Large-scale allosteric conformational transitions of adenylate kinase appear to involve a population-shift mechanism

Allostery can convert binding free energies into concerted domain motions in enzymes

Enzymatic mechanisms are typically inferred from structural data. However, understanding enzymes require unravelling the intricate dynamic interplay between dynamics, conformational substates, and multiple protein structures. Here, we use single-molecule nanopore analysis to investigate the catalytic conformational changes of adenylate kinase (AK), an enzyme that catalyzes the interconversion of various adenosine phosphates (ATP, ADP, and AMP). Kinetic analysis validated by hidden Markov models unravels the details of domain motions during catalysis. Our findings reveal that allosteric interactions between ligands and cofactor enable converting binding energies into directional conformational changes of the two catalytic domains of AK. These coordinated motions emerged to control the exact sequence of ligand binding and the affinity for the three different substrates, thereby guiding the reactants along the reaction coordinates. Interestingly, we find that about 10% of enzymes show altered allosteric regulation and ligand affinities, indicating that a subset of enzymes folds in alternative catalytically active forms. Since molecules or proteins might be able to selectively stabilize one of the folds, this observation suggests an evolutionary path for allostery in enzymes. In AK, this complex catalytic framework has likely emerged to prevent futile ATP/ADP hydrolysis and to regulate the enzyme for different energy needs of the cell.

Mechanism of activation and autophosphorylation of a histidine kinase

Histidine kinases (HK) are one of the main prokaryotic signaling systems. Two structurally conserved catalytic domains inside the HK enable autokinase, phosphotransfer, and phosphatase activities. Here, we focus on a detailed mechanistic understanding of the functional cycle of the WalK HK by a multi-scale simulation approach, consisting of classical as well as hybrid QM/MM molecular dynamics simulation. Strikingly, a conformational transition induced solely in DHp leads to the correct activated conformation in CA crucial for autophosphorylation. This finding explains how variable sensor domains induce the transition from inactive to active state. The subsequent autophosphorylation inside DHp proceeds via a penta-coordinated transition state to a protonated phosphohistidine intermediate. This intermediate is consequently deprotonated by a suitable nearby base. The reaction energetics are controlled by the final proton acceptor and presence of a magnesium cation. The slow rates of the process result from the high energy barrier of the conformational transition between inactive and active states. The phosphorylation step exhibits a lower barrier and down-the-hill energetics. Thus, our work suggests a detailed mechanistic model for HK autophosphorylation.

Magnesium induced structural reorganization in the active site of adenylate kinase

Phosphoryl transfer is a fundamental reaction in cellular signaling and metabolism that requires Mg2+ as an essential cofactor. While the primary function of Mg2+ is electrostatic activation of substrates, such as ATP, the full spectrum of catalytic mechanisms exerted by Mg2+ is not known. In this study, we integrate structural biology methods, molecular dynamic (MD) simulations, phylogeny, and enzymology assays to provide molecular insights into Mg2+-dependent structural reorganization in the active site of the metabolic enzyme adenylate kinase. Our results demonstrate that Mg2+ induces a conformational rearrangement of the substrates (ATP and ADP), resulting in a 30° adjustment of the angle essential for reversible phosphoryl transfer, thereby optimizing it for catalysis. MD simulations revealed transitions between conformational substates that link the fluctuation of the angle to large-scale enzyme dynamics. The findings contribute detailed insight into Mg2+ activation of enzymes and may be relevant for reversible and irreversible phosphoryl transfer reactions.

Genome-Wide Identification and Expression Analysis of ADK Gene Family Members in Cotton under Abiotic Stress

Adenosine kinase (ADK) is a key enzyme widely distributed in plants, playing an important role in maintaining cellular energy homeostasis and regulating plant growth, development, and responses to environmental stresses. However, research on ADK genes in cotton (Gossypium hirsutum), an economically significant crop, has been limited. This study identified 92 ADK genes from four cotton species (G. arboreum, G. raimondii, G. hirsutum, and G. barbadense) using HMMER and Local BLASTP methods and classified them into six groups. Chromosomal localization revealed a random distribution of ADK genes in G. hirsutum, with 13 genes located on the At subgenome and 14 genes on the Dt subgenome. Gene structure analysis showed consistency in exon-intron organization within subgroups, while conserved motif analysis identified subgroup-specific motifs, indicating functional diversity. Synteny and collinearity mapping analysis revealed that the primary expansion mechanisms of the ADK gene family in cotton are polyploidy and segmental duplication. Cis-regulatory elements in GhADK promoters were classified into light response, hormone response, developmental regulation, and stress response. We also analyzed the expression patterns of GhADK genes under a low temperature (4 °C) and drought conditions. Most GhADK genes responded to cold stress with different expression patterns, indicating their roles in rapid response and long-term cold adaptation. Under drought stress, expression patterns varied, with some genes showing sustained high expression levels. The qRT-PCR validation of transcriptomic data confirmed the stress-induced expression patterns of selected GhADK genes. Functional analysis through the VIGS silencing of GhADK25 demonstrated its importance in cold and drought stress responses, with silencing resulting in poor growth under stress, highlighting its significance in stress tolerance. This study provides a basis for further understanding the evolutionary relationships and functions of the cotton ADK gene family.

Deeper Insights into Mixed Crowding through Enzyme Activity, Dynamics, and Crowder Diffusion

Given the fact that the cellular interior is crowded by many different kinds of macromolecules, it is important that in vitro studies be carried out in the presence of mixed crowder systems. In this regard, we have used binary crowders formed by the combination of some of the commonly used crowding agents, namely, Ficoll 70, Dextran 70, Dextran 40, and PEG 8000 (PEG 8), to study how these affect enzyme activity, dynamics, and crowder diffusion. The enzyme chosen is AK3L1, an isoform of adenylate kinase. To investigate its dynamics, we have carried out three single point mutations (A74C, A132C, and A209C) with the cysteine residues being labeled with a coumarin-based solvatochromic probe [CPM: (7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin)]. Both enzyme activity and dynamics decreased in the binary mixtures as compared with the sum of the individual crowders, suggesting a reduction in excluded volume (in the mixture). To gain deeper insights into the binary mixtures, fluorescence correlation spectroscopy studies were carried out using fluorescein isothiocyanate-labeled Dextran 70 and tetramethylrhodamine-labeled AK3L1 as the diffusion probes. Diffusion in binary mixtures was observed to be much more constrained (relative to the sum of the individual crowders) for the labeled enzyme as compared to the labeled crowder showing different environments being faced by the two species. This was further confirmed during imaging of the phase-separated droplets formed in the binary mixtures having PEG as one of the crowding agents. The interior of these droplets was found to be rich in crowders and densely packed, as shown by confocal and digital holographic microscopy images, with the enzymes predominantly residing outside these droplets, that is, in the relatively less crowded regions. Taken together, our data provide important insights into various aspects of the simplest form of mixed crowding, that is, composed of just two components, and also hint at the enhanced complexity that the cellular interior presents toward having a detailed and comprehensive understanding of the same.

Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Elucidating Dynamics of Adenylate Kinase from Enzyme Opening to Ligand Release

This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.

Conformation state-specific monobodies regulate the functions of flexible proteins through conformation trapping

Synthetic binding proteins have emerged as modulators of protein functions through protein-protein interactions (PPIs). Because PPIs are influenced by the structural dynamics of targeted proteins, investigating whether the synthetic-binders-based strategy is applicable for proteins with large conformational changes is important. This study demonstrates the applicability of monobodies (fibronectin type-III domain-based synthetic binding proteins) in regulating the functions of proteins that undergo tens-of-angstroms-scale conformational changes, using an example of the A55C/C77S/V169C triple mutant (Adktm ; a phosphoryl transfer-catalyzing enzyme with a conformational change between OPEN/CLOSED forms). Phage display successfully developed monobodies that recognize the OPEN form (substrate-unbound form), but not the CLOSED form of Adktm . Two OPEN form-specific clones (OP-2 and OP-4) inhibited Adktm kinase activity. Epitope mapping with a yeast-surface display/flow cytometry indicated that OP-2 binds to the substrate-entry side of Adktm , whereas OP-4 binding occurs at another site. Small angle X-ray scattering  coupled with size-exclusion chromatography (SEC-SAXS) indicated that OP-4 binds to the hinge side opposite to the substrate-binding site of Adktm , retaining the whole OPEN-form structure of Adktm . Titration of the OP-4-Adktm complex with Ap5 A, a transition-state analog of Adktm , showed that the conformational shift to the CLOSED form was suppressed although Adktm retained the OPEN-form (i.e., substrate-binding ready form). These results show that OP-4 captures and stabilizes the OPEN-form state, thereby affecting the hinge motion. These experimental results indicate that monobody-based modulators can regulate the functions of proteins that show tens-of-angstroms-scale conformational changes, by trapping specific conformational states generated during large conformational change process that is essential for function exertion.

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge-driven or artificial intelligence-driven and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary-structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models that contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly while refining them against the density maps. We introduce such an adaptive decision-making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two prototypical protein systems, adenylate kinase and carbon monoxide dehydrogenase. For these test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2-3 Å map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that are inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from the chimpanzee adenovirus. The overhead for decision making remains low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install R-MDFF on different computing environments, from local Linux-based workstations to high-performance computing environments.

Tackling Hysteresis in Conformational Sampling: How to Be Forgetful with MEMENTO

The structure of proteins has long been recognized to hold the key to understanding and engineering their function, and rapid advances in structural biology and protein structure prediction are now supplying researchers with an ever-increasing wealth of structural information. Most of the time, however, structures can only be determined in free energy minima, one at a time. While conformational flexibility may thus be inferred from static end-state structures, their interconversion mechanisms─a central ambition of structural biology─are often beyond the scope of direct experimentation. Given the dynamical nature of the processes in question, many studies have attempted to explore conformational transitions using molecular dynamics (MD). However, ensuring proper convergence and reversibility in the predicted transitions is extremely challenging. In particular, a commonly used technique to map out a path from a starting to a target conformation called steered MD (SMD) can suffer from starting-state dependence (hysteresis) when combined with techniques such as umbrella sampling (US) to compute the free energy profile of a transition. Here, we study this problem in detail on conformational changes of increasing complexity. We also present a new, history-independent approach that we term "MEMENTO" (Morphing End states by Modelling Ensembles with iNdependent TOpologies) to generate paths that alleviate hysteresis in the construction of conformational free energy profiles. MEMENTO utilizes template-based structure modelling to restore physically reasonable protein conformations based on coordinate interpolation (morphing) as an ensemble of plausible intermediates, from which a smooth path is picked. We compare SMD and MEMENTO on well-characterized test cases (the toy peptide deca-alanine and the enzyme adenylate kinase) before discussing its use in more complicated systems (the kinase P38α and the bacterial leucine transporter LeuT). Our work shows that for all but the simplest systems SMD paths should not in general be used to seed umbrella sampling or related techniques, unless the paths are validated by consistent results from biased runs in opposite directions. MEMENTO, on the other hand, performs well as a flexible tool to generate intermediate structures for umbrella sampling. We also demonstrate that extended end-state sampling combined with MEMENTO can aid the discovery of collective variables on a case-by-case basis.

Mechanistic Basis for a Connection between the Catalytic Step and Slow Opening Dynamics of Adenylate Kinase

Escherichia coli adenylate kinase (AdK) is a small, monomeric enzyme that synchronizes the catalytic step with the enzyme's conformational dynamics to optimize a phosphoryl transfer reaction and the subsequent release of the product. Guided by experimental measurements of low catalytic activity in seven single-point mutation AdK variants (K13Q, R36A, R88A, R123A, R156K, R167A, and D158A), we utilized classical mechanical simulations to probe mutant dynamics linked to product release, and quantum mechanical and molecular mechanical calculations to compute a free energy barrier for the catalytic event. The goal was to establish a mechanistic connection between the two activities. Our calculations of the free energy barriers in AdK variants were in line with those from experiments, and conformational dynamics consistently demonstrated an enhanced tendency toward enzyme opening. This indicates that the catalytic residues in the wild-type AdK serve a dual role in this enzyme's function─one to lower the energy barrier for the phosphoryl transfer reaction and another to delay enzyme opening, maintaining it in a catalytically active, closed conformation for long enough to enable the subsequent chemical step. Our study also discovers that while each catalytic residue individually contributes to facilitating the catalysis, R36, R123, R156, R167, and D158 are organized in a tightly coordinated interaction network and collectively modulate AdK's conformational transitions. Unlike the existing notion of product release being rate-limiting, our results suggest a mechanistic interconnection between the chemical step and the enzyme's conformational dynamics acting as the bottleneck of the catalytic process. Our results also suggest that the enzyme's active site has evolved to optimize the chemical reaction step while slowing down the overall opening dynamics of the enzyme.

Adenylate Kinase-Catalyzed Reactions of AMP in Pieces: Specificity for Catalysis at the Nucleoside Activator and Dianion Catalytic Sites

The pressure to optimize the enzymatic rate acceleration for adenylate kinase (AK)-catalyzed phosphoryl transfer has led to the evolution of an induced-fit mechanism, where the binding energy from interactions between the protein and substrate adenosyl group is utilized to drive a protein conformational change that activates the enzyme for catalysis. The adenine group of adenosine contributes 11.8 kcal mol-1 to the total ≥14.7 kcal mol-1 adenosine stabilization of the transition state for AK-catalyzed phosphoryl transfer to AMP. The relative third-order rate constants for activation of adenylate kinase, by the C-5 truncated adenosine 1-(β-d-erythrofuranosyl)adenine (EA), for catalysis of phosphoryl transfer from ATP to phosphite dianion (HP, kcat/KHPKAct = 260 M-2 s-1), fluorophosphate (47 M-2 s-1), and phosphate (9.6 M-2 s-1), show that substitution of -F for -H and of -OH for -H at HP results, respectively, in decreases in the reactivity of AK for catalysis of phosphoryl transfer due to polar and steric effects of the -F and -OH substituents. The addition of a 5'-CH2OH to the EA activator results in a 3.0 kcal mol-1 destabilization of the transition state for AK-activated phosphoryl transfer to HP due to a steric effect. This is smaller than the 8.3 kcal mol-1 steric effect of the 5'-CH2OH substituent at OMP on HP-activated OMPDC-catalyzed decarboxylation of 1-(β-d-erythrofuranosyl)orotate. The 2'-OH ribosyl substituent shows significant interactions with the transition states for AK-catalyzed phosphoryl transfer from ATP to AMP and for adenosine-activated AK-catalyzed phosphoryl transfer from ATP to HP.

Role of Repeated Conformational Transitions in Substrate Binding of Adenylate Kinase

The catalytic cycle of the enzyme adenylate kinase involves large conformational motions between open and closed states. A previous single-molecule experiment showed that substrate binding tends to accelerate both the opening and the closing rates and that a single turnover event often involves multiple rounds of conformational switching. In this work, we showed that the repeated conformational transitions of adenylate kinase are essential for the relaxation of incorrectly bound substrates into the catalytically competent conformation by combining all-atom and coarse-grained molecular simulations. In addition, free energy calculations based on all-atom and coarse-grained models demonstrated that the enzyme with incorrectly bound substrates has much a lower free energy barrier for domain opening compared to that with the correct substrate conformation, which may explain the the acceleration of the domain opening rate by substrate binding. The results of this work provide mechanistic understanding to previous experimental observations and shed light onto the interplay between conformational dynamics and enzyme catalysis.

Synergic action of an inserted carbohydrate-binding module in a glycoside hydrolase family 5 endoglucanase

Most known cellulase-associated carbohydrate-binding modules (CBMs) are attached to the N- or C-terminus of the enzyme or are expressed separately and assembled into multi-enzyme complexes (for example to form cellulosomes), rather than being an insertion into the catalytic domain. Here, by solving the crystal structure, it is shown that MtGlu5 from Meiothermus taiwanensis WR-220, a GH5-family endo-β-1,4-glucanase (EC 3.2.1.4), has a bipartite architecture consisting of a Cel5A-like catalytic domain with a (β/α)8 TIM-barrel fold and an inserted CBM29-like noncatalytic domain with a β-jelly-roll fold. Deletion of the CBM significantly reduced the catalytic efficiency of MtGlu5, as determined by isothermal titration calorimetry using inactive mutants of full-length and CBM-deleted MtGlu5 proteins. Conversely, insertion of the CBM from MtGlu5 into TmCel5A from Thermotoga maritima greatly enhanced the substrate affinity of TmCel5A. Bound sugars observed between two tryptophan side chains in the catalytic domains of active full-length and CBM-deleted MtGlu5 suggest an important stacking force. The synergistic action of the catalytic domain and CBM of MtGlu5 in binding to single-chain polysaccharides was visualized by substrate modeling, in which additional surface tryptophan residues were identified in a cross-domain groove. Subsequent site-specific mutagenesis results confirmed the pivotal role of several other tryptophan residues from both domains of MtGlu5 in substrate binding. These findings reveal a way to incorporate a CBM into the catalytic domain of an existing enzyme to make a robust cellulase.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.

Correlating the Local and Global Dynamics of an Enzyme in the Crowded Milieu

Enzymes are dynamic biological macromolecules, with their catalytic function(s) being largely influenced by the changes in local fluctuations of amino acid side chains as well as global structural modulations that the enzyme undergoes. Such local and global motions can be highly affected inside the crowded physiological interior of the cell. Here, we have addressed the role of dynamic structural flexibility in affecting the activation energy barrier of a flexible multidomain enzyme adenylate kinase (AK3L1, UniProtKB: Q9UIJ7). Activation energy profiles of both local (at three different sites along the polypeptide backbone) and global dynamics of the enzyme have been monitored using solvation studies on the subnanosecond time scale and tryptophan quenching studies over the temperature range of 278-323 K, respectively, under crowded conditions (Ficoll 70, Dextran 40, Dextran 70, and PEG 8). This study not only provides the site-specific mapping of dynamics but reveals that the activation energies associated with these local motions undergo a significant decrease in the presence of macromolecular crowders, providing new insights into how crowding affects internal protein dynamics. The crowded scenario also aids in enhancing the coupling between the local and global motions of the enzyme. Moreover, select portions/regions of the enzyme when taken together can well mirror the overall dynamics of the biomolecule, showing possible energy hotspots along the polypeptide backbone.

Mapping Enzyme Landscapes by Time-Resolved Crystallography with Synchrotron and X-Ray Free Electron Laser Light

Directly observing enzyme catalysis in real time at the molecular level has been a long-standing goal of structural enzymology. Time-resolved serial crystallography methods at synchrotron and X-ray free electron laser (XFEL) sources have enabled researchers to follow enzyme catalysis and other nonequilibrium events at ambient conditions with unprecedented time resolution. X-ray crystallography provides detailed information about conformational heterogeneity and protein dynamics, which is enhanced when time-resolved approaches are used. This review outlines the ways in which information about the underlying energy landscape of a protein can be extracted from X-ray crystallographic data, with an emphasis on new developments in XFEL and synchrotron time-resolved crystallography. The emerging view of enzyme catalysis afforded by these techniques can be interpreted as enzymes moving on a time-dependent energy landscape. Some consequences of this view are discussed, including the proposal that irreversible enzymes or enzymes that use covalent catalytic mechanisms may commonly exhibit catalysis-activated motions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Tracking the ATP-binding response in adenylate kinase in real time

The biological function of proteins is critically dependent on dynamics inherent to the native structure. Such structural dynamics obey a predefined order and temporal timing to execute the specific reaction. Determination of the cooperativity of key structural rearrangements requires monitoring protein reactions in real time. In this work, we used time-resolved x-ray solution scattering (TR-XSS) to visualize structural changes in the Escherichia coli adenylate kinase (AdK) enzyme upon laser-induced activation of a protected ATP substrate. A 4.3-ms transient intermediate showed partial closing of both the ATP- and AMP-binding domains, which indicates a cooperative closing mechanism. The ATP-binding domain also showed local unfolding and breaking of an Arg¹³¹-Asp¹⁴⁶ salt bridge. Nuclear magnetic resonance spectroscopy data identified similar unfolding in an Arg¹³¹Ala AdK mutant, which refolded in a closed, substrate-binding conformation. The observed structural dynamics agree with a “cracking mechanism” proposed to underlie global structural transformation, such as allostery, in proteins.

Explore Protein Conformational Space With Variational Autoencoder

Molecular dynamics (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational resources and takes a prohibitive amount of time. In this study, we demonstrated that variational autoencoders (VAEs), a type of deep learning model, can be employed to explore the conformational space of a protein through MD simulations. VAEs are shown to be superior to autoencoders (AEs) through a benchmark study, with low deviation between the training and decoded conformations. Moreover, we show that the learned latent space in the VAE can be used to generate unsampled protein conformations. Additional simulations starting from these generated conformations accelerated the sampling process and explored hidden spaces in the conformational landscape.

Understanding enzyme behavior in a crowded scenario through modulation in activity, conformation and dynamics

Macromolecular crowding, inside the physiological interior, modulates the energy landscape of biological macromolecules in multiple ways. Amongst these, enzymes occupy a special place and hence understanding the function of the same in the crowded interior is of utmost importance. In this study, we have investigated the manner in which the multidomain enzyme, AK3L1 (PDB ID: 1ZD8), an isoform of adenylate kinase, has its features affected in presence of commonly used crowders (PEG 8, Dextran 40, Dextran 70, and Ficoll 70). Michaelis Menten plots reveal that the crowders in general enhance the activity of the enzyme, with the K_m and V_max values showing significant variations. Ficoll 70, induced the maximum activity for AK3L1 at 100 g/L, beyond which the activity reduced. Ensemble FRET studies were performed to provide insights into the relative domain (LID and CORE) displacements in presence of the crowders. Solvation studies reveal that the protein matrix surrounding the probe CPM (7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin) gets restricted in presence of the crowders, with Ficoll 70 providing the maximum rigidity, the same being linked to the decrease in the activity of the enzyme. Through our multipronged approach, we have observed a distinct correlation between domain displacement, enzyme activity and associated dynamics. Thus, keeping in mind the complex nature of enzyme activity and the surrounding bath of dense soup that the biological entity remains immersed in, indeed more such approaches need to be undertaken to have a better grasp of the "enzymes in the crowd".

Genome-Wide Identification and Expression Analysis of Tomato ADK Gene Family during Development and Stress

Adenylate kinase (ADK) is widely distributed in organisms and plays an important role in cellular energy homeostasis. In plants, ADK has important functions in plant growth and development regulation as well as in adaptation to the environment. However, little information is available about the ADK genes in tomato (Solanum lycopersicum), an important economic crop. To investigate the characteristics and functions of ADK genes in tomato, a total of 11 ADK genes were identified and named according to their chromosomal locations. The ADK family in Arabidopsis, tomato, potato, and rice was divided into six groups, and motif analysis revealed that each SlADK protein contained five to eight conserved motifs. A total of 4 to 19 exons were identified in tomato ADK gene family members, and interestingly, most members possessed 4 exons. Several stress response elements were identified in the promoter regions of SlADKs. The 11 SlADKs were randomly distributed on 9 of the 12 tomato chromosomes. Three duplication events were observed between tomato chromosomes, and a high degree of conservation of synteny was demonstrated between tomato and potato. The online TomExpress platform prediction revealed that SlADKs were expressed in various tissues and organs, basically consistent with the data obtained from real-time quantitative PCR (qPCR). The qPCR verification was also performed to determine the expression level of SlADKs and demonstrated that the genes responded to multiple abiotic stresses, such as drought, salt, and cold. Besides, the qPCR results showed that SlADK transcription was responsive to most of the applied hormone treatment. For correlation network analysis under 44 global conditions, the results showed that the number of 17, 3, 4, and 6 coexpressed genes matched with SlADK5, 8, 9, and 11, respectively. For specific gene function analysis, expression of SlADK10 was inhibited using virus-induced gene silencing (VIGS). Compared to wild-type plants, plants with silenced SlADK10 gene had poor drought resistance, indicating SlADK10 regulated drought tolerance of tomato positively. In summary, the information provided in the present study will be helpful to understand the evolutionary relationship and their roles of tomato ADK gene family in further research.

Dynamic Connection between Enzymatic Catalysis and Collective Protein Motions

Enzymes employ a wide range of protein motions to achieve efficient catalysis of chemical reactions. While the role of collective protein motions in substrate binding, product release, and regulation of enzymatic activity is generally understood, their roles in catalytic steps per se remain uncertain. Here, molecular dynamics simulations, enzyme kinetics, X-ray crystallography, and nuclear magnetic resonance spectroscopy are combined to elucidate the catalytic mechanism of adenylate kinase and to delineate the roles of catalytic residues in catalysis and the conformational change in the enzyme. This study reveals that the motions in the active site, which occur on a time scale of picoseconds to nanoseconds, link the catalytic reaction to the slow conformational dynamics of the enzyme by modulating the free energy landscapes of subdomain motions. In particular, substantial conformational rearrangement occurs in the active site following the catalytic reaction. This rearrangement not only affects the reaction barrier but also promotes a more open conformation of the enzyme after the reaction, which then results in an accelerated opening of the enzyme compared to that of the reactant state. The results illustrate a linkage between enzymatic catalysis and collective protein motions, whereby the disparate time scales between the two processes are bridged by a cascade of intermediate-scale motion of catalytic residues modulating the free energy landscapes of the catalytic and conformational change processes.

Identification of novel DNA hypermethylation of the adenylate kinase 5 promoter in colorectal adenocarcinoma

Adenylate kinase 5 (AK5) belongs to the adenylate kinase family that catalyses reversible phosphate transfer between adenine nucleotides, and it is related to various energetic signalling mechanisms. However, the role of AK5 in colorectal cancer (CRC) has not been reported. In this study, AK5 was significantly hypermethylated in CRC compared to adjacent normal tissues (P < 0.0001) and normal tissues (P = 0.0015). Although the difference in mRNA expression was not statistically significant in all of them, the selected 49 cases of CRC tissues with AK5 hypermethylation with the cut off value of 40% showed a significant inverse correlation with mRNA expression (P = 0.0003). DNA methylation of AK5 promoter significantly decreased and AK5 expression recovered by 5-aza-2'-deoxycytidine, DNA methyltransferase inhibitor in CRC cell lines. In addition, AK5 promoter activity significantly decreased due to DNA methyltransferase, and it increased due to 5-aza. Moreover, AK5 regulated the phosphorylated AMPK and mTOR phosphorylation and inhibited the cell migration and cell invasion in CRC cell lines. Furthermore, low AK5 expression is associated with poor differentiation (P = 0.014). These results demonstrate that the AK5 promoter is frequently hypermethylated and induced methylation-mediated gene down-regulation. AK5 expression regulates AMPK/mTOR signalling and may be closely related to metastasis in colorectal adenocarcinoma.

Assessing the Interactions of Statins with Human Adenylate Kinase Isoenzyme 1: Fluorescence and Enzyme Kinetic Studies

Statins are the most effective cholesterol-lowering drugs. They also exert many pleiotropic effects, including anti-cancer and cardio- and neuro-protective. Numerous nano-sized drug delivery systems were developed to enhance the therapeutic potential of statins. Studies on possible interactions between statins and human proteins could provide a deeper insight into the pleiotropic and adverse effects of these drugs. Adenylate kinase (AK) was found to regulate HDL endocytosis, cellular metabolism, cardiovascular function and neurodegeneration. In this work, we investigated interactions between human adenylate kinase isoenzyme 1 (hAK1) and atorvastatin (AVS), fluvastatin (FVS), pravastatin (PVS), rosuvastatin (RVS) and simvastatin (SVS) with fluorescence spectroscopy. The tested statins quenched the intrinsic fluorescence of hAK1 by creating stable hAK1-statin complexes with the binding constants of the order of 10⁴ M⁻¹. The enzyme kinetic studies revealed that statins inhibited hAK1 with significantly different efficiencies, in a noncompetitive manner. Simvastatin inhibited hAK1 with the highest yield comparable to that reported for diadenosine pentaphosphate, the only known hAK1 inhibitor. The determined AK sensitivity to statins differed markedly between short and long type AKs, suggesting an essential role of the LID domain in the AK inhibition. Our studies might open new horizons for the development of new modulators of short type AKs.

Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov State Model

To initiate transcription, the holoenzyme (RNA polymerase [RNAP] in complex with σ factor) loads the promoter DNA via the flexible loading gate created by the clamp and β-lobe, yet their roles in DNA loading have not been characterized. We used a quasi-Markov State Model (qMSM) built from extensive molecular dynamics simulations to elucidate the dynamics of Thermus aquaticus holoenzyme's gate opening. We showed that during gate opening, β-lobe oscillates four orders of magnitude faster than the clamp, whose opening depends on the Switch 2's structure. Myxopyronin, an antibiotic that binds to Switch 2, was shown to undergo a conformational selection mechanism to inhibit clamp opening. Importantly, we reveal a critical but undiscovered role of β-lobe, whose opening is sufficient for DNA loading even when the clamp is partially closed. These findings open the opportunity for the development of antibiotics targeting β-lobe of RNAP. Finally, we have shown that our qMSMs, which encode non-Markovian dynamics based on the generalized master equation formalism, hold great potential to be widely applied to study biomolecular dynamics.

Inhibition of Nonfunctional Ras

Intuitively, functional states should be targeted; not nonfunctional ones. So why could drugging the inactive K-Ras4BG12Cwork-but drugging the inactive kinase will likely not? The reason is the distinct oncogenic mechanisms. Kinase driver mutations work by stabilizing the active state and/or destabilizing the inactive state. Either way, oncogenic kinases are mostly in the active state. Ras driver mutations work by quelling its deactivation mechanisms, GTP hydrolysis, and nucleotide exchange. Covalent inhibitors that bind to the inactive GDP-bound K-Ras4BG12C conformation can thus work. By contrast, in kinases, allosteric inhibitors work by altering the active-site conformation to favor orthosteric drugs. From the translational standpoint this distinction is vital: it expedites effective pharmaceutical development and extends the drug classification based on the mechanism of action. Collectively, here we postulate that drug action relates to blocking the mechanism of activation, not to whether the protein is in the active or inactive state.

Increasing the Sampling Efficiency of Protein Conformational Change by Combining a Modified Replica Exchange Molecular Dynamics and Normal Mode Analysis

Understanding conformational change at an atomic level is significant when determining a protein functional mechanism. Replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method to explore protein conformational space. However, REMD with an explicit solvent model requires huge computational resources, immensely limiting its application. In this study, a variation of parallel tempering metadynamics (PTMetaD) with the omission of solvent-solvent interactions in exchange attempts and the use of low-frequency modes calculated by normal-mode analysis (NMA) as collective variables (CVs), namely ossPTMetaD, is proposed with the aim to accelerate MD simulations simultaneously in temperature and geometrical spaces. For testing the performance of ossPTMetaD, five protein systems with diverse biological functions and motion patterns were selected, including large-scale domain motion (AdK), flap movement (HIV-1 protease and BACE1), and DFG-motif flip in kinases (p38α and c-Abl). The simulation results showed that ossPTMetaD requires much fewer numbers of replicas than temperature REMD (T-REMD) with a reduction of ∼70% to achieve a similar exchange ratio. Although it does not obey the detailed balance condition, ossPTMetaD provides consistent results with T-REMD and experimental data. The high accessibility of the large conformational change of protein systems by ossPTMetaD, especially in simulating the very challenging DFG-motif flip of protein kinases, demonstrated its high efficiency and robustness in the characterization of the large-scale protein conformational change pathway and associated free energy profile.

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

How fast are the motions of tertiary-structure elements in proteins?

Protein motions occur on multiple time and distance scales. Large-scale motions of protein tertiary-structure elements, i.e., domains, are particularly intriguing as they are essential for the catalytic activity of many enzymes and for the functional cycles of protein machines and motors. Theoretical estimates suggest that domain motions should be very fast, occurring on the nanosecond or microsecond time scales. Indeed, free-energy barriers for domain motions are likely to involve salt bridges, which can break in microseconds. Experimental methods that can directly probe domain motions on fast time scales have appeared only in recent years. This Perspective discusses briefly some of these techniques, including nuclear magnetic resonance and single-molecule fluorescence spectroscopies. We introduce a few recent studies that demonstrate ultrafast domain motions and discuss their potential roles. Particularly surprising is the observation of tertiary-structure element dynamics that are much faster than the functional cycles in some protein machines. These swift motions can be rationalized on a case-by-case basis. For example, fast domain closure in multi-substrate enzymes may be utilized to optimize relative substrate orientation. Whether a large mismatch in time scales of conformational dynamics vs functional cycles is a general design principle in proteins remains to be determined.

The crystal structures of Thermus thermophilus CMP kinase complexed with a phosphoryl group acceptor and donor

Nucleoside monophosphate kinases play crucial roles in biosynthesis and regeneration of nucleotides. These are bi-substrate enzymes that catalyze reversible transfers of a phosphoryl group between ATP and nucleoside monophosphate. These enzymes are comprised of the CORE domain, the NMP-binding domain, and the LID domain. Large conformational rearrangement of the three domains occurs during the catalytic cycle. Although many structures of CMP kinase have been determined, only limited structural information has been available on the conformational changes along the reaction pathway. We determined five crystal structures of CMP kinase of Thermus thermophilus HB8 in ligand-free form and the CMP "open", CMP "closed", ADP-CDP-Gd3+-, and CDP-bound forms at resolutions of 1.7, 2.2, 1.5, 1.6, and 1.7 Å, respectively. The ligand-free form was in an open conformation, whereas the structures of the CMP "closed", ADP-CDP-Gd3+-, and CDP-bound forms were in a closed conformation, in which the shift of the NMP-binding domain and LID domain caused closure of the substrate-binding cleft. Interestingly, the CMP "open" form was in an open conformation even with CMP bound, implying intrinsic conformational fluctuation. The structure of the ADP-CDP complex is the first structure of CMP kinase with a phosphoryl group donor and an acceptor. Upon simultaneous binding of ADP and CDP, the side chains of several residues in the LID domain moved toward the nucleotides without global open-closed conformational changes compared to those in the CMP "closed" and CDP complexes. These global and local conformational changes may be crucial for the substrate recognition and catalysis. The terminal phosphate groups of ADP and CDP had similar geometry to those of two ADP in AMP kinase, suggesting common catalytic mechanisms to other nucleoside monophosphate kinases. Our findings are expected to contribute to detailed understanding of the reaction mechanism of CMP kinase.

Perturb-Scan-Pull: A Novel Method Facilitating Conformational Transitions in Proteins

Conformational transitions in proteins facilitate precise physiological functions. Therefore, it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and dynamical properties of proteins is notoriously challenging due to the complexity of the underlying potential energy surfaces (PES). We have previously developed the perturbation-response scanning (PRS) method to identify key residues that participate in the communication network responsible for specific conformational transitions. PRS is based on a residue-by-residue scan of the protein to determine the subset of residues/forces which provide the closest conformational change leading to a target conformational state, inasmuch as linear response theory applies to these motions. Here, we develop a novel method to further evaluate if conformational transitions may be triggered on the PES. We aim to study functionally relevant conformational transitions in proteins by using results obtained from PRS and feeding them as inputs to steered molecular dynamics simulations. The success and the transferability of the method are evaluated on three protein systems having different complexities of motion on the PES: calmodulin, adenylate kinase, and bacterial ferric binding protein. We find that the method captures the target conformation, while providing key residues and the optimum paths with relatively low free energy profiles.

A Two-Ended Data-Driven Accelerated Sampling Method for Exploring the Transition Pathways between Two Known States of Protein

Conformational transitions of protein between different states are often associated with their biological functions. These dynamic processes, however, are usually not easy to be well characterized by experimental measurements, mainly because of inadequate temporal and spatial resolution. Meantime, sampling of configuration space with molecular dynamics (MD) simulations is still a challenge. Here we proposed a robust two-ended data-driven accelerated (teDA2) conformational sampling method, which drives the structural change in an adaptively updated feature space without introducing a bias potential. teDA2 was applied to explore adenylate kinase (ADK), a model with well characterized "open" and "closed" states. A single conformational transition event of ADK could be achieved within only a few or tens of nanoseconds sampled with teDA2. By analyzing hundreds of transition events, we reproduced different mechanisms and the associated pathways for domain motion of ADK reported in the literature. The multiroute characteristic of ADK was confirmed by the fact that some metastable states identified with teDA2 resemble available crystal structures determined at different conditions. This feature was further validated with Markov state modeling with independent MD simulations. Therefore, our work provides strong evidence for the conformational plasticity of protein, which is mainly due to the inherent degree of flexibility. As a reliable and efficient enhanced sampling protocol, teDA2 could be used to study the dynamics between functional states of various biomolecular machines.

Difference contact maps: From what to why in the analysis of the conformational flexibility of proteins

Protein structures, usually visualized in various highly idealized forms focusing on the three-dimensional arrangements of secondary structure elements, can also be described as lists of interacting residues or atoms and visualized as two-dimensional distance or contact maps. We show that contact maps provide an ideal tool to describe and analyze differences between structures of proteins in different conformations. Expanding functionality of the PDBFlex server and database developed previously in our group, we describe how analysis of difference contact maps (DCMs) can be used to identify critical interactions stabilizing alternative protein conformations, recognize residues and positions controlling protein functions and build hypotheses as to molecular mechanisms of disease mutations.

Exploring Conformational Change of Adenylate Kinase by Replica Exchange Molecular Dynamic Simulation

Replica exchange molecular dynamics (REMD) simulation is a popular enhanced sampling method that is widely used for exploring the atomic mechanism of protein conformational change. However, the requirement of huge computational resources for REMD, especially with the explicit solvent model, largely limits its application. In this study, the availability and efficiency of a variant of velocity-scaling REMD (vsREMD) was assessed with adenylate kinase as an example. Although vsREMD achieved results consistent with those from conventional REMD and experimental studies, the number of replicas required for vsREMD (30) was much less than that for conventional REMD (80) to achieve a similar acceptance rate (∼0.2), demonstrating high efficiency of vsREMD to characterize the protein conformational change and associated free-energy profile. Thus, vsREMD is a highly efficient approach for studying the large-scale conformational change of protein systems.

Computational Studies of Catalytic Loop Dynamics in Yersinia Protein Tyrosine Phosphatase Using Pathway Optimization Methods

Yersinia Protein Tyrosine Phosphatase (YopH) is the most efficient enzyme among all known PTPases and relies on its catalytic loop movements for substrate binding and catalysis. Fluorescence, NMR, and UV resonance Raman (UVRR) techniques have been used to study the thermodynamic and dynamic properties of the loop motions. In this study, a computational approach based on the pathway refinement methods nudged elastic band (NEB) and harmonic Fourier beads (HFB) has been developed to provide structural interpretations for the experimentally observed kinetic processes. In this approach, the minimum potential energy pathways for the loop open/closure conformational changes were determined by NEB using a one-dimensional global coordinate. Two dimensional data analyses of the NEB results were performed as an efficient method to qualitatively evaluate the energetics of transitions along several specific physical coordinates. The free energy barriers for these transitions were then determined more precisely using the HFB method. Kinetic parameters were estimated from the energy barriers using transition state theory and compared against experimentally determined kinetic parameters. When the calculated energy barriers are calibrated by a simple "scaling factor", as have been done in our previous vibrational frequency calculations to explain the ligand frequency shift upon its binding to protein, it is possible to make structural interpretations of several observed enzyme dynamic rates. For example, the nanosecond kinetics observed by fluorescence anisotropy may be assigned to the translational motion of the catalytic loop and microsecond kinetics observed in fluorescence T-jump can be assigned to the loop backbone dihedral angle flipping. Furthermore, we can predict that a Trp354 conformational conversion associated with the loop movements would occur on the tens of nanoseconds time scale, to be verified by future UVRR T-jump studies.

Probing the Transition State in Enzyme Catalysis by High-Pressure NMR Dynamics

Protein conformational changes are frequently essential for enzyme catalysis, and in several cases, shown to be the limiting factor for overall catalytic speed. However, a structural understanding of corresponding transition states, needed to rationalize the kinetics, remains obscure due to their fleeting nature. Here, we determine the transition-state ensemble of the rate-limiting conformational transition in the enzyme adenylate kinase, by a synergistic approach between experimental high-pressure NMR relaxation during catalysis and molecular dynamics simulations. By comparing homologous kinases evolved under ambient or high pressure in the deep-sea, we detail transition state ensembles that differ in solvation as directly measured by the pressure dependence of catalysis. Capturing transition-state ensembles begins to complete the catalytic energy landscape that is generally characterized by structures of all intermediates and frequencies of transitions among them.

Determining selection free energetics from nucleotide pre-insertion to insertion in viral T7 RNA polymerase transcription fidelity control

An elongation cycle of a transcribing RNA polymerase (RNAP) usually consists of multiple kinetics steps, so there exist multiple kinetic checkpoints where non-cognate nucleotides can be selected against. We conducted comprehensive free energy calculations on various nucleotide insertions for viral T7 RNAP employing all-atom molecular dynamics simulations. By comparing insertion free energy profiles between the non-cognate nucleotide species (rGTP and dATP) and a cognate one (rATP), we obtained selection free energetics from the nucleotide pre-insertion to the insertion checkpoints, and further inferred the selection energetics down to the catalytic stage. We find that the insertion of base mismatch rGTP proceeds mainly through an off-path along which both pre-insertion screening and insertion inhibition play significant roles. In comparison, the selection against dATP is found to go through an off-path pre-insertion screening along with an on-path insertion inhibition. Interestingly, we notice that two magnesium ions switch roles of leave and stay during the dATP on-path insertion. Finally, we infer that substantial selection energetic is still required to catalytically inhibit the mismatched rGTP to achieve an elongation error rate ∼10-4 or lower; while no catalytic selection seems to be further needed against dATP to obtain an error rate ∼10-2.

Nature's Shortcut to Protein Folding

This Feature Article presents a view of the protein folding transition based on the hypothesis that Nature has built features within the sequences that enable a Shortcut to efficient folding. Nature's Shortcut is proposed to be the early establishment of a set of nonlocal weak contacts, constituting protein loops that significantly constrain regions of the collapsed disordered protein into a native-like low-resolution fluctuating topology of major sections of the backbone. Nature's establishment of this scaffold of nonlocal contacts is claimed to bypass what would otherwise be a nearly hopeless unaided search for the final three-dimensional structure in proteins longer than ∼100 amino acids. To support this main contention of the Feature Article, the loop hypothesis (LH) description of early folding events is experimentally tested with time-resolved Förster resonance energy transfer techniques for adenylate kinase, and the data are shown to be consistent with theoretical predictions from the sequential collapse model (SCM). The experimentally based LH and the theoretically founded SCM are argued to provide a unified picture of the role of nonlocal contacts as constituting Nature's Shortcut to protein folding. Importantly, the SCM is shown to reliably predict key nonlocal contacts utilizing only primary sequence information. This view on Nature's Shortcut is open to the protein community for further detailed assessment, including its practical consequences, by suitable application of advanced experimental and computational techniques.

Electrostatic interactions determine entrance/release order of substrates in the catalytic cycle of adenylate kinase

Adenylate kinase is a monomeric phosphotransferase with important biological function in regulating concentration of adenosine triphosphate (ATP) in cells, by transferring the terminal phosphate group from ATP to adenosine monophosphate (AMP) and forming two adenosine diphosphate (ADP) molecules. During this reaction, the kinase may undergo a large conformational transition, forming different states with its substrates. Although many structures of the protein are available, atomic details of the whole process remain unclear. In this article, we use both conventional molecular dynamics (MD) simulation and an enhanced sampling technique called parallel cascade selection MD simulation to explore different conformational states of the Escherichia coli adenylate kinase. Based on the simulation results, we propose a possible entrance/release order of substrates during the catalytic cycle. The substrate-free protein prefers an open conformation, but changes to a closed state once ATP·Mg enters into its binding pocket first and then AMP does. After the reaction of ATP transferring the terminal phosphate group to AMP, ADP·Mg and ADP are released sequentially, and finally the whole catalyze cycle is completed. Detailed contact and distance analysis reveals that the entrance/release order of substrates may be largely controlled by electrostatic interactions between the protein and the substrates.

Why the Energy Landscape of Barnase Is Hierarchical

We have used NMR and computational methods to characterize the dynamics of the ribonuclease barnase over a wide range of timescales in free and inhibitor-bound states. Using temperature- and denaturant-dependent measurements of chemical shift, we show that barnase undergoes frequent and highly populated hinge bending. Using relaxation dispersion, we characterize a slower and less populated motion with a rate of 750 ± 200 s⁻¹, involving residues around the lip of the active site, which occurs in both free and bound states and therefore suggests conformational selection. Normal mode calculations characterize correlated hinge bending motions on a very rapid timescale. These three measurements are combined with previous measurements and molecular dynamics calculations on barnase to characterize its dynamic landscape on timescales from picoseconds to milliseconds and length scales from 0.1 to 2.5 nm. We show that barnase has two different large-scale fluctuations: one on a timescale of 10⁻⁹−10⁻⁶ s that has no free energy barrier and is a hinge bending that is determined by the architecture of the protein; and one on a timescale of milliseconds (i.e., 750 s⁻¹) that has a significant free energy barrier and starts from a partially hinge-bent conformation. These two motions can be described as hierarchical, in that the more highly populated faster motion provides a platform for the slower (less probable) motion. The implications are discussed. The use of temperature and denaturant is suggested as a simple and general way to characterize motions on the intermediate ns-μs timescale.

Prediction of perturbed proton transfer networks

The transfer of protons through proton translocating channels is a complex process, for which direct samplings of different protonation states and side chain conformations in a transition network calculation provide an efficient, bias-free description. In principle, a new transition network calculation is required for every unsampled change in the system of interest, e.g. an unsampled protonation state change, which is associated with significant computational costs. Transition networks void of or including an unsampled change are termed unperturbed or perturbed, respectively. Here, we present a prediction method, which is based on an extensive coarse-graining of the underlying transition networks to speed up the calculations. It uses the minimum spanning tree and a corresponding sensitivity analysis of an unperturbed transition network as initial guess and refinement parameter for the determination of an unknown, perturbed transition network. Thereby, the minimum spanning tree defines a sub-network connecting all nodes without cycles and minimal edge weight sum, while the sensitivity analysis analyzes the stability of the minimum spanning tree towards individual edge weight reductions. Using the prediction method, we are able to reduce the calculation costs in a model system by up to 80%, while important network properties are maintained in most predictions.

t-Distributed Stochastic Neighbor Embedding Method with the Least Information Loss for Macromolecular Simulations

Dimensionality reduction methods are usually applied on molecular dynamics simulations of macromolecules for analysis and visualization purposes. It is normally desired that suitable dimensionality reduction methods could clearly distinguish functionally important states with different conformations for the systems of interest. However, common dimensionality reduction methods for macromolecules simulations, including predefined order parameters and collective variables (CVs), principal component analysis (PCA), and time-structure based independent component analysis (t-ICA), only have limited success due to significant key structural information loss. Here, we introduced the t-distributed stochastic neighbor embedding (t-SNE) method as a dimensionality reduction method with minimum structural information loss widely used in bioinformatics for analyses of macromolecules, especially biomacromolecules simulations. It is demonstrated that both one-dimensional (1D) and two-dimensional (2D) models of the t-SNE method are superior to distinguish important functional states of a model allosteric protein system for free energy and mechanistic analysis. Projections of the model protein simulations onto 1D and 2D t-SNE surfaces provide both clear visual cues and quantitative information, which is not readily available using other methods, regarding the transition mechanism between two important functional states of this protein.

Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling

Clinically used RAF inhibitors are ineffective in RAS mutant tumors because they enhance homo- and heterodimerization of RAF kinases, leading to paradoxical activation of ERK signaling. Overcoming enhanced RAF dimerization and the resulting resistance is a challenge for drug design. Combining multiple inhibitors could be more effective, but it is unclear how the best combinations can be chosen. We built a next-generation mechanistic dynamic model to analyze combinations of structurally different RAF inhibitors, which can efficiently suppress MEK/ERK signaling. This rule-based model of the RAS/ERK pathway integrates thermodynamics and kinetics of drug-protein interactions, structural elements, posttranslational modifications, and cell mutational status as model rules to predict RAF inhibitor combinations for inhibiting ERK activity in oncogenic RAS and/or BRAFV600E backgrounds. Predicted synergistic inhibition of ERK signaling was corroborated by experiments in mutant NRAS, HRAS, and BRAFV600E cells, and inhibition of oncogenic RAS signaling was associated with reduced cell proliferation and colony formation.

Interaction between adenylate kinase 3 and glyceraldehyde-3-phosphate dehydrogenase from Chlamydomonas reinhardtii

The critical and ubiquitous enzyme adenylate kinase (ADK) catalyzes the nucleotide phosphoryl exchange reaction: 2ADP ↔ ATP + AMP. The ADK3 in the chloroplasts of the green alga Chlamydomonas reinhardtii, bears an unusual C-terminal extension that is similar to the C-terminal end of the intrinsically disordered protein CP12. In this study, we report that this enzyme, when oxidized but not when reduced, is able to interact with the chloroplast glyceraldehyde-3-phosphate dehydrogenase (GAPDH) forming a stable complex as shown by native electrophoresis and mass spectrometry. In this bienzyme complex, the activity of ADK3 is unchanged while the NADPH-dependent activity of GAPDH is significantly inhibited. Moreover ADK3, like CP12, can protect GAPDH against thermal inactivation and aggregation. The ADK3-GAPDH bienzyme complex is unable to recruit phosphoribulokinase (PRK), in contrast with the ternary complex formed between GAPDH-CP12 and PRK. The interaction between ADK3 and GAPDH might be a mechanism to regulate the crucial ATP: NADPH ratio within chloroplasts to optimize the Calvin-Benson cycle during rapid fluctuation in environmental resources.

ENZYMES

Adenylate kinase (EC 2.7.4.3), glyceraldehyde-3-phosphate dehydrogenase (GAPDH, EC 1.2.1.13), phosphoribulokinase (PRK, EC 2.7.1.19).

Green function of correlated genes in a minimal mechanical model of protein evolution

The function of proteins arises from cooperative interactions and rearrangements of their amino acids, which exhibit large-scale dynamical modes. Long-range correlations have also been revealed in protein sequences, and this has motivated the search for physical links between the observed genetic and dynamic cooperativity. We outline here a simplified theory of protein, which relates sequence correlations to physical interactions and to the emergence of mechanical function. Our protein is modeled as a strongly coupled amino acid network with interactions and motions that are captured by the mechanical propagator, the Green function. The propagator describes how the gene determines the connectivity of the amino acids and thereby, the transmission of forces. Mutations introduce localized perturbations to the propagator that scatter the force field. The emergence of function is manifested by a topological transition when a band of such perturbations divides the protein into subdomains. We find that epistasis-the interaction among mutations in the gene-is related to the nonlinearity of the Green function, which can be interpreted as a sum over multiple scattering paths. We apply this mechanical framework to simulations of protein evolution and observe long-range epistasis, which facilitates collective functional modes.