Exploring the Dynamic Functional Landscape of Adenylate Kinase Modulated by Substrates

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.

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.

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.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

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.

Protein conformational transitions explored by a morphing approach based on normal mode analysis in internal coordinates

Large-scale conformational changes are essential for proteins to function properly. Given that these transition events rarely occur, however, it is challenging to comprehend their underlying mechanisms through experimental and theoretical approaches. In this study, we propose a new computational methodology called internal coordinate normal mode-guided elastic network interpolation (ICONGENI) to predict conformational transition pathways in proteins. Its basic approach is to sample intermediate conformations by interpolating the interatomic distance between two end-point conformations with the degrees of freedom constrained by the low-frequency dynamics afforded by normal mode analysis in internal coordinates. For validation of ICONGENI, it is applied to proteins that undergo open-closed transitions, and the simulation results (i.e., simulated transition pathways) are compared with those of another technique, to demonstrate that ICONGENI can explore highly reliable pathways in terms of thermal and chemical stability. Furthermore, we generate an ensemble of transition pathways through ICONGENI and investigate the possibility of using this method to reveal the transition mechanisms even when there are unknown metastable states on rough energy landscapes.

Deciphering the molecular mechanism of the cancer formation by chromosome structural dynamics

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness.

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.

Micro-Aqueous Organic System: A Neglected Model in Computational Lipase Design?

Water content is an important factor in lipase-catalyzed reactions in organic media but is frequently ignored in the study of lipases by molecular dynamics (MD) simulation. In this study, Candida antarctica lipase B, Candida rugosa lipase and Rhizopus chinensis lipase were used as research models to explore the mechanisms of lipase in micro-aqueous organic solvent (MAOS) media. MD simulations indicated that lipases in MAOS systems showed unique conformations distinguished from those seen in non-aqueous organic solvent systems. The position of water molecules aggregated on the protein surface in MAOS media is the major determinant of the unique conformations of lipases and particularly impacts the distribution of hydrophilic and hydrophobic amino acids on the lipase surface. Additionally, two maxima were observed in the water-lipase radial distribution function in MAOS systems, implying the formation of two water shells around lipase in these systems. The energy landscapes of lipases along solvent accessible areas of catalytic residues and the minimum energy path indicated the dynamic open states of lipases in MAOS systems differ from those in other solvent environments. This study confirmed the necessity of considering the influence of the microenvironment on MD simulations of lipase-catalyzed reactions in organic media.

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.

Moving beyond static snapshots: Protein dynamics and the Protein Data Bank

Proteins are the molecular machines of living systems. Their dynamics are an intrinsic part of their evolutionary selection in carrying out their biological functions. Although the dynamics are more difficult to observe than a static, average structure, we are beginning to observe these dynamics and form sound mechanistic connections between structure, dynamics, and function. This progress is highlighted in case studies from myoglobin and adenylate kinase to the ribosome and molecular motors where these molecules are being probed with a multitude of techniques across many timescales. New approaches to time-resolved crystallography are allowing simple “movies” to be taken of proteins in action, and new methods of mapping the variations in cryo-electron microscopy are emerging to reveal a more complete description of life’s machines. The results of these new methods are aided in their dissemination by continual improvements in curation and distribution by the Protein Data Bank and their partners around the world.

Thermodynamic and sequential characteristics of phase separation and droplet formation for an intrinsically disordered region/protein ensemble

Liquid–liquid phase separation (LLPS) of some IDPs/IDRs can lead to the formation of the membraneless organelles in vitro and in vivo, which are essential for many biological processes in the cell. Here we select three different IDR segments of chaperon Swc5 and develop a polymeric slab model at the residue-level. By performing the molecular dynamics simulations, LLPS can be observed at low temperatures even without charge interactions and disappear at high temperatures. Both the sequence length and the charge pattern of the Swc5 segments can influence the critical temperature of LLPS. The results suggest that the effects of the electrostatic interactions on the LLPS behaviors can change significantly with the ratios and distributions of the charged residues, especially the sequence charge decoration (SCD) values. In addition, three different forms of swc conformation can be distinguished on the phase diagram, which is different from the conventional behavior of the free IDP/IDR. Both the packed form (the condensed-phase) and the dispersed form (the dilute-phase) of swc chains are found to be coexisted when LLPS occurs. They change to the fully-spread form at high temperatures. These findings will be helpful for the investigation of the IDP/IDR ensemble behaviors as well as the fundamental mechanism of the LLPS process in bio-systems.

The membraneless organelles caused by liquid–liquid phase separation (LLPS) of IDPs/IDRs are involved in a wide range of biological functions such as RNA processing, ribosome biogenesis, and sequestration of mRNA, proteins, and compacted chromatin. In this study, we focus on the histone H2A-H2B binding partner, Swc5 and investigate the effects of the temperature, sequence length and number of charged residues on the LLPS behaviors. Moreover, we proposed three forms of swc conformation in ensemble according to the phase diagram. These characteristics of conformational changes (from LLPS to no LLPS, from condensed-phase to dilute-phase) are observed in the swc chains with different sequence length and charge pattern, which may be the general property for the IDP/IDR ensembles.

Influence of sequence length and charged residues on Swc5 binding with histone H2A-H2B

SWR is a member of chromatin remodeler family and participates the replacement of histone H2A with H2A.Z. One of the SWR subunits, Swc5, has an intrinsically disordered region and binds to H2A-H2B dimer. Though the binding structure of Swc5 and H2A-H2B has been resolved recently, it is still challenging to investigate the binding mechanism as well as the role of the charge interactions between Swc5 and H2A-H2B. Here we developed a coarse-grained structure-based model and performed molecular dynamics simulations to investigate the binding processes of two Swc5 regions with different lengths (swc5-a and swc5-b) to H2A-H2B. The simulation results suggest a different role of electrostatic interactions between swc5-a/swc5-b and H2A-H2B on binding. The electrostatic interactions between swc5-a/swc5-b and H2A-H2B can not only accelerate the initial capture step of binding, but can also trap the swc5-a/swc5-b at the wrong binding site on H2A. Besides, the conserved DEF/Y-2 motif of Swc5 is important for the binding affinity and the recognition with H2A-H2B at the initial step. Both swc5-a and swc5-b undergo a structural shift before reaching the final bound state. This theoretical study provides important details and the underlying physical mechanisms of the binding processes of swc5-a/swc5-b and H2A-H2B.

Double-Well Ultra-Coarse-Grained Model to Describe Protein Conformational Transitions

The double-well model is usually used to describe the conformational transition between two states of a protein. Since conformational changes usually occur within a relatively large time scale, coarse-grained models are often used to accelerate the dynamic process due to their inexpensive computational cost. In this work, we develop a double-well ultra-coarse-grained (DW-UCG) model to describe the conformational transitions of the adenylate kinase, glutamine-binding protein, and lactoferrin. The coarse-grained simulation results show that the DW-UCG model of adenylate kinase captures the crucial intermediate states in the LID-closing and NMP-closing pathways, reflecting the key secondary structural changes in the conformational transition. A comparison of the different DW-UCG models of adenylate kinase indicates that an appropriate choice of bead resolution could generate the free energy landscape that is comparable to that from the residue-based model. The coarse-grained simulations for the glutamine-binding protein and lactoferrin also demonstrate that the DW-UCG model is valid in reproducing the correct two-state behavior for their functional study, which indicates the potential application of the DW-UCG model in investigating the mechanism of conformational changes of large proteins.

Conformational state switching and pathways of chromosome dynamics in cell cycle

The cell cycle is a process and function of a cell with different phases essential for cell growth, proliferation, and replication. It depends on the structure and dynamics of the underlying DNA molecule, which underpins the genome function. A microscopic structural-level understanding of how a genome or its functional module chromosome performs the cell cycle in terms of large-scale conformational transformation between different phases, such as the interphase and the mitotic phase, is still challenging. Here, we develop a non-equilibrium, excitation-relaxation energy landscape-switching model to quantify the underlying chromosome conformational transitions through (de-)condensation for a complete microscopic understanding of the cell cycle. We show that the chromosome conformational transition mechanism from the interphase to the mitotic phase follows a two-stage scenario, in good agreement with the experiments. In contrast, the mitotic exit pathways show the existence of an over-expanded chromosome that recapitulates the chromosome in the experimentally identified intermediate state at the telophase. We find the conformational pathways are heterogeneous and irreversible as a result of the non-equilibrium dynamics of the cell cycle from both structural and kinetic perspectives. We suggest that the irreversibility is mainly due to the distinct participation of the ATP-dependent structural maintenance of chromosomal protein complexes during the cell cycle. Our findings provide crucial insights into the microscopic molecular structural and dynamical physical mechanism for the cell cycle beyond the previous more macroscopic descriptions. Our non-equilibrium landscape framework is general and applicable to study diverse non-equilibrium physical and biological processes such as active matter, differentiation/development, and cancer.

Role of substrate-product frustration on enzyme functional dynamics

Natural enzymes often have enormous catalytic power developed by evolution. Revealing the underlying physical strategy used by enzymes to achieve high catalysis efficiency is one of the central focuses in the field of biological physics. Our recent work demonstrated that multisubstrate enzymes can utilize steric frustration encountered in the substrate-product cobound complex to overcome the bottleneck of the enzymatic cycle [W. Li et al., Phys. Rev. Lett. 122, 238102 (2019)10.1103/PhysRevLett.122.238102]. However, the key atomic-level interactions by which the steric frustration contributes to the enzymatic cycle remain elusive. In this work we study the microscopic mechanism for the role of the substrate-product frustration on the key physical steps in the enzymatic cycle of adenylate kinase (AdK), a multisubstrate enzyme catalyzing the reversible phosphoryl transfer reaction ATP+AMP⇋ADP+ADP. By using atomistic molecular dynamics simulations with enhanced sampling, we showed that the competitive interactions from the phosphate groups of the substrate ATP and product ADP in the ATP-ADP cobound complex of the AdK lead to local frustration in the binding pockets. Such local frustration disrupts the hydrogen bond network around the binding pockets, which causes lowered barrier height for the opening of the enzyme conformations and expedited release of the bottleneck product ADP. Our results directly demonstrated from the atomistic level that the local frustration in the active sites of the enzyme can be utilized to facilitate the key physical steps of the enzymatic cycle, providing numerical evidence to the predictions of the previous theoretical work.

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.

Charge Interactions Modulate the Encounter Complex Ensemble of Two Differently Charged Disordered Protein Partners of KIX

Disordered proteins play important roles in cell signaling and are frequently involved in protein-protein interactions. They also have a larger proportion of charged and polar residues than their folded counterparts. Here, we developed a structure-based model and applied molecular dynamics simulations to examine the presence and importance of electrostatic interactions in the binding processes of two differently charged intrinsically disordered ligands of the KIX domain of CBP. We observed non-native opposite-charged contacts in the encounter complexes for both ligands with KIX, and this may be a general feature of coupled folding and binding reactions. The ensemble of successful encounter complexes is a diverse set of structures, and in the case of the highly charged ligand, this ensemble was found to be malleable with respect to ionic strength. There are only minor differences between encounter complex ensembles for successful and unsuccessful collisions with no key interactions that appear to make the process far more productive. The energy landscape at this early stage in the process does not appear highly funneled. Strikingly we observed many native interactions that appear to reduce chances of an encounter complex being productive. Instead it appears that collectively non-native electrostatic interactions in the encounter complex increase the likelihood of productivity by holding the proteins together long enough for folding to take place. This mechanism is more effective for the more highly charged ligand.

Quantification of the Underlying Mechanisms and Relationships Among Cancer, Metastasis, and Differentiation and Development

Recurrence and metastasis have been regarded as two of the greatest obstacles to cancer therapy. Cancer stem cells (CSCs) contribute to cancer development, with the distinctive features of recurrence and resistance to popular treatments such as drugs and chemotherapy. In addition, recent discoveries suggest that the epithelial mesenchymal transition (EMT) is an essential process in normal embryogenesis and tissue repair, as well as being a required step in cancer metastasis. Although there are many indications of the connections between metastasis and stem cells, these have often been studied separately or at most bi-laterally, not in an integrated way. In this study, we aimed to explore the global mechanisms and interrelationships among cancer, development, and metastasis, which are currently poorly understood. First, we constructed a core gene regulatory network containing specific genes and microRNAs of CSCs, EMT, and cancer. We uncovered seven distinct states emerging from the underlying landscape, denoted normal, premalignant, cancer, stem cell, CSC, lesion, and hyperplasia. Given the biological definition of each state, we also discuss the metastasis ability of each state. We show how and which types of cells can be transformed to a cancer state, and the connections among cancer, CSCs, and EMT. The barrier height and flux of the kinetic paths are explored to quantify how and which cells switch stochastically between the states. Our landscape model provides a quantitative approach to reveal the global mechanisms of cancer, development, and metastasis.

Multiscale landscape of molecular mechanism of SIRT1 activation by STACs

Sirtuins are a family of highly conserved NAD-dependent deacetylase that are involved in multiple biological processes in both prokaryotes and eukaryotes. Many sirtuin-activating compounds (STACs) have been reported for SIRT1, which is the best-characterized sirtuin. However, the molecular mechanism of SIRT1 activation by STACs remains controversial. Here, we developed a multiscale simulation model to explore this mechanism. By quantifying the free energy landscape for the closed conformation of a SIRT1-FdL peptide-resveratrol complex, we found a positive correlation between the barrier height of the active free energy basin and the experimentally determined fluctuations in the rate of SIRT1 deacetylation by resveratrol. In addition, by monitoring dynamics, we found that the open conformation of a SIRT1-p53-STAC-1 complex had a faster rate of conformational change than the closed structure. We also determined the structural properties of each thermodynamic or dynamic state and found that two potential activating factors, the stability of FdL peptide (the p53 peptide substrate including an AMC fluorophore group) binding and the stability of the SIRT1 conformation, were weakly correlated under certain conditions. These results address the controversial question of whether the AMC fluorophore group and native hydrophobic residues have similar roles in the SIRT1 activation process. Finally, we captured the global landscape of the transition, including less stable and more stable states, and proposed a global physical landscape for the mechanism of SIRT1 activation by STACs.

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.

Overcoming the Bottleneck of the Enzymatic Cycle by Steric Frustration

The enormous catalytic power of natural enzymes relies on the ability to overcome the bottleneck event in the enzymatic cycle, yet the underlying physical mechanisms are not fully understood. Here, by performing molecular simulations of the whole enzymatic cycle for a model multisubstrate enzyme with a dynamic energy landscape model, we show that multisubstrate enzymes can utilize steric frustration to facilitate the rate-limiting product-release step. During the enzymatic cycles, the bottleneck product is actively squeezed out by the binding of a new substrate at the neighboring site through the population of a substrate-product cobound complex, in which the binding pockets are frustrated due to steric incompatibility. Such steric frustration thereby enables an active mechanism of product release driven by substrate-binding energy, facilitating the enzymatic cycle.

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.

Structural Basis of Membrane Protein Chaperoning through the Mitochondrial Intermembrane Space

The exchange of metabolites between the mitochondrial matrix and the cytosol depends on β-barrel channels in the outer membrane and α-helical carrier proteins in the inner membrane. The essential translocase of the inner membrane (TIM) chaperones escort these proteins through the intermembrane space, but the structural and mechanistic details remain elusive. We have used an integrated structural biology approach to reveal the functional principle of TIM chaperones. Multiple clamp-like binding sites hold the mitochondrial membrane proteins in a translocation-competent elongated form, thus mimicking characteristics of co-translational membrane insertion. The bound preprotein undergoes conformational dynamics within the chaperone binding clefts, pointing to a multitude of dynamic local binding events. Mutations in these binding sites cause cell death or growth defects associated with impairment of carrier and β-barrel protein biogenesis. Our work reveals how a single mitochondrial "transfer-chaperone" system is able to guide α-helical and β-barrel membrane proteins in a "nascent chain-like" conformation through a ribosome-free compartment.

Mechanochemical Model of the Power Stroke of the Single-Headed Motor Protein KIF1A

During the process of ATP binding to an apo-kinesin microtubule (MT), the kinesin core rotates on the MT, and the neck linker (NL) of the kinesin undergoes an undocked to docked transition. This has been suggested to be a power stroke of kinesin, on the basis of the structural analysis. Here, we developed a mesoscopic structure-based model and studied the power stroke of KIF1A. We quantified the underlying free energy landscape and showed the emergence of several states for the power stroke of KIF1A: UB-UR-UD (unbound, unrotating, undock), B-IR-UD (bound, initial rotating, undock), B-PR-UD (bound, partial rotating, undock), and B-R-D (bound, rotating, dock). We found that ATP binding triggered conformational fluctuations of key elements. We also explored the conformational change of key structural elements during the rotation of KIF1A and docking of the NL. In addition, we semiquantitatively and qualitatively estimated the free energy released by the ATP binding, and how much of this remains for the docking of the NL during the power stroke process at different temperatures. Finally, based on results from the thermodynamics landscape and conformational change of structural key elements, we proposed a mechanochemical model of the power stroke of KIF1A.

Quantifying the Intrinsic Conformation Energy Landscape Topography of Proteins with Large-Scale Open-Closed Transition

Large-scale conformational changes of proteins, including the open-closed transitions, are crucial for a variety of protein functions. These open-closed transitions are often associated with ligand binding. However, the understandings of the underlying mechanisms of the conformational changes within proteins during the open-closed transitions are still challenging at present. In this study, we quantified the intrinsic underlying conformational energy landscapes of five different proteins with large-scale open-closed transitions. This is realized by exploring the underlying density of states and the intrinsic conformational energy landscape topography measure Λ. Λ is a dimensionless ratio of conformational energy gap δE versus conformational energy roughness δE and configurational entropy S or size of the intrinsic conformational energy landscape. By quantifying the Λ of intrinsic open-closed conformational (Λ^oc) and intrinsic global folding (Λ^global) energy landscapes, we show that both intrinsic open-closed conformation energy and entropy landscapes are funneled toward the closed state. Furthermore, our results indicate the strong correlations between Λ and thermodynamics (conformational state transition temperature against trapping temperature) as well as between Λ and kinetics (open-closed kinetic time) of these proteins. This shows that the intrinsic conformational landscape topography determines both the conformational thermodynamic stability and kinetic speed of the conformational dynamics. Our investigations provide important insights for understanding the fundamental mechanisms of the protein conformational dynamics in a physical and global way.

Investigation of sliding DNA clamp dynamics by single-molecule fluorescence, mass spectrometry and structure-based modeling

Proliferating cell nuclear antigen (PCNA) is a trimeric ring-shaped clamp protein that encircles DNA and interacts with many proteins involved in DNA replication and repair. Despite extensive structural work to characterize the monomeric, dimeric, and trimeric forms of PCNA alone and in complex with interacting proteins, no structure of PCNA in a ring-open conformation has been published. Here, we use a multidisciplinary approach, including single-molecule Förster resonance energy transfer (smFRET), native ion mobility-mass spectrometry (IM-MS), and structure-based computational modeling, to explore the conformational dynamics of a model PCNA from Sulfolobus solfataricus (Sso), an archaeon. We found that Sso PCNA samples ring-open and ring-closed conformations even in the absence of its clamp loader complex, replication factor C, and transition to the ring-open conformation is modulated by the ionic strength of the solution. The IM-MS results corroborate the smFRET findings suggesting that PCNA dynamics are maintained in the gas phase and further establishing IM-MS as a reliable strategy to investigate macromolecular motions. Our molecular dynamic simulations agree with the experimental data and reveal that ring-open PCNA often adopts an out-of-plane left-hand geometry. Collectively, these results implore future studies to define the roles of PCNA dynamics in DNA loading and other PCNA-mediated interactions.

Revealing dynamically-organized receptor ion channel clusters in live cells by a correlated electric recording and super-resolution single-molecule imaging approach

The N-methyl-d-aspartate (NMDA) receptor ion-channel is activated by the binding of ligands, along with the application of action potential, important for synaptic transmission and memory functions. Despite substantial knowledge of the structure and function, the gating mechanism of the NMDA receptor ion channel for electric on-off signals is still a topic of debate. We investigate the NMDA receptor partition distribution and the associated channel's open-close electric signal trajectories using a combined approach of correlating single-molecule fluorescence photo-bleaching, single-molecule super-resolution imaging, and single-channel electric patch-clamp recording. Identifying the compositions of NMDA receptors, their spatial organization and distributions over live cell membranes, we observe that NMDA receptors are organized inhomogeneously: nearly half of the receptor proteins are individually dispersed; whereas others exist in heterogeneous clusters of around 50 nm in size as well as co-localized within the diffraction limited imaging area. We demonstrate that inhomogeneous interactions and partitions of the NMDA receptors can be a cause of the heterogeneous gating mechanism of NMDA receptors in living cells. Furthermore, comparing the imaging results with the ion-channel electric current recording, we propose that the clustered NMDA receptors may be responsible for the variation in the current amplitude observed in the on-off two-state ion-channel electric signal trajectories. Our findings shed new light on the fundamental structure-function mechanism of NMDA receptors and present a conceptual advancement of the ion-channel mechanism in living cells.

Multiple Pathways and Time Scales for Conformational Transitions in apo-Adenylate Kinase

The open/close transition in adenylate kinase (AK) is regarded as a representative example for large-scale conformational transition in proteins, yet its mechanism remains unclear despite numerous experimental and computational studies. Using extensive (∼50 μs) explicit solvent atomistic simulations and Markov state analysis, we shed new lights on the mechanism of this transition in the apo form of AK. The closed basin of apo AK features an open NMP domain while the LID domain closes and rotates toward it. Therefore, although the computed structural properties of the closed ensemble are consistent with previously reported FRET and PRE measurements, our simulations suggest that NMP closure is likely to follow AMP binding, in contrast to the previous interpretation of FRET and PRE data that the apo state was able to sample the fully closed conformation for "ligand selection". The closed state ensemble is found to be kinetically heterogeneous; multiple pathways and time scales are associated with the open/close transition, providing new clues to the disparate time scales observed in different experiments. Besides interdomain interactions, a novel mutual information analysis identifies specific intradomain interactions that correlate strongly to transition kinetics, supporting observations from previous chimera experiments. While our results underscore the role of internal domain properties in determining the kinetics of open/close transition in apo AK, no evidence is observed for any significant degree of local unfolding during the transition. These observations about AK have general implications to our view of conformational states, transition pathways, and time scales of conformational changes in proteins. The key features and time scales of observed transition pathways are robust and similar from simulations using two popular fixed charge force fields.

Exploration of Multistate Conformational Dynamics upon Ligand Binding of a Monomeric Enzyme Involved in Pyrophosphoryl Transfer

HPPK (6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase) is a monomeric protein with 158 residues, which undergoes large-scale conformational changes between apo, open, and holo states responding to ligand binding for its function. It has been explored widely as an excellent target for potential antibacterial drug development. However, little is known about how conformational dynamics between the native states influences the substrate recognition and the functionality of enzymatic catalysis. Here, we report a coarse-grained triple-basin structure-based model upon ligand binding to describe such multiple-state system by the molecular dynamics simulation. With our model, we have made theoretical predictions that are in good agreement with the experimental measurements. Our results revealed the intrinsic conformational fluctuations between apo and open states without ligand binding. We found that HPPK can switch to the activated holo state upon the ordered binding of the two ligands (ATP and HP). We uncovered the underlying mechanism by which major induced fit and minor population shift pathways coexist upon ligand binding by quantitative flux analysis. Additionally, we pointed out the structural origin for the conformational changes and identified the key residues as well as contact interactions. We further explored the temperature effect on the conformational distributions and pathway weights. It gave strong support that higher temperatures promote population shift, while the induced fit pathway is always the predominant activation route of the HPPK system. These findings will provide significant insights of the mechanisms of the multistate conformational dynamics of HPPK upon ligand binding.

Binding mechanism and dynamic conformational change of C subunit of PKA with different pathways

The catalytic subunit of PKA (PKAc) exhibits three major conformational states (open, intermediate, and closed) during the biocatalysis process. Both ATP and substrate/inhibitor can effectively induce the conformational changes of PKAc from open to closed states. Aiming to explore the mechanism of this allosteric regulation, we developed a coarse-grained model and analyzed the dynamics of conformational changes of PKAc during binding by performing molecular dynamics simulations for apo PKAc, binary PKAc (PKAc with ATP, PKAc with PKI), and ternary PKAc (PKAc with ATP and PKI). Our results suggest a mixed binding mechanism of induced fit and conformational selection, with the induced fit dominant. The ligands can drive the movements of Gly-rich loop as well as some regions distal to the active site in PKAc and stabilize them at complex state. In addition, there are two parallel pathways (pathway with PKAc-ATP as an intermediate and pathway PKAc-PKI as an intermediate) during the transition from open to closed states. By molecular dynamics simulations and rate constant analyses, we find that the pathway through PKAc-ATP intermediate is the main binding route from open to closed state because of the fact that the bound PKI will hamper ATP from successful binding and significantly increase the barrier for the second binding subprocess. These findings will provide fundamental insights of the mechanisms of PKAc conformational change upon binding.

Molecular dynamics simulation reveals how phosphorylation of tyrosine 26 of phosphoglycerate mutase 1 upregulates glycolysis and promotes tumor growth

Phosphoglycerate mutase 1 (PGAM1) catalyzes the eighth step of glycolysis and is often found upregulated in cancer cells. To test the hypothesis that the phosphorylation of tyrosine 26 residue of PGAM1 greatly enhances its activity, we performed both conventional and steered molecular dynamics simulations on the binding and unbinding of PGAM1 to its substrates, with tyrosine 26 either phosphorylated or not. We analyzed the simulated data in terms of structural stability, hydrogen bond formation, binding free energy, etc. We found that tyrosine 26 phosphorylation enhances the binding of PGAM1 to its substrates through generating electrostatic environment and structural features that are advantageous to the binding. Our results may provide valuable insights into computer-aided design of drugs that specifically target cancer cells with PGAM1 tyrosine 26 phosphorylated.

Molecular mechanism of multispecific recognition of Calmodulin through conformational changes

Calmodulin (CaM) is found to have the capability to bind multiple targets. Investigations on the association mechanism of CaM to its targets are crucial for understanding protein-protein binding and recognition. Here, we developed a structure-based model to explore the binding process between CaM and skMLCK binding peptide. We found the cooperation between nonnative electrostatic interaction and nonnative hydrophobic interaction plays an important role in nonspecific recognition between CaM and its target. We also found that the conserved hydrophobic anchors of skMLCK and binding patches of CaM are crucial for the transition from high affinity to high specificity. Furthermore, this association process involves simultaneously both local conformational change of CaM and global conformational changes of the skMLCK binding peptide. We found a landscape with a mixture of the atypical "induced fit," the atypical "conformational selection," and "simultaneously binding-folding," depending on the synchronization of folding and binding. Finally, we extend our discussions on multispecific binding between CaM and its targets. These association characteristics proposed for CaM and skMLCK can provide insights into multispecific binding of CaM.

Role of non-native electrostatic interactions in the coupled folding and binding of PUMA with Mcl-1

PUMA, which belongs to the BH3-only protein family, is an intrinsically disordered protein (IDP). It binds to its cellular partner Mcl-1 through its BH3 motif, which folds upon binding into an α helix. We have applied a structure-based coarse-grained model, with an explicit Debye-Hückel charge model, to probe the importance of electrostatic interactions both in the early and the later stages of this model coupled folding and binding process. This model was carefully calibrated with the experimental data on helical content and affinity, and shown to be consistent with previously published experimental data on binding rate changes with respect to ionic strength. We find that intramolecular electrostatic interactions influence the unbound states of PUMA only marginally. Our results further suggest that intermolecular electrostatic interactions, and in particular non-native electrostatic interactions, are involved in formation of the initial encounter complex. We are able to reveal the binding mechanism in more detail than is possible using experimental data alone however, and in particular we uncover the role of non-native electrostatic interactions. We highlight the potential importance of such electrostatic interactions for describing the binding reactions of IDPs. Such approaches could be used to provide predictions for the results of mutational studies.

Enzymatic Activity and Thermodynamic Stability of Biliverdin IXβ Reductase Are Maintained by an Active Site Serine

Biliverdin reductase IXβ (BLVRB) is a crucial enzyme in heme metabolism. Recent studies in humans have identified a loss-of-function mutation (Ser111Leu) that unmasks a fundamentally important role in hematopoiesis. We have undertaken experimental and thermodynamic modeling studies to provide further insight into the role of the cofactor in substrate accessibility and protein folding properties regulating BLVRB catalytic mechanisms. Site-directed mutagenesis with molecular dynamic (MD) simulations establish the critical role of NAD(P)H-dependent conformational changes on substrate accessibility by forming the "hydrophobic pocket", along with identification of a single key residue (Arg35) modulating NADPH/NADH selectivity. Loop80 and Loop120 block the hydrophobic substrate binding pocket in apo BLVRB (open), whereas movement of these structures after cofactor binding results in the "closed" (catalytically active) conformation. Both enzymatic activity and thermodynamic stability are affected by mutation(s) involving Ser111, which is located in the core of the BLVRB active site. This work 1) elucidates the crucial role of Ser111 in enzymatic catalysis and thermodynamic stability by active site hydrogen bond network; 2) defines a dynamic model for apo BLVRB extending beyond the crystal structure of the binary BLVRB/NADP⁺ complex; 3) provides a structural basis for the "encounter" and "equilibrium" states of the binary complex, which are regulated by NAD(P)H.

Probing conformational dynamics of an enzymatic active site by an in situ single fluorogenic probe under piconewton force manipulation

Unraveling the conformational details of an enzyme during the essential steps of a catalytic reaction (i.e., enzyme-substrate interaction, enzyme-substrate active complex formation, nascent product formation, and product release) is challenging due to the transient nature of intermediate conformational states, conformational fluctuations, and the associated complex dynamics. Here we report our study on the conformational dynamics of horseradish peroxidase using single-molecule multiparameter photon time-stamping spectroscopy with mechanical force manipulation, a newly developed single-molecule fluorescence imaging magnetic tweezers nanoscopic approach. A nascent-formed fluorogenic product molecule serves as a probe, perfectly fitting in the enzymatic reaction active site for probing the enzymatic conformational dynamics. Interestingly, the product releasing dynamics shows the complex conformational behavior with multiple product releasing pathways. However, under magnetic force manipulation, the complex nature of the multiple product releasing pathways disappears and more simplistic conformations of the active site are populated.

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7-15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4-3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its "parents" up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5-2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions.

Mapping the Dynamics Landscape of Conformational Transitions in Enzyme: The Adenylate Kinase Case

Conformational transition describes the essential dynamics and mechanism of enzymes in pursuing their various functions. The fundamental and practical challenge to researchers is to quantitatively describe the roles of large-scale dynamic transitions for regulating the catalytic processes. In this study, we tackled this challenge by exploring the pathways and free energy landscape of conformational changes in adenylate kinase (AdK), a key ubiquitous enzyme for cellular energy homeostasis. Using explicit long-timescale (up to microseconds) molecular dynamics and bias-exchange metadynamics simulations, we determined at the atomistic level the intermediate conformational states and mapped the transition pathways of AdK in the presence and absence of ligands. There is clearly chronological operation of the functional domains of AdK. Specifically in the ligand-free AdK, there is no significant energy barrier in the free energy landscape separating the open and closed states. Instead there are multiple intermediate conformational states, which facilitate the rapid transitions of AdK. In the ligand-bound AdK, the closed conformation is energetically most favored with a large energy barrier to open it up, and the conformational population prefers to shift to the closed form coupled with transitions. The results suggest a perspective for a hybrid of conformational selection and induced fit operations of ligand binding to AdK. These observations, depicted in the most comprehensive and quantitative way to date, to our knowledge, emphasize the underlying intrinsic dynamics of AdK and reveal the sophisticated conformational transitions of AdK in fulfilling its enzymatic functions. The developed methodology can also apply to other proteins and biomolecular systems.

Molecular simulations of substrate release and coupled conformational motions in adenylate kinase

Conformational opening coupled substrate release is believed to be related to the rate limiting step in the catalysis cycle of the adenylate kinase. However, it is still unclear how the substrate dissociates from its active site and how the substrate release is coupled to conformational changes of the kinase. In this work, by using metadynamics simulations, we investigated the ADP release process and the coupled protein dynamics. We found that the ADP release involves overcoming a high free energy barrier, and protonation of the [Formula: see text]-phosphate of the ADP molecules can drastically reduce the barrier height, therefore, promote the ADP release. We identified several key residues contributing to the high free energy barrier. We also showed that the ADP attached to LID domain leaves the binding pocket earlier than the one attached to the NMP domain. We further observed that the ADP release is accompanied by almost fully opening of the LID domain and partially opening of the NMP domain. Our results provide insight into the molecular mechanism of the substrate release of adenylate kinase and the coupled conformational motions.

Domain Motion Enhanced (DoME) Model for Efficient Conformational Sampling of Multidomain Proteins

Large conformational changes of multidomain proteins are difficult to simulate using all-atom molecular dynamics (MD) due to the slow time scale. We show that a simple modification of the structure-based coarse-grained (CG) model enables a stable and efficient MD simulation of those proteins. "Motion Tree", a tree diagram that describes conformational changes between two structures in a protein, provides information on rigid structural units (domains) and the magnitudes of domain motions. In our new CG model, which we call the DoME (domain motion enhanced) model, interdomain interactions are defined as being inversely proportional to the magnitude of the domain motions in the diagram, whereas intradomain interactions are kept constant. We applied the DoME model in combination with the Go model to simulations of adenylate kinase (AdK). The results of the DoME-Go simulation are consistent with an all-atom MD simulation for 10 μs as well as known experimental data. Unlike the conventional Go model, the DoME-Go model yields stable simulation trajectories against temperature changes and conformational transitions are easily sampled despite domain rigidity. Evidently, identification of domains and their interfaces is useful approach for CG modeling of multidomain proteins.

The Atomistic Mechanism of Conformational Transition of Adenylate Kinase Investigated by Lorentzian Structure-Based Potential

We present a new all-atom structure-based method to study protein conformational transitions using Lorentzian attractive interactions based on native structures. The variability of each native contact is estimated based on evolutionary information using a machine learning method. To test the validity of this approach, we have investigated the conformational transition of adenylate kinase (ADK). The intrinsic boundedness of the Lorentzian attractive interactions facilitated frequent conformational transitions, and consequently we were able to observe more than 1000 structural interconversions between the open and closed states of ADK out of a total of 6 μs MD simulations. ADK has three domains: the nucleoside monophosphate (NMP) binding domain, the LID-domain, and the CORE domain, which catalyze the interconversion between ATP and ADP. We identified two transition states: a more frequent LID-closed-NMP-open (TS1) state and a less frequent LID-open-NMP-closed (TS2) state. The transition was found to be symmetric in both directions via TS1. We also obtained an off-pathway metastable state that was previously observed with physics-based all-atom simulations but not with coarse-grained models. In the metastable state, the LID domain was slightly twisted and formed contacts with the NMP domain. Our model correctly identified a total of 14 out of the top 16 residues with highest fluctuation by NMR experiment, thus showing excellent agreement with experimental NMR relaxation data and overwhelmingly better results than existing models.

Energetics and structural characterization of the large-scale functional motion of adenylate kinase

Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.