Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

What is allosteric regulation? Exploring the exceptions that prove the rule!

"Allosteric" was first introduced to mean the other site (i.e., a site distinct from the active or orthosteric site), an adjective for "regulation" to imply a regulatory outcome resulting from ligand binding at another site. That original idea outlines a system with two ligand-binding events at two distinct locations on a macromolecule (originally a protein system), which defines a four-state energy cycle. An allosteric energy cycle provides a quantifiable allosteric coupling constant and focuses our attention on the unique properties of the four equilibrated protein complexes that constitute the energy cycle. Because many observed phenomena have been referenced as "allosteric regulation" in the literature, the goal of this work is to use literature examples to explore which systems are and are not consistent with the two-ligand thermodynamic energy cycle-based definition of allosteric regulation. We emphasize the need for consistent language so comparisons can be made among the ever-increasing number of allosteric systems. Building on the mutually exclusive natures of an energy cycle definition of allosteric regulation versus classic two-state models, we conclude our discussion by outlining how the often-proposed Rube-Goldberg-like mechanisms are likely inconsistent with an energy cycle definition of allosteric regulation.

The 2.4 Å structure of Zymomonas mobilis pyruvate kinase: Implications for stability and regulation

Human liver pyruvate kinase (hlPYK) catalyzes the final step in glycolysis, the formation of pyruvate (PYR) and ATP from phosphoenolpyruvate (PEP) and ADP. Fructose 1,6-bisphosphate (FBP), a pathway intermediate of glycolysis, serves as an allosteric activator of hlPYK. Zymomonas mobilis pyruvate kinase (ZmPYK) performs the final step of the Entner-Doudoroff pathway, which is similar to glycolysis in that energy is harvested from glucose and pyruvate is generated. The Entner-Doudoroff pathway does not have FBP as a pathway intermediate, and ZmPYK is not allosterically activated. In this work, we solved the 2.4 Å X-ray crystallographic structure of ZmPYK. The protein is dimeric in solution as determined by gel filtration chromatography, but crystallizes as a tetramer. The buried surface area of the ZmPYK tetramerization interface is significantly smaller than that of hlPYK, and yet tetramerization using the standard interfaces from higher organisms provides an accessible low energy crystallization pathway. Interestingly, the ZmPYK structure showed a phosphate ion in the analogous location to the 6-phosphate binding site of FBP in hlPYK. Circular Dichroism (CD) was used to measure melting temperatures of hlPYK and ZmPYK in the absence and presence of substrates and effectors. The only significant difference was an additional phase of small amplitude for the ZmPYK melting curves. We conclude that the phosphate ion plays neither a structural or allosteric role in ZmPYK under the conditions tested. We hypothesize that ZmPYK does not have sufficient protein stability for activity to be tuned by allosteric effectors as described for rheostat positions in the allosteric homologues.

PYK-SubstitutionOME: an integrated database containing allosteric coupling, ligand affinity and mutational, structural, pathological, bioinformatic and computational information about pyruvate kinase isozymes

Interpreting changes in patient genomes, understanding how viruses evolve and engineering novel protein function all depend on accurately predicting the functional outcomes that arise from amino acid substitutions. To that end, the development of first-generation prediction algorithms was guided by historic experimental datasets. However, these datasets were heavily biased toward substitutions at positions that have not changed much throughout evolution (i.e. conserved). Although newer datasets include substitutions at positions that span a range of evolutionary conservation scores, these data are largely derived from assays that agglomerate multiple aspects of function. To facilitate predictions from the foundational chemical properties of proteins, large substitution databases with biochemical characterizations of function are needed. We report here a database derived from mutational, biochemical, bioinformatic, structural, pathological and computational studies of a highly studied protein family-pyruvate kinase (PYK). A centerpiece of this database is the biochemical characterization-including quantitative evaluation of allosteric regulation-of the changes that accompany substitutions at positions that sample the full conservation range observed in the PYK family. We have used these data to facilitate critical advances in the foundational studies of allosteric regulation and protein evolution and as rigorous benchmarks for testing protein predictions. We trust that the collected dataset will be useful for the broader scientific community in the further development of prediction algorithms. Database URL https://github.com/djparente/PYK-DB.

Is BF.7 more infectious than other Omicron subtypes: Insights from structural and simulation studies of BF.7 spike RBD variant

Fear of a fresh infection wave and a global health issue in the ongoing COVID-19 pandemic have been rekindled by the appearance of two new novel variants BF.7 and BA.4/5 of Omicron lineages. Predictions of increased antibody evasion capabilities and transmissibility have been recognised in addition to the existing lineages (BA.1.1, BA.2, BA.2.12.1 and BA.3) as cause for worry. In comparison to Omicron, BA.4 and BF.7 share nine mutations in the spike protein, Leu371Phe, Thr376Ala, Asp405Asn, Arg408Ser, Ser446Gly, Leu452Arg, Phe486Val, Arg493Gln, Ser496Gly, whereas BF.7 contains an additional mutation, Arg346Thr, in the receptor binding domain (RBD) region. Due to the critical need for analysis and data on the BA.4 and BF.7 variants, we have computationally analyzed the interaction pattern between the Omicron, BA.4 and BF.7 RBD and angiotensin-converting enzyme 2 (ACE2) to determine the influence of these unique mutations on the structures, functions, and binding affinity of RBD towards ACE2. These analyses also allow to compare molecular models to previously reported data to evaluate the robustness of our methods for quick prediction of emerging future variants. The docking results reveal that BA.4 and BF.7 have particularly strong interactions with ACE2 when compared to Omicron, as shown by several parameters such as salt bridge, hydrogen bond, and non-bonded interactions. In addition, the estimations of binding free energy corroborated the findings further. BA.4 and BF.7 were found to bind to ACE2 with similar affinities (-72.14 and - 71.54 kcal/mol, respectively) and slightly stronger than Omicron (-70.04 kcal/mol). The differences in the binding pattern between the Omicron, BA.4 and BF.7 variant complexes indicated that the BA.4 and BF.7 RBD substitutions Asp405Asn, Ser446Gly, Leu452Arg, Phe486Val and Arg493Gln caused additional interactions with ACE2. In addition, normal mode analyses also indicate more stable conformations of BA.4 and BF.7 RBDs against human ACE2. Based on these structural and simulation analyses, we hypothesized that these changes may affect the binding affinity of BA.4 and BF.7 with ACE2.

Roadmap to Pyruvate Kinase M2 Modulation - A Computational Chronicle

Pyruvate kinase M2 (PKM2) has surfaced as a potential target for anti-cancer therapy. PKM2 is known to be overexpressed in the tumor cells and is a critical metabolic conduit in supplying the augmented bioenergetic demands of the recalcitrant cancer cells. The presence of PKM2 in structurally diverse tetrameric as well as dimeric forms has opened new avenues to design novel modulators. It is also a truism to state that drug discovery has advanced significantly from various computational techniques like molecular docking, virtual screening, molecular dynamics, and pharmacophore mapping. The present review focuses on the role of computational tools in exploring novel modulators of PKM2. The structural features of various isoforms of PKM2 have been discussed along with reported modulators. An extensive analysis of the structure-based and ligand- based in silico methods aimed at PKM2 modulation has been conducted with an in-depth review of the literature. The role of advanced tools like QSAR and quantum mechanics has been established with a brief discussion of future perspectives.

Mechanical coupling in the nitrogenase complex

The enzyme nitrogenase reduces dinitrogen to ammonia utilizing electrons, protons, and energy obtained from the hydrolysis of ATP. Mo-dependent nitrogenase is a symmetric dimer, with each half comprising an ATP-dependent reductase, termed the Fe Protein, and a catalytic protein, known as the MoFe protein, which hosts the electron transfer P-cluster and the active-site metal cofactor (FeMo-co). A series of synchronized events for the electron transfer have been characterized experimentally, in which electron delivery is coupled to nucleotide hydrolysis and regulated by an intricate allosteric network. We report a graph theory analysis of the mechanical coupling in the nitrogenase complex as a key step to understanding the dynamics of allosteric regulation of nitrogen reduction. This analysis shows that regions near the active sites undergo large-scale, large-amplitude correlated motions that enable communications within each half and between the two halves of the complex. Computational predictions of mechanically regions were validated against an analysis of the solution phase dynamics of the nitrogenase complex via hydrogen-deuterium exchange. These regions include the P-loops and the switch regions in the Fe proteins, the loop containing the residue β-188Ser adjacent to the P-cluster in the MoFe protein, and the residues near the protein-protein interface. In particular, it is found that: (i) within each Fe protein, the switch regions I and II are coupled to the [4Fe-4S] cluster; (ii) within each half of the complex, the switch regions I and II are coupled to the loop containing β-188Ser; (iii) between the two halves of the complex, the regions near the nucleotide binding pockets of the two Fe proteins (in particular the P-loops, located over 130 Å apart) are also mechanically coupled. Notably, we found that residues next to the P-cluster (in particular the loop containing β-188Ser) are important for communication between the two halves.

H/D Exchange Characterization of Silent Coupling: Entropy-Enthalpy Compensation in Allostery

The allosteric coupling constant in K-type allosteric systems is defined as a ratio of the binding of substrate in the absence of effector to the binding of the substrate in the presence of a saturating concentration of effector. As a result, the coupling constant is itself an equilibrium value comprised of a ΔH and a TΔS component. In the scenario in which TΔS completely compensates ΔH, no allosteric influence of effector binding on substrate affinity is observed. However, in this "silent coupling" scenario, the presence of effector causes a change in the ΔH associated with substrate binding. A suggestion has now been made that "silent modulators" are ideal drug leads because they can be modified to act as either allosteric activators or inhibitors. Any attempt to rationally design the effector to be an allosteric activator or inhibitor is likely to be benefitted by knowledge of the mechanism that gives rise to coupling. Hydrogen/deuterium exchange with mass spectrometry detection has now been used to identify regions of proteins that experience conformational and/or dynamic changes in the allosteric regulation. Here, we demonstrate the expected temperature dependence of the allosteric regulation of rabbit muscle pyruvate kinase by Ala to demonstrate that this effector reduces substrate (phosphoenolpyruvate) affinity at 35°C and at 10°C but is silent at intermediate temperatures. We then explore the use of hydrogen/deuterium exchange with mass spectrometry to evaluate the areas of the protein that are modified in the mechanism that gives rise to the silent coupling between Ala and phosphoenolpyruvate. Many of the peptide regions of the protein identified as changing in this silent system (Ala as the effector) were included in changes previously identified for allosteric inhibition by Phe.

Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s

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Dynamics and allosteric potentials of the RFTS domain are proposed.

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Hinge sites located at the RFTS-CD interface are key regulators for inter-domain interactions.

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Network analysis reveals local allosteric networks and inter-domain communication pathways in DNMT1.

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A potential allosteric site at the TRD interface for DNMT1 is identified.

DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.

Functional tunability from a distance: Rheostat positions influence allosteric coupling between two distant binding sites

For protein mutagenesis, a common expectation is that important positions will behave like on/off “toggle” switches (i.e., a few substitutions act like wildtype, most abolish function). However, there exists another class of important positions that manifests a wide range of functional outcomes upon substitution: “rheostat” positions. Previously, we evaluated rheostat positions located near the allosteric binding sites for inhibitor alanine (Ala) and activator fructose-1,6-bisphosphate (Fru-1,6-BP) in human liver pyruvate kinase. When substituted with multiple amino acids, many positions demonstrated moderate rheostatic effects on allosteric coupling between effector binding and phosphoenolpyruvate (PEP) binding in the active site. Nonetheless, the combined outcomes of all positions sampled the full range of possible allosteric coupling (full tunability). However, that study only evaluated allosteric tunability of “local” positions, i.e., positions were located near the binding sites of the allosteric ligand being assessed. Here, we evaluated tunability of allosteric coupling when mutated sites were distant from the allosterically-coupled binding sites. Positions near the Ala binding site had rheostatic outcomes on allosteric coupling between Fru-1,6-BP and PEP binding. In contrast, positions in the Fru-1,6-BP site exhibited modest effects on coupling between Ala and PEP binding. Analyzed in aggregate, both PEP/Ala and PEP/Fru-1,6-BP coupling were again fully tunable by amino acid substitutions at this limited set of distant positions. Furthermore, some positions exhibited rheostatic control over multiple parameters and others exhibited rheostatic effects on one parameter and toggle control over a second. These findings highlight challenges in efforts to both predict/interpret mutational outcomes and engineer functions into proteins.