. This lack of structural and dynamic understanding is frequently observed in multidomain enzymatic complexes. Here we present the first full and dynamic structural model of full human PDC (hPDC), including binding of the linking arms to the surrounding E1 and E3 enzymes via their binding domains with variable stoichiometries. All of the linking domains were modeled at atomistic and coarse-grained levels, and the latter was parametrized to reproduce the same properties of those from the atomistic model. The radii of gyration of the wild-type full complex and functional trimeric subunits were in agreement with available experimental data. Furthermore, the E1 and E3 population effect on the overall structure of the full complex was studied. The results indicated that decreasing the number of E1s increases the flexibility of the now nonoccupied arms. Furthermore, their flexibility depends on the presence of other E1s and E3s in the vicinity, even if they are associated with other arms. As one consequence, the radius of gyration decreases with decreasing number of E1s. This effect also provides an indication of the optimal configuration of E1 and E3 on the basis of the assumption that a certain stability of the enymatic cloud is necessary to avoid free metabolic diffusion of intermediates (metabolic channeling). Our approach and results open a window for future enzyme engineering in a more effective way by evaluating the effect of different linker arm lengths, flexibilities, and combinations of mutations on the activity of other complex enzymes that involve flexible domains, including for example processive enzymes.

Nuclear localization of metabolic enzymes in immunity and metastasis

Metabolism is essential to all living organisms that provide cells with energy, regulators, building blocks, enzyme cofactors and signaling molecules, and is in tune with nutritional conditions and the function of cells to make the appropriate developmental decisions or maintain homeostasis. As a fundamental biological process, metabolism state affects the production of multiple metabolites and the activation of various enzymes that participate in regulating gene expression, cell apoptosis, cancer progression and immunoreactions. Previous studies generally focus on the function played by the metabolic enzymes in the cytoplasm and mitochondrion. In this review, we conclude the role of them in the nucleus and their implications for cancer progression, immunity and metastasis.

Investigation of Core Structure and Stability of Human Pyruvate Dehydrogenase Complex: A Coarse-Grained Approach

The human pyruvate dehydrogenase complex (hPDC) is a large macromolecular machine, and its unique structural and functional properties make it a versatile target for manipulation aiming for the design of new types of artificial multienzyme cascades. However, model-based and hence systematic understanding of the structure-function relationship of this kind of complexes is yet poor. However, with new structure data, modeling techniques, and increasing computation power available, this shortfall is about to cease. Recently, we have built new atomistic models of E2/E3BP, the two subunits of the massive hPDC core. Here, we present developed coarse-grained models of the same, on the basis of which we built and simulated the full core of hPDC, which is so far the first simulation of the catalytic core of any member in the branched-chain α-keto acid dehydrogenase complex family. We explored the stability of two previously proposed substitutional models of hPDC core: 40E2+20E3BP and 48E2+12E3BP. Our molecular dynamics simulations showed a higher stability and sphericity for the second model. Our core's radius of gyration was found to be in strong agreement with previously published experimental dynamic light scattering (DLS) data. Finally, in the direction of our experimental effort to design active minimized complexes, we simulated C-terminal truncated E2/E3BP cores of different lengths, which clearly showed the instability of the core assembly and symmetry due to subunit separations. This correlated very well with the findings of our experimental investigations by analysis of DLS data for variable truncation lengths. The use of polarizable water and an increased total ion concentration did not lead to a substantially different initial stability of the truncated mutants compared to that of standard MARTINI water; however, a different rearrangement behavior of the fragments was observed. The obtained structure models will serve as a basis for full complex simulations in the future, providing the possibility for the model-assisted targeted manipulation of such a complex enzymatic system.