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

Stoichiometry and architecture of the human pyruvate dehydrogenase complex

The pyruvate dehydrogenase complex (PDHc) is a key megaenzyme linking glycolysis with the citric acid cycle. In mammalian PDHc, dihydrolipoamide acetyltransferase (E2) and the dihydrolipoamide dehydrogenase-binding protein (E3BP) form a 60-subunit core that associates with the peripheral subunits pyruvate dehydrogenase (E1) and dihydrolipoamide dehydrogenase (E3). The structure and stoichiometry of the fully assembled, mammalian PDHc or its core remained elusive. Here, we demonstrate that the human PDHc core is formed by 48 E2 copies that bind 48 E1 heterotetramers and 12 E3BP copies that bind 12 E3 homodimers. Cryo-electron microscopy, together with native and cross-linking mass spectrometry, confirmed a core model in which 8 E2 homotrimers and 12 E2-E2-E3BP heterotrimers assemble into a pseudoicosahedral particle such that the 12 E3BP molecules form six E3BP-E3BP intertrimer interfaces distributed tetrahedrally within the 60-subunit core. The even distribution of E3 subunits in the peripheral shell of PDHc guarantees maximum enzymatic activity of the megaenzyme.

Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model

The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.

The structure and evolutionary diversity of the fungal E3-binding protein

The pyruvate dehydrogenase complex (PDC) is a central metabolic enzyme in all living cells composed majorly of E1, E2, and E3. Tight coupling of their reactions makes each component essential, so that any loss impacts oxidative metabolism pathologically. E3 retention is mediated by the E3-binding protein (E3BP), which is here resolved within the PDC core from N.crassa, resolved to 3.2Å. Fungal and mammalian E3BP are shown to be orthologs, arguing E3BP as a broadly eukaryotic gene. Fungal E3BP architectures predicted from sequence data and computational models further bridge the evolutionary distance between N.crassa and humans, and suggest discriminants for E3-specificity. This is confirmed by similarities in their respective E3-binding domains, where an interaction previously not described is also predicted. This provides evolutionary parallels for a crucial interaction human metabolism, an interaction specific to fungi that can be targeted, and an example of protein evolution following gene neofunctionalization.

Hierarchical Coarse-Grained Strategy for Macromolecular Self-Assembly: Application to Hepatitis B Virus-Like Particles

Macromolecular self-assembly is at the basis of many phenomena in material and life sciences that find diverse applications in technology. One example is the formation of virus-like particles (VLPs) that act as stable empty capsids used for drug delivery or vaccine fabrication. Similarly to the capsid of a virus, VLPs are protein assemblies, but their structural formation, stability, and properties are not fully understood, especially as a function of the protein modifications. In this work, we present a data-driven modeling approach for capturing macromolecular self-assembly on scales beyond traditional molecular dynamics (MD), while preserving the chemical specificity. Each macromolecule is abstracted as an anisotropic object and high-dimensional models are formulated to describe interactions between molecules and with the solvent. For this, data-driven protein-protein interaction potentials are derived using a Kriging-based strategy, built on high-throughput MD simulations. Semi-automatic supervised learning is employed in a high performance computing environment and the resulting specialized force-fields enable a significant speed-up to the micrometer and millisecond scale, while maintaining high intermolecular detail. The reported generic framework is applied for the first time to capture the formation of hepatitis B VLPs from the smallest building unit, i.e., the dimer of the core protein HBcAg. Assembly pathways and kinetics are analyzed and compared to the available experimental observations. We demonstrate that VLP self-assembly phenomena and dependencies are now possible to be simulated. The method developed can be used for the parameterization of other macromolecules, enabling a molecular understanding of processes impossible to be attained with other theoretical models.

Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function

Pyruvate dehydrogenase complex (PDC) deficiency is a major cause of primary lactic acidemia resulting in high morbidity and mortality, with limited therapeutic options. The E1 component of the mitochondrial multienzyme PDC (PDC-E1) is a symmetric dimer of heterodimers (αβ/α'β') encoded by the PDHA1 and PDHB genes, with two symmetric active sites each consisting of highly conserved phosphorylation loops A and B. PDHA1 mutations are responsible for 82-88% of cases. Greater than 85% of E1α residues with disease-causing missense mutations (DMMs) are solvent-inaccessible, with ∼30% among those involved in subunit-subunit interface contact (SSIC). We performed molecular dynamics simulations of wild-type (WT) PDC-E1 and E1 variants with E1α DMMs at R349 and W185 (residues involved in SSIC), to investigate their impact on human PDC-E1 structure. We evaluated the change in E1 structure and dynamics and examined their implications on E1 function with the specific DMMs. We found that the dynamics of phosphorylation Loop A, which is crucial for E1 biological activity, changes with DMMs that are at least about 15 Å away. Because communication is essential for PDC-E1 activity (with alternating active sites), we also investigated the possible communication network within WT PDC-E1 via centrality analysis. We observed that DMMs altered/disrupted the communication network of PDC-E1. Collectively, these results indicate allosteric effect in PDC-E1, with implications for the development of novel small-molecule therapeutics for specific recurrent E1α DMMs such as replacements of R349 responsible for ∼10% of PDC deficiency due to E1α DMMs.

Regulation of pyruvate dehydrogenase complex related to lactate switch in CHO cells

The metabolism of Chinese hamster ovary (CHO) cell lines is typically characterized by high rates of aerobic glycolysis with increased lactate formation, known as the "Warburg" effect. Although this metabolic state can switch to lactate consumption, the involved regulations of the central metabolism have only been partially studied so far. An important reaction transferring the lactate precursor, pyruvate, into the tricarboxylic acid cycle is the decarboxylation reaction catalyzed by the pyruvate dehydrogenase enzyme complex (PDC). Among other mechanisms, PDC is mainly regulated by phosphorylation-dephosphorylation at the three sites Ser232, Ser293, and Ser300. In this work, the PDC phosphorylation in antibody-producing CHO DP-12 cell culture is investigated during the lactate switch. Batch cultivations were carried out with frequent sampling (every 6 h) during the transition from lactate formation to lactate uptake, and the PDC phosphorylation levels were quantified using a novel indirect flow cytometry protocol. Contrary to the expected activation of PDC (i.e., reduced PDC phosphorylation) during lactate consumption, Ser293 and Ser300 phosphorylation levels were 33% higher compared to the phase of glucose excess. At the same time, the relative phosphorylation level of Ser232 increased steadily throughout the cultivation (66% increase overall). The intracellular pyruvate was found to accumulate only during the period of high lactate production, while acetyl-CoA showed nearly no accumulation. These results indicate a deactivation of PDC and reduced oxidative metabolism during lactate switch even though the cells undergo a metabolic transition to lactate-based cell growth and metabolism. Overall, this study provides a unique view on the regulation of PDC during the lactate switch, which contributes to an improved understanding of PDC and its interaction with the bioprocess.

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.

How phosphorylation influences E1 subunit pyruvate dehydrogenase: A computational study

Pyruvate (PYR) dehydrogenase complex (PDC) is an enzymatic system that plays a crucial role in cellular metabolism as it controls the entry of carbon into the Krebs cycle. From a structural point of view, PDC is formed by three different subunits (E1, E2 and E3) capable of catalyzing the three reaction steps necessary for the full conversion of pyruvate to acetyl-CoA. Recent investigations pointed out the crucial role of this enzyme in the replication and survival of specific cancer cell lines, renewing the interest of the scientific community. Here, we report the results of our molecular dynamics studies on the mechanism by which posttranslational modifications, in particular the phosphorylation of three serine residues (Ser-264-α, Ser-271-α, and Ser-203-α), influence the enzymatic function of the protein. Our results support the hypothesis that the phosphorylation of Ser-264-α and Ser-271-α leads to (1) a perturbation of the catalytic site structure and dynamics and, especially in the case of Ser-264-α, to (2) a reduction in the affinity of E1 for the substrate. Additionally, an analysis of the channels connecting the external environment with the catalytic site indicates that the inhibitory effect should not be due to the occlusion of the access/egress pathways to/from the active site.

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.