Relating Protein Motion to Catalysis

Unraveling the Interplay between Stability and Flexibility in the Design of Polyethylene Terephthalate (PET) Hydrolases

The accumulation of polyethylene terephthalate (PET), a widely used polyester plastic in packaging and textiles, has led to a global environmental crisis. Biodegradation presents a promising strategy for PET recycling, with PET hydrolases (PETase) undertaking the task at the molecular level. Unfortunately, PETase operates only at ambient temperatures with low efficiency, limiting its industrial application. Current engineering efforts focus on enhancing the thermostability of PETase, but increased stability can reduce the structural dynamics needed for substrate binding, potentially slowing enzymatic activity. To elucidate the balance between stability and flexibility in optimizing PETase catalytic activity, we performed theoretical investigations on both wild-type PETase (WT-PETase) and a thermophilic variant (Thermo-PETase) using molecular dynamics simulations and frustration analysis. Despite being initially designed to stabilize the native structure of the enzyme, our findings reveal that Thermo-PETase exhibits an unprecedented increase in structural flexibility at the PET-binding and catalytic sites, beneficial for substrate recruitment and product release, compared to WT-PETase. Upon PET binding, we observed that the structural dynamics of Thermo-PETase is largely quenched, favoring the proximity between the catalytic residues and the carbonyl of the PET substrate. This may potentially contribute to a higher probability of a catalytic reaction occurring in Thermo-PETase compared to WT-PETase. We suggest that Thermo-PETase can exhibit higher PET-degradation performance than WT-PETase across a broad temperature range by leveraging stability and flexibility at high and low temperatures, respectively. Our findings provide valuable insights into how PETase optimizes its enzymatic performance by balancing stability and flexibility, which may contribute to future PETase design strategies.

Conformational Modulation of a Mobile Loop Controls Catalysis in the (βα)8-Barrel Enzyme of Histidine Biosynthesis HisF

The overall significance of loop motions for enzymatic activity is generally accepted. However, it has largely remained unclear whether and how such motions can control different steps of catalysis. We have studied this problem on the example of the mobile active site β1α1-loop (loop1) of the (βα)8-barrel enzyme HisF, which is the cyclase subunit of imidazole glycerol phosphate synthase. Loop1 variants containing single mutations of conserved amino acids showed drastically reduced rates for the turnover of the substrates N'-[(5'-phosphoribulosyl) formimino]-5-aminoimidazole-4-carboxamide ribonucleotide (PrFAR) and ammonia to the products imidazole glycerol phosphate (ImGP) and 5-aminoimidazole-4-carboxamide-ribotide (AICAR). A comprehensive mechanistic analysis including stopped-flow kinetics, X-ray crystallography, NMR spectroscopy, and molecular dynamics simulations detected three conformations of loop1 (open, detached, closed) whose populations differed between wild-type HisF and functionally affected loop1 variants. Transient stopped-flow kinetic experiments demonstrated that wt-HisF binds PrFAR by an induced-fit mechanism whereas catalytically impaired loop1 variants bind PrFAR by a simple two-state mechanism. Our findings suggest that PrFAR-induced formation of the closed conformation of loop1 brings active site residues in a productive orientation for chemical turnover, which we show to be the rate-limiting step of HisF catalysis. After the cyclase reaction, the closed loop conformation is destabilized, which favors the formation of detached and open conformations and hence facilitates the release of the products ImGP and AICAR. Our data demonstrate how different conformations of active site loops contribute to different catalytic steps, a finding that is presumably of broad relevance for the reaction mechanisms of (βα)8-barrel enzymes and beyond.

Rare Events Sampling Methods for Quantum and Classical Ab Initio Molecular Dynamics

We provide an approach to sample rare events during classical ab initio molecular dynamics and quantum wavepacket dynamics. For classical AIMD, a set of fictitious degrees of freedom are introduced that may harmonically interact with the electronic and nuclear degrees of freedom to steer the dynamics in a conservative fashion toward energetically forbidden regions. A similar approach when introduced for quantum wavepacket dynamics has the effect of biasing the trajectory of the wavepacket centroid toward the regions of the potential surface that are difficult to sample. The approach is demonstrated for a phenol-amine system, which is a prototypical problem for condensed phase-proton transfer, and for model potentials undergoing wavepacket dynamics. In all cases, the approach yields trajectories that conserve energy while sampling rare events.

Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase

The role of dynamics in enzymatic function is a highly debated topic. Dihydrofolate reductase (DHFR), due to its universality and the depth with which it has been studied, is a model system in this debate. Myriad previous works have identified networks of residues in positions near to and remote from the active site that are involved in dynamics and others that are important for catalysis. For example, specific mutations on the Met20 loop in E. coli DHFR (N23PP/S148A) are known to disrupt millisecond-timescale motions and reduce catalytic activity. However, how and if networks of dynamically coupled residues influence the evolution of DHFR is still an unanswered question. In this study, we first identify, by statistical coupling analysis and molecular dynamic simulations, a network of coevolving residues, which possess increased correlated motions. We then go on to show that allosteric communication in this network is selectively knocked down in N23PP/S148A mutant E. coli DHFR. Finally, we identify two sites in the human DHFR sector which may accommodate the Met20 loop double proline mutation while preserving dynamics. These findings strongly implicate protein dynamics as a driving force for evolution.

Identification of the Thermal Activation Network in Human 15-Lipoxygenase-2: Divergence from Plant Orthologs and Its Relationship to Hydrogen Tunneling Activation Barriers

The oxidation of polyunsaturated fatty acids by lipoxygenases (LOXs) is initiated by a C-H cleavage step in which the hydrogen atom is transferred quantum mechanically (i.e., via tunneling). In these reactions, protein thermal motions facilitate the conversion of ground-state enzyme-substrate complexes to tunneling-ready configurations and are thus important for transferring energy from the solvent to the active site for the activation of catalysis. In this report, we employed temperature-dependent hydrogen-deuterium exchange mass spectrometry (TDHDX-MS) to identify catalytically linked, thermally activated peptides in a representative animal LOX, human epithelial 15-LOX-2. TDHDX-MS of wild-type 15-LOX-2 was compared to two active site mutations that retain structural stability but have increased activation energies (Ea) of catalysis. The Ea value of one variant, V427L, is implicated to arise from suboptimal substrate positioning by increased active-site side chain rotamer dynamics, as determined by X-ray crystallography and ensemble refinement. The resolved thermal network from the comparative Eas of TDHDX-MS between wild-type and V426A is localized along the front face of the 15-LOX-2 catalytic domain. The network contains a clustering of isoleucine, leucine, and valine side chains within the helical peptides. This thermal network of 15-LOX-2 is different in location, area, and backbone structure compared to a model plant lipoxygenase from soybean that exhibits a low Ea value of catalysis compared to the human ortholog. The presented data provide insights into the divergence of thermally activated protein motions in plant and animal LOXs and their relationships to the enthalpic barriers for facilitating hydrogen tunneling.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study, we employ this paradigm to answer a basic question: in enzyme superfamilies, where the catalytic mechanism, active sites, and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as representatives of the conserved protein tyrosine phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of the catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Origin of the multi-phasic quenching dynamics in the BLUF domains across the species

Blue light using flavin (BLUF) photoreceptors respond to light via one of nature's smallest photo-switching domains. Upon photo-activation, the flavin cofactor in the BLUF domain exhibits multi-phasic dynamics, quenched by a proton-coupled electron transfer reaction involving the conserved Tyr and Gln. The dynamic behavior varies drastically across different species, the origin of which remains controversial. Here, we incorporate site-specific fluorinated Trp into three BLUF proteins, i.e., AppA, OaPAC and SyPixD, and characterize the percentages for the Wout, WinNHin and WinNHout conformations using 19F nuclear magnetic resonance spectroscopy. Using femtosecond spectroscopy, we identify that one key WinNHin conformation can introduce a branching one-step proton transfer in AppA and a two-step proton transfer in OaPAC and SyPixD. Correlating the flavin quenching dynamics with the active-site structural heterogeneity, we conclude that the quenching rate is determined by the percentage of WinNHin, which encodes a Tyr-Gln configuration that is not conducive to proton transfer.

Conformational Dynamics in Proteins: Entangled Slow Fluctuations and Nonequilibrium Reaction Events

Proteins exhibit conformational fluctuations and changes over various time scales, ranging from rapid picosecond-scale local atomic motions to slower microsecond-scale global conformational transformations. In the presence of these intricate fluctuations, chemical reactions occur and functions emerge. These conformational fluctuations of proteins are not merely stochastic random motions but possess distinct spatiotemporal characteristics. Moreover, chemical reactions do not always proceed along a single reaction coordinate in a quasi-equilibrium manner. Therefore, it is essential to understand spatiotemporal conformational fluctuations of proteins and the conformational change processes associated with reactions. In this Perspective, we shed light on the complex dynamics of proteins and their role in enzyme catalysis by presenting recent results regarding dynamic couplings and disorder in the conformational dynamics of proteins and rare but rapid enzymatic reaction events obtained from molecular dynamics simulations.

Ratcheting synthesis

Synthetic chemistry has traditionally relied on reactions between reactants of high chemical potential and transformations that proceed energetically downhill to either a global or local minimum (thermodynamic or kinetic control). Catalysts can be used to manipulate kinetic control, lowering activation energies to influence reaction outcomes. However, such chemistry is still constrained by the shape of one-dimensional reaction coordinates. Coupling synthesis to an orthogonal energy input can allow ratcheting of chemical reaction outcomes, reminiscent of the ways that molecular machines ratchet random thermal motion to bias conformational dynamics. This fundamentally distinct approach to synthesis allows multi-dimensional potential energy surfaces to be navigated, enabling reaction outcomes that cannot be achieved under conventional kinetic or thermodynamic control. In this Review, we discuss how ratcheted synthesis is ubiquitous throughout biology and consider how chemists might harness ratchet mechanisms to accelerate catalysis, drive chemical reactions uphill and programme complex reaction sequences.

Two-Legged Molecular Walker and Curvature: Mechanochemical Ring Migration on Graphene

Attaining controllable molecular motion at the nanoscale can be beneficial for multiple reasons, spanning from optoelectronics to catalysis. Here we study the movement of a two-legged molecular walker by modeling the migration of a phenyl aziridine ring on curved graphene. We find that directional ring migration can be attained on graphene in the cases of both 1D (wrinkled/rippled) and 2D (bubble-shaped) curvature. Using a descriptor approach based on graphene's frontier orbital orientation, we can understand the changes in binding energy of the ring as it translates across different sites with variable curvature and the kinetic barriers associated with ring migration. Additionally, we show that the extent of covalent bonding between graphene and the molecule at different sites directly controls the binding energy gradient, propelling molecular migration. Importantly, one can envision such walkers as carriers of charge and disruptors of local bonding. This study enables a new way to tune the electronic structure of two-dimensional materials for a range of applications.

Unveiling Switching Function of Amino Acids in Proteins Using a Machine Learning Approach

Dynamics of individual amino acids play key roles in the overall properties of proteins. However, the knowledge of protein structural features at the residue level is limited due to the current resolutions of experimental and computational techniques. To address this issue, we designed a novel machine-learning (ML) framework that uses Molecular Dynamics (MD) trajectories to identify the major conformational states of individual amino acids, classify amino acids switching between two distinct modes, and evaluate their degree of dynamic stability. The Random Forest model achieved 96.94% classification accuracy in identifying switch residues within proteins. Additionally, our framework distinguishes between the stable switch (SS) residues, which remain stable in one angular state and jump once to another state during protein dynamics, and unstable switch (US) residues, which constantly fluctuate between the two angular states. This study also illustrates the correlation between the dynamics of SS residues and the protein's global properties.

Dynamic Domain Links Substrate Binding and Catalysis in the Factor-Inhibiting-HIF-1

The interplay between active-site chemistry and functionally relevant enzyme motions can provide useful insights into selective enzyme modulation. Modulation of the hypoxia-sensing function of factor-inhibiting-HIF-1 (FIH) enzyme is a potential therapeutic strategy in disease states such as ischemia and cancer. The hypoxia-sensing function of FIH relies in major part on the tight coupling of the first half of the catalytic mechanism which involves O2 activation and eventual succinate production to the second half which involves HIF-1α/CTAD substrate hydroxylation. In this study, we demonstrate the role of a loop hinge domain in FIH (FIH102-118) called the 100s loop in maintaining this particular tight coupling. Molecular dynamics patterns from Gaussian Network Model (iGNM) database analysis of FIH identified the 100s loop as one dynamic domain containing a hinge residue (Tyr102) with a potential substrate positioning role. Enzymological and biophysical studies of the 100s loop point mutants revealed altered enzyme kinetics with the exception of the conservative FIH mutant Y102F, which suggests a sterics-related role for this residue. Removal of the bulk of Tyr102 (Y102A) resulted in succinate production, autohydroxylation, and an O2 binding environment comparable to wild-type FIH. However, the HIF-1α/CTAD substrate hydroxylation of this mutant was significantly reduced which implies that (1) the FIH loop hinge residue Tyr102 does not affect O2 activation, (2) the stacking steric interaction of Tyr102 is important in substrate positioning for productive hydroxylation, and (3) Tyr102 is important for the synchronization of O2 activation and substrate hydroxylation.

Loop dynamics and the evolution of enzyme activity

In the early 2000s, Tawfik presented his 'New View' on enzyme evolution, highlighting the role of conformational plasticity in expanding the functional diversity of limited repertoires of sequences. This view is gaining increasing traction with increasing evidence of the importance of conformational dynamics in both natural and laboratory evolution of enzymes. The past years have seen several elegant examples of harnessing conformational (particularly loop) dynamics to successfully manipulate protein function. This Review revisits flexible loops as critical participants in regulating enzyme activity. We showcase several systems of particular interest: triosephosphate isomerase barrel proteins, protein tyrosine phosphatases and β-lactamases, while briefly discussing other systems in which loop dynamics are important for selectivity and turnover. We then discuss the implications for engineering, presenting examples of successful loop manipulation in either improving catalytic efficiency, or changing selectivity completely. Overall, it is becoming clearer that mimicking nature by manipulating the conformational dynamics of key protein loops is a powerful method of tailoring enzyme activity, without needing to target active-site residues.

Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics

Dynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study we employ this paradigm to answer a basic question: in enzyme superfamilies where the catalytic mechanism, active sites and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as the representatives of the conserved Protein Tyrosine Phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.

Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology

Using high-throughput microfluidic enzyme kinetics (HT-MEK), we measured over 9,000 inhibition curves detailing impacts of 1,004 single-site mutations throughout the alkaline phosphatase PafA on binding affinity for two transition state analogs (TSAs), vanadate and tungstate. As predicted by catalytic models invoking transition state complementary, mutations to active site and active-site-contacting residues had highly similar impacts on catalysis and TSA binding. Unexpectedly, most mutations to more distal residues that reduced catalysis had little or no impact on TSA binding and many even increased tungstate affinity. These disparate effects can be accounted for by a model in which distal mutations alter the enzyme's conformational landscape, increasing the occupancy of microstates that are catalytically less effective but better able to accommodate larger transition state analogs. In support of this ensemble model, glycine substitutions (rather than valine) were more likely to increase tungstate affinity (but not more likely to impact catalysis), presumably due to increased conformational flexibility that allows previously disfavored microstates to increase in occupancy. These results indicate that residues throughout an enzyme provide specificity for the transition state and discriminate against analogs that are larger only by tenths of an Ångström. Thus, engineering enzymes that rival the most powerful natural enzymes will likely require consideration of distal residues that shape the enzyme's conformational landscape and fine-tune active-site residues. Biologically, the evolution of extensive communication between the active site and remote residues to aid catalysis may have provided the foundation for allostery to make it a highly evolvable trait.

Conserved Conformational Dynamics Reveal a Key Dynamic Residue in the Gatekeeper Loop of Human Cyclophilins

Cyclophilins are ubiquitous human enzymes that catalyze peptidyl-prolyl cis-trans isomerization in protein substrates. Of the 17 unique isoforms, five closely related isoforms (CypA-E) are found in various environments and participate in diverse cellular processes, yet all have similar structures and the same core catalytic function. The question is what key residues are behind the conserved function of these enzymes. Here, conformational dynamics are compared across these isoforms to detect conserved dynamics essential for the catalytic activity of cyclophilins. A set of key dynamic residues, defined by the most dynamically conserved positions, are identified in the gatekeeper 2 region. The highly conserved glycine (Gly80) in this region is predicted to underlie the local flexibility, which is further tested by molecular dynamics simulations performed on mutants (G80A) of CypE and CypA. The mutation leads to decreased flexibility of CypE and CypA during substrate binding but increased flexibility during catalysis. Dynamical changes occur in the mutated region and a distal loop downstream of the mutation site in sequence. Examinations of the mutational effect on catalysis show that both mutated CypE and CypA exhibit shifted binding free energies of the substrate under distinct isomer conformations. The results suggest a loss of function in the mutated CypE and CypA. These catalytic changes by the mutation are likely independent of the substrate sequence, at least in CypA. Our work presents a method to identify function-related key residues in proteins.

Non-active Site Residue in Loop L4 Alters Substrate Capture and Product Release in d-Arginine Dehydrogenase

Numerous studies demonstrate that enzymes undergo multiple conformational changes during catalysis. The malleability of enzymes forms the basis for allosteric regulation: residues located far from the active site can exert long-range dynamical effects on the active site residues to modulate catalysis. The structure of Pseudomonas aeruginosa d-arginine dehydrogenase (PaDADH) shows four loops (L1, L2, L3, and L4) that span the substrate and the FAD-binding domains. Loop L4 comprises residues 329-336, spanning over the flavin cofactor. The I335 residue on loop L4 is ∼10 Å away from the active site and ∼3.8 Å from N(1)-C(2)═O atoms of the flavin. In this study, we used molecular dynamics and biochemical techniques to investigate the effect of the mutation of I335 to histidine on the catalytic function of PaDADH. Molecular dynamics showed that the conformational dynamics of PaDADH are shifted to a more closed conformation in the I335H variant. In agreement with an enzyme that samples more in a closed conformation, the kinetic data of the I335H variant showed a 40-fold decrease in the rate constant of substrate association (k₁), a 340-fold reduction in the rate constant of substrate dissociation from the enzyme-substrate complex (k₂), and a 24-fold decrease in the rate constant of product release (k₅), compared to that of the wild-type. Surprisingly, the kinetic data are consistent with the mutation having a negligible effect on the reactivity of the flavin. Altogether, the data indicate that the residue at position 335 has a long-range dynamical effect on the catalytic function in PaDADH.

Looking at Biomolecular Interactions through the Lens of Correlated Fluorescence Microscopy and Optical Tweezers

Understanding complex biological events at the molecular level paves the path to determine mechanistic processes across the timescale necessary for breakthrough discoveries. While various conventional biophysical methods provide some information for understanding biological systems, they often lack a complete picture of the molecular-level details of such dynamic processes. Studies at the single-molecule level have emerged to provide crucial missing links to understanding complex and dynamic pathways in biological systems, which are often superseded by bulk biophysical and biochemical studies. Latest developments in techniques combining single-molecule manipulation tools such as optical tweezers and visualization tools such as fluorescence or label-free microscopy have enabled the investigation of complex and dynamic biomolecular interactions at the single-molecule level. In this review, we present recent advances using correlated single-molecule manipulation and visualization-based approaches to obtain a more advanced understanding of the pathways for fundamental biological processes, and how this combination technique is facilitating research in the dynamic single-molecule (DSM), cell biology, and nanomaterials fields.

Structural features, temperature adaptation and industrial applications of microbial lipases from psychrophilic, mesophilic and thermophilic origins

Microbial lipases are very prominent biocatalysts because of their ability to catalyze a wide variety of reactions in aqueous and non-aqueous media. Here microbial lipases from different origins (psychrophiles, mesophiles, and thermophiles) have been reviewed. This review emphasizes an update of structural diversity in temperature adaptation and industrial applications, of psychrophilic, mesophilic, and thermophilic lipases. The microbial origins of lipases are logically dynamic, proficient, and also have an extensive range of industrial uses with the manufacturing of altered molecules. It is therefore of interest to understand the molecular mechanisms of adaptation to temperature in occurring lipases. However, lipases from extremophiles (psychrophiles, and thermophiles) are widely used to design biotransformation reactions with higher yields, fewer byproducts, or useful side products and have been predicted to catalyze those reactions also, which otherwise are not possible with the mesophilic lipases. Lipases as a multipurpose biological catalyst have given a favorable vision in meeting the needs of several industries such as biodiesel, foods, and drinks, leather, textile, detergents, pharmaceuticals, and medicals.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Increasing the O2 Resistance of the [FeFe]-Hydrogenase CbA5H through Enhanced Protein Flexibility

The high turnover rates of [FeFe]-hydrogenases under mild conditions and at low overpotentials provide a natural blueprint for the design of hydrogen catalysts. However, the unique active site (H-cluster) degrades upon contact with oxygen. The [FeFe]-hydrogenase fromClostridium beijerinckii (CbA5H) is characterized by the flexibility of its protein structure, which allows a conserved cysteine to coordinate to the active site under oxidative conditions. Thereby, intrinsic cofactor degradation induced by dioxygen is minimized. However, the protection from O₂ is only partial, and the activity of the enzyme decreases upon each exposure to O₂. By using site-directed mutagenesis in combination with electrochemistry, ATR-FTIR spectroscopy, and molecular dynamics simulations, we show that the kinetics of the conversion between the oxygen-protected inactive state (cysteine-bound) and the oxygen-sensitive active state can be accelerated by replacing a surface residue that is very distant from the active site. This sole exchange of methionine for a glutamate residue leads to an increased resistance of the hydrogenase to dioxygen. With our study, we aim to understand how local modifications of the protein structure can have a crucial impact on protein dynamics and how they can control the reactivity of inorganic active sites through outer sphere effects.

Modeling Ensembles of Enzyme Reaction Pathways with Hi-MSM Reveals the Importance of Accounting for Pathway Diversity

Conventional quantum mechanical-molecular mechanics (QM/MM) simulation approaches for modeling enzyme reactions often assume that there is one dominant reaction pathway and that this pathway can be sampled starting from an X-ray structure of the enzyme. These assumptions reduce computational cost; however, their validity has not been extensively tested. This is due in part to the lack of a rigorous formalism for integrating disparate pathway information from dynamical QM/MM calculations. Here, we present a way to model ensembles of reaction pathways efficiently using a divide-and-conquer strategy through Hierarchical Markov State Modeling (Hi-MSM). This approach allows information on multiple, distinct pathways to be incorporated into a chemical kinetic model, and it allows us to test these two assumptions. Applying Hi-MSM to the reaction carried out by dihydrofolate reductase (DHFR) we find (i) there are multiple, distinct pathways significantly contributing to the overall flux of the reaction that the conventional approach does not identify and (ii) that the conventional approach does not identify the dominant reaction pathway. Thus, both assumptions underpinning the conventional approach are violated. Since DHFR is a relatively small enzyme, and configuration space scales exponentially with protein size, accounting for multiple reaction pathways is likely to be necessary for most enzymes.

Comparison of the Role of Protein Dynamics in Catalysis by Dihydrofolate Reductase from E. coli and H. sapiens

Dihydrofolate reductase (DHFR) is a well-studied, clinically relevant enzyme known for being highly dynamic over the course of its catalytic cycle. However, the role dynamic motions play in the explicit hydride transfer from the nicotinamide cofactor to the dihydrofolate substrate remains unclear because reaction initiation and direct spectroscopic examination on the appropriate time scale for such femtosecond to picosecond motions is challenging. Here, we employ pre-steady-state kinetics to observe the hydride transfer as directly as possible in two different species of DHFR: Escherichia coli and Homo sapiens. While the hydride transfer has been well-characterized in DHFR from E. coli, improvements in time resolution now allow for sub-millisecond dead times for stopped-flow spectroscopy, which reveals that the maximum rate is indeed faster than previously recorded. The rate in the human enzyme, previously only estimated, is also able to be directly observed using cutting-edge stopped-flow instrumentation. In addition to the pH dependence of the hydride transfer rates for both enzymes, we examine the primary H/D kinetic isotope effect to reveal a temperature dependence in the human enzyme that is absent from the E. coli counterpart. This dependence, which appears above a temperature of 15 °C is a shared feature among other hydride transfer enzymes and is also consistent with computational work suggesting the presence of a fast promoting-vibration that provides donor-acceptor compression on the time scale of catalysis to facilitate the chemistry step.

A single nucleotide polymorphism of the thyrotropin releasing hormone degrading ectoenzyme (TRHDE) gene is associated with post-partum anestrus in Murrah buffalo

Thyrotropin releasing hormone degrading enzyme (TRHDE) gene is implicated in Thyrotropin releasing hormone (TRH) mediated prolactin secretion. It has been shown that the prolactin secretion alters the Gonadotropin-releasinghormone(GnRH) mediated estrous cycle. Therefore, TRHDE may also regulate postpartum anestrus. Earlier studies reported the role of non-synonymous single nucleotide polymorphism (SNPs) in various pathophysiological conditions by altering the structure and function of the proteins. Hence, in the present study, we identified SNPs in the putative promoter, first exon, middle exon and 3'-UTR containing the last exon of TRHDE gene and determined their association with postpartum anestrus (PPA) in Murrah buffaloes. We found one non synonymous SNP (G > C at 118095875 bp on chromosome 4) in the first exon of TRHDE and performed its association analysis in a population sample of 50 extreme PPA (residual PPAI: 123.06 ± 12.98 days) and 50 normal (residual PPAI: -80.46 ± 3.19 days) buffaloes. The residual PPAI value was the observed PPAI adjusted for the effect of 38 non-genetic factors. The analysis showed a significant (P < 0.004167) association of this SNP with PPA in buffaloes. Molecular dynamics simulations (MDS) also supported that the C allele altering Glutamine to Histidine at the amino acid 148 of TRHDE could enhance the stability and rigidity of TRHDE protein, which may lower its activity, increase TRH and prolactin, and reduce GnRH in PPA buffaloes. The MDS analysis further strengthens the association of the SNP (G > C) in the TRHDE gene with PPA condition in Murrah buffaloes. However, further investigation is needed to prove the MDS observations.

Enabling Role of Ligand-Driven Conformational Changes in Enzyme Evolution

Many enzymes that show a large specificity in binding the enzymatic transition state with a higher affinity than the substrate utilize substrate binding energy to drive protein conformational changes to form caged substrate complexes. These protein cages provide strong stabilization of enzymatic transition states. Using part of the substrate binding energy to drive the protein conformational change avoids a similar strong stabilization of the Michaelis complex and irreversible ligand binding. A seminal step in the development of modern enzyme catalysts was the evolution of enzymes that couple substrate binding to a conformational change. These include enzymes that function in glycolysis (triosephosphate isomerase), the biosynthesis of lipids (glycerol phosphate dehydrogenase), the hexose monophosphate shunt (6-phosphogluconate dehydrogenase), and the mevalonate pathway (isopentenyl diphosphate isomerase), catalyze the final step in the biosynthesis of pyrimidine nucleotides (orotidine monophosphate decarboxylase), and regulate the cellular levels of adenine nucleotides (adenylate kinase). The evolution of enzymes that undergo ligand-driven conformational changes to form active protein-substrate cages is proposed to proceed by selection of variants, in which the selected side chain substitutions destabilize a second protein conformer that shows compensating enhanced binding interactions with the substrate. The advantages inherent to enzymes that incorporate a conformational change into the catalytic cycle provide a strong driving force for the evolution of flexible protein folds such as the TIM barrel. The appearance of these folds represented a watershed event in enzyme evolution that enabled the rapid propagation of enzyme activities within enzyme superfamilies.

Beyond structure: Deciphering site-specific dynamics in proteins from double histidine-based EPR measurements

Site-specific dynamics in proteins are at the heart of protein function. While electron paramagnetic resonance (EPR) has potential to measure dynamics in large protein complexes, the reliance on flexible nitroxide labels is limitating especially for the accurate measurement of site-specific β-sheet dynamics. Here, we employed EPR spectroscopy to measure site-specific dynamics across the surface of a protein, GB1. Through the use of the double Histidine (dHis) motif, which enables labeling with a Cu(II) - nitrilotriacetic acid (NTA) complex, dynamics information was obtained for both α-helical and β-sheet sites. Spectral simulations of the resulting CW-EPR report unique site-specific fluctuations across the surface of GB1. Additionally, we performed molecular dynamics (MD) simulations to complement the EPR data. The dynamics observed from MD agree with the EPR results. Furthermore, we observe small changes in gǁ values for different sites, which may be due to small differences in coordination geometry and/or local electrostatics of the site. Taken together, this work expands the utility of Cu(II)NTA-based EPR measurements to probe information beyond distance constraints.

Leveraging intrinsic flexibility to engineer enhanced enzyme catalytic activity

Dynamic motions of enzymes occurring on a broad range of timescales play a pivotal role in all steps of the reaction pathway, including substrate binding, catalysis, and product release. However, it is unknown whether structural information related to conformational flexibility can be exploited for the directed evolution of enzymes with higher catalytic activity. Here, we show that mutagenesis of residues exclusively located at flexible regions distal to the active site of Homo sapiens kynureninase (HsKYNase) resulted in the isolation of a variant (BF-HsKYNase) in which the rate of the chemical step toward kynurenine was increased by 45-fold. Mechanistic pre–steady-state kinetic analysis of the wild type and the evolved enzyme shed light on the underlying effects of distal mutations (>10 Å from the active site) on the rate-limiting step of the catalytic cycle. Hydrogen-deuterium exchange coupled to mass spectrometry and molecular dynamics simulations revealed that the amino acid substitutions in BF-HsKYNase allosterically affect the flexibility of the pyridoxal-5′-phosphate (PLP) binding pocket, thereby impacting the rate of chemistry, presumably by altering the conformational ensemble and sampling states more favorable to the catalyzed reaction.

Hydride Transfer Mechanism of Enzymatic Sugar Nucleotide C2 Epimerization Probed with a Loose-Fit CDP-Glucose Substrate

Transient oxidation–reduction through hydride transfer with tightly bound NAD coenzyme is used by a large class of sugar nucleotide epimerases to promote configurational inversion of carbon stereocenters in carbohydrate substrates. A requirement for the epimerases to coordinate hydride abstraction and re-addition with substrate rotation in the binding pocket poses a challenge for dynamical protein conformational selection linked to enzyme catalysis. Here, we studied the thermophilic C2 epimerase from Thermodesulfatator atlanticus (TaCPa2E) in combination with a slow CDP-glucose substrate (k_cat ≈ 1.0 min^–1; 60 °C) to explore the sensitivity of the enzymatic hydride transfer toward environmental fluctuations affected by temperature (20–80 °C). We determined noncompetitive primary kinetic isotope effects (KIE) due to ²H at the glucose C2 and showed that a normal KIE on the k_cat (^Dk_cat) reflects isotope sensitivity of the hydrogen abstraction to enzyme-NAD⁺ in a rate-limiting transient oxidation. The ^Dk_cat peaked at 40 °C was 6.1 and decreased to 2.1 at low (20 °C) and 3.3 at high temperature (80 °C). The temperature profiles for k_cat with the ¹H and ²H substrate showed a decrease in the rate below a dynamically important breakpoint (∼40 °C), suggesting an equilibrium shift to an impaired conformational landscape relevant for catalysis in the low-temperature region. Full Marcus-like model fits of the rate and KIE profiles provided evidence for a high-temperature reaction via low-frequency conformational sampling associated with a broad distribution of hydride donor–acceptor distances (long-distance population centered at 3.31 ± 0.02 Å), only poorly suitable for quantum mechanical tunneling. Collectively, dynamical characteristics of TaCPa2E-catalyzed hydride transfer during transient oxidation of CDP-glucose reveal important analogies to mechanistically simpler enzymes such as alcohol dehydrogenase and dihydrofolate reductase. A loose-fit substrate (in TaCPa2E) resembles structural variants of these enzymes by extensive dynamical sampling to balance conformational flexibility and catalytic efficiency.

Identification of allosteric fingerprints of alpha-synuclein aggregates in matrix metalloprotease-1 and substrate-specific virtual screening with single molecule insights

Alpha-synuclein (aSyn) has implications in pathological protein aggregations in neurodegeneration. Matrix metalloproteases (MMPs) are broad-spectrum proteases and cleave aSyn, leading to aggregation. Previous reports showed that allosteric communications between the two domains of MMP1 on collagen fibril and fibrin depend on substrates, activity, and ligands. This paper reports quantification of allostery using single molecule measurements of MMP1 dynamics on aSyn-induced aggregates by calculating Forster Resonance Energy Transfer (FRET) between two dyes attached to the catalytic and hemopexin domains of MMP1. The two domains of MMP1 prefer open conformations that are inhibited by a single point mutation E219Q of MMP1 and tetracycline, an MMP inhibitor. A two-state Poisson process describes the interdomain dynamics, where the two states and kinetic rates of interconversion between them are obtained from histograms and autocorrelations of FRET values. Since a crystal structure of aSyn-bound MMP1 is unavailable, binding poses were predicted by molecular docking of MMP1 with aSyn using ClusPro. MMP1 dynamics were simulated using predicted binding poses and compared with the experimental interdomain dynamics to identify an appropriate pose. The selected aSyn-MMP1 binding pose near aSyn residue K45 was simulated and analyzed to define conformational changes at the catalytic site. Allosteric residues in aSyn-bound MMP1 exhibiting strong correlations with the catalytic motif residues were compared with allosteric residues in free MMP1, and aSyn-specific residues were identified. The allosteric residues in aSyn-bound MMP1 are K281, T283, G292, G327, L328, E329, R337, F343, G345, N346, Y348, G353, Q354, D363, Y365, S366, S367, F368, P371, R372, V374, K375, A379, F391, A394, R399, M414, F419, V426, and C466. Shannon entropy was defined to quantify MMP1 dynamics. Virtual screening was performed against a site on selected aSyn-MMP1 binding poses, which showed that lead molecules differ between free MMP1 and substrate-bound MMP1. Also, identifying aSyn-specific allosteric residues in MMP1 enabled further selection of lead molecules. In other words, virtual screening needs to take substrates into account for potential substrate-specific control of MMP1 activity in the future. Molecular understanding of interactions between MMP1 and aSyn-induced aggregates may open up the possibility of degrading aggregates by targeting MMPs.

An Enzyme with High Catalytic Proficiency Utilizes Distal Site Substrate Binding Energy to Stabilize the Closed State but at the Expense of Substrate Inhibition

Understanding the factors that underpin the enormous catalytic proficiencies of enzymes is fundamental to catalysis and enzyme design. Enzymes are, in part, able to achieve high catalytic proficiencies by utilizing the binding energy derived from nonreacting portions of the substrate. In particular, enzymes with substrates containing a nonreacting phosphodianion group coordinated in a distal site have been suggested to exploit this binding energy primarily to facilitate a conformational change from an open inactive form to a closed active form, rather than to either induce ground state destabilization or stabilize the transition state. However, detailed structural evidence for the model is limited. Here, we use β-phosphoglucomutase (βPGM) to investigate the relationship between binding a phosphodianion group in a distal site, the adoption of a closed enzyme form, and catalytic proficiency. βPGM catalyzes the isomerization of β-glucose 1-phosphate to glucose 6-phosphate via phosphoryl transfer reactions in the proximal site, while coordinating a phosphodianion group of the substrate(s) in a distal site. βPGM has one of the largest catalytic proficiencies measured and undergoes significant domain closure during its catalytic cycle. We find that side chain substitution at the distal site results in decreased substrate binding that destabilizes the closed active form but is not sufficient to preclude the adoption of a fully closed, near-transition state conformation. Furthermore, we reveal that binding of a phosphodianion group in the distal site stimulates domain closure even in the absence of a transferring phosphoryl group in the proximal site, explaining the previously reported β-glucose 1-phosphate inhibition. Finally, our results support a trend whereby enzymes with high catalytic proficiencies involving phosphorylated substrates exhibit a greater requirement to stabilize the closed active form.

Machine Learning Approaches for Metalloproteins

Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.

Tuning Protein Dynamics to Sense Rapid Endoplasmic-Reticulum Calcium Dynamics

Multi-scale calcium (Ca²⁺ ) dynamics, exhibiting wide-ranging temporal kinetics, constitutes a ubiquitous mode of signal transduction. We report a novel endoplasmic-reticulum (ER)-targeted Ca²⁺ indicator, R-CatchER, which showed superior kinetics in vitro (k_off ≥2×10³  s^-1 , k_on ≥7×10⁶  M^-1  s^-1 ) and in multiple cell types. R-CatchER captured spatiotemporal ER Ca²⁺ dynamics in neurons and hotspots at dendritic branchpoints, enabled the first report of ER Ca²⁺ oscillations mediated by calcium sensing receptors (CaSRs), and revealed ER Ca²⁺ -based functional cooperativity of CaSR. We elucidate the mechanism of R-CatchER and propose a principle to rationally design genetically encoded Ca²⁺ indicators with a single Ca²⁺ -binding site and fast kinetics by tuning rapid fluorescent-protein dynamics and the electrostatic potential around the chromophore. The design principle is supported by the development of G-CatchER2, an upgrade of our previous (G-)CatchER with improved dynamic range. Our work may facilitate protein design, visualizing Ca²⁺ dynamics, and drug discovery.

Molecular Mechanism of Methanol Inhibition in CALB-Catalyzed Alcoholysis: Analyzing Molecular Dynamics Simulations by a Markov State Model

Lipases are widely used enzymes that catalyze hydrolysis and alcoholysis of fatty acid esters. At high concentrations of small alcohols such as methanol or ethanol, many lipases are inhibited by the substrate. The molecular basis of the inhibition of Candida antarctica lipase B (CALB) by methanol was investigated by unbiased molecular dynamics (MD) simulations, and the substrate binding kinetics was analyzed by Markov state models (MSMs). The modeled fluxes of productive methanol binding at concentrations between 50 mM and 5.5 M were in good agreement with the experimental activity profile of CALB, with a peak at 300 mM. The kinetic and structural analysis uncovered the molecular basis of CALB inhibition. Beyond 300 mM, the kinetic bottleneck results from crowding of methanol in the substrate access channel, which is caused by the gradual formation of methanol patches close to Leu140 (helix α5), Leu278, and Ile285 (helix α10) at a distance of 4-5 Å from the active site. Our findings demonstrate the usefulness of unbiased MD simulations to study enzyme-substrate interactions at realistic substrate concentrations and the feasibility of scale-bridging by an MSM analysis to derive kinetic information.

Out-of-Equilibrium Biophysical Chemistry: The Case for Multidimensional, Integrated Single-Molecule Approaches

Out-of-equilibrium processes are ubiquitous across living organisms and all structural hierarchies of life. At the molecular scale, out-of-equilibrium processes (for example, enzyme catalysis, gene regulation, and motor protein functions) cause biological macromolecules to sample an ensemble of conformations over a wide range of time scales. Quantifying and conceptualizing the structure–dynamics to function relationship is challenging because continuously evolving multidimensional energy landscapes are necessary to describe nonequilibrium biological processes in biological macromolecules. In this perspective, we explore the challenges associated with state-of-the-art experimental techniques to understanding biological macromolecular function. We argue that it is time to revisit how we probe and model functional out-of-equilibrium biomolecular dynamics. We suggest that developing integrated single-molecule multiparametric force–fluorescence instruments and using advanced molecular dynamics simulations to study out-of-equilibrium biomolecules will provide a path towards understanding the principles of and mechanisms behind the structure–dynamics to function paradigm in biological macromolecules.

Role of Active Site Loop Dynamics in Mediating Ligand Release from E. coli Dihydrofolate Reductase

Conformational fluctuations from ground-state to sparsely populated but functionally important excited states play a key role in enzyme catalysis. For Escherichia coli dihydrofolate reductase (DHFR), the release of the product tetrahydrofolate (THF) and oxidized cofactor NADP⁺ occurs through exchange between closed and occluded conformations of the Met20 loop. A "dynamic knockout" mutant of E. coli DHFR, where the E. coli sequence in the Met20 loop is replaced by the human sequence (N23PP/S148A), models human DHFR and is incapable of accessing the occluded conformation. ¹H and ¹⁵N CPMG relaxation dispersion analysis for the ternary product complex of the mutant enzyme with NADP⁺ and the product analogue 5,10-dideazatetrahydrofolate (ddTHF) (E:ddTHF:NADP⁺) reveals the mechanism by which NADP⁺ is released when the Met20 loop cannot undergo the closed-to-occluded conformational transition. Two excited states were observed: one related to a faster, relatively high-amplitude conformational fluctuation in areas near the active site, associated with the shuttling of the nicotinamide ring of the cofactor out of the active site, and the other to a slower process where ddTHF undergoes small-amplitude motions within the binding site that are consistent with disorder observed in a room-temperature X-ray crystal structure of the N23PP/S148A mutant protein. These motions likely arise due to steric conflict of the pterin ring of ddTHF with the ribose-nicotinamide moiety of NADP⁺ in the closed active site. These studies demonstrate that site-specific kinetic information from relaxation dispersion experiments can provide intimate details of the changes in catalytic mechanism that result from small changes in local amino acid sequence.

Temperature-Dependent Low-Frequency Modes in the Active Site of Bovine Carbonic Anhydrase II Probed by 2D-IR Spectroscopy

Enzyme catalysis achieves tremendous rate accelerations. Enzyme reaction centers provide a constraint geometry that preferentially binds an activated form of the substrate and thus lowers the energy barrier. However, this transition state picture neglects the flexibility of proteins and its role in enzymatic catalysis. Especially for proton transfer reactions, it has been suggested that motions of the protein modulate the donor-acceptor distance and prepare a tunneling-ready state. We report the detection of frequency fluctuations of an azide anion (N₃^-) bound in the active site of the protein carbonic anhydrase II, where a low-frequency mode of the protein has been proposed to facilitate proton transfer over two water molecules during the catalyzed reaction. 2D-IR spectroscopy resolves an underdamped low-frequency mode at about 1 THz (30 cm^-1). We find its frequency to be viscosity- and temperature-dependent and to decrease by 6 cm^-1 between 230 and 320 K, reporting the softening of the mode's potential.

Dimensional reduction in complex living systems: Where, why, and how

The unprecedented prowess of measurement techniques provides a detailed, multi-scale look into the depths of living systems. Understanding these avalanches of high-dimensional data-by distilling underlying principles and mechanisms-necessitates dimensional reduction. We propose that living systems achieve exquisite dimensional reduction, originating from their capacity to learn, through evolution and phenotypic plasticity, the relevant aspects of a non-random, smooth physical reality. We explain how geometric insights by mathematicians allow one to identify these genuine hallmarks of life and distinguish them from universal properties of generic data sets. We illustrate these principles in a concrete example of protein evolution, suggesting a simple general recipe that can be applied to understand other biological systems.

Molecular configuration-mediated thermo-responsiveness in oligo(ethylene glycol) derivatives attached on gold nanoparticles

Biomolecular systems actively control their local environment on a sub-nm scale via changes in molecular configuration from their flexible structures and derive emergent functions. Although this functional emergence based on local environmental control is attracting a great deal of attention in chemistry, it remains challenging to realize this artificially. Herein, we report the tuning of the thermo-responsive properties of oligo(ethylene glycol) (OEG) derivatives attached on gold nanoparticles via local environmental control not only by the hydrophobic moiety at their terminus but also by their molecular configuration. OEG-attached alkane thiol-modified AuNPs showed thermo-responsive assembly/disassembly in water through the hydration/dehydration of the OEG portions in a manner dependent both on the hydrophobicity at their terminus and the surface curvature of the core nanoparticles. Further, the assembly temperature (T _A) was also tuned by ligand mixing with a non-thermo-responsive ligand with a shorter OEG length. Molecular dynamics simulations show that the distribution of the hydrophobic terminus in the normal direction along the gold surface varied in accordance with the surface curvature, indicating variations in molecular configuration. It is expected that a bent configuration could accelerate the thermo-responsiveness of OEG by allowing them greater accessibility to the hydrophobic terminus. Experimental and simulation results support the notion that local OEG density tuning by surface curvature or ligand mixing with a different OEG length leads to different degrees of accessibility to the hydrophobic terminus via changes in molecular configuration, promoting local environmental control-directed assembly temperature tuning.

A Minireview on Temperature Dependent Protein Conformational Sampling

In this minireview we discuss the role of the more subtle conformational change-protein conformational sampling and connect it to the classic relationship of protein structure and function. The theory of pre-existing functional states of protein are discussed in context of alternate protein conformational sampling. Last, we discuss how temperature, ligand binding and mutations affect the protein conformational sampling mode which is linked to the protein function regulation. The review includes several protein systems that showed temperature dependent protein conformational sampling. We also specifically included two enzyme systems, thermophilic alcohol dehydrogenase (ht-ADH) and thermolysin which we previously studied when discussing temperature dependent protein conformational sampling.

From Bioorganic Models to Cells

I endeavor to share how various choices-some deliberate, some unconscious-and the unmistakable influence of many others shaped my scientific pursuits. I am fascinated by how two long-term, major streams of my research, DNA replication and purine biosynthesis, have merged with unexpected interconnections. If I have imparted to many of the talented individuals who have passed through my lab a degree of my passion for uncloaking the mysteries hidden in scientific research and an understanding of the honesty and rigor it demands and its impact on the world community, then my mentorship has been successful.

A Genetically Encoded Two-Dimensional Infrared Probe for Enzyme Active-Site Dynamics

While two-dimensional infrared (2D-IR) spectroscopy is uniquely suitable for monitoring femtosecond (fs) to picosecond (ps) water dynamics around static protein structures, its utility for probing enzyme active-site dynamics is limited due to the lack of site-specific 2D-IR probes. We demonstrate the genetic incorporation of a novel 2D-IR probe, m-azido-L-tyrosine (N3Y) in the active-site of DddK, an iron-dependent enzyme that catalyzes the conversion of dimethylsulfoniopropionate to dimethylsulphide. Our results show that both the oxidation of active-site iron to Fe^III , and the addition of denaturation reagents, result in significant decrease in enzyme activity and active-site water motion confinement. As tyrosine residues play important roles, including as general acids and bases, and electron transfer agents in many key enzymes, the genetically encoded 2D-IR probe N3Y should be broadly applicable to investigate how the enzyme active-site motions at the fs-ps time scale direct reaction pathways to facilitating specific chemical reactions.

Distal Regions Regulate Dihydrofolate Reductase-Ligand Interactions

Protein motions play a fundamental role in enzyme catalysis and ligand binding. The relationship between protein motion and function has been extensively investigated in the model enzyme dihydrofolate reductase (DHFR). DHFR is an essential enzyme that catalyzes the reduction of dihydrofolate to tetrahydrofolate. Numerous experimental and computational methods have been used to probe the motions of DHFR through the catalytic cycle and to investigate the effect of distal mutations on DHFR motions and ligand binding. These experimental investigations have pushed forward the study of protein motions and their role in protein-ligand interactions. The introduction of mutations distal to the active site has been shown to have profound effects on ligand binding, hydride transfer rates and catalytic efficacy and these changes are captured by enzyme kinetics measurements. Distal mutations have been shown to exert their effects through a network of correlated amino acids and these effects have been investigated by NMR, protein dynamics, and analysis of coupled amino acids. The experimental methods and the findings that are reviewed here have broad implications for our understanding of enzyme mechanisms, ligand binding and for the future design and discovery of enzyme inhibitors.

Microsecond timescale MD simulations at the transition state of PmHMGR predict remote allosteric residues

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to reach the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale. Application of this approach to the second hydride transfer transition state of HMG-CoA reductase from Pseudomonas mevalonii (PmHMGR) identified three remote residues, R396, E399 and L407, (15-27 Å away from the active site) that have a remote dynamic effect on enzyme activity. The predictions were subsequently validated experimentally via site-directed mutagenesis. These results show that microsecond timescale MD simulations of transition states are possible and can predict rather than just rationalize remote allosteric residues.